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January 2013

1. 1 Use the Select a prediction type drop menu to specify the type of results you want Fig IIl B 13 The options are a BME Mode the mode of the prediction posterior PDF at each output grid node b BME Moments the mean variance and skewness coefficient of the prediction posterior PDF at each output grid node c BME PDF the complete prediction posterior PDF at each output grid node d BME Confidence Intervals the complete prediction posterior PDF and the user specified percentile confidence interval at each output grid node The above options are ranked with respect to the time required for the computations starting with the fastest one and ending with the most time consuming gt To start BME prediction you must first select a prediction type gt With the exception of the BME Mode computation type each one of the gradually slower selections c and d above provides all of the information given by the previous faster ones BME Mode results cannot be extracted from the information in b c or d You can obtain all possible BME prediction outcomes by performing both the BME Mode and CI tasks BME Prediction Wizard 6 BME PREDICTION ge performs the computations for BME prediction Please choose from one of the available prediction types set any available options and patiently wait for the outcome notification If a data transformation has been applied the output is automatically back transformed If you already have
2. 2 B Instructions 1 The left hand side of the screen displays statistics about the data Fig III B 1 Depending on the presence of hard and or soft data these statistics are based on the hard data and the soft data approximations and refer to the whole data set Statistics of subsets at individual temporal instances in the spatiotemporal case are unavailable You choose from the drop down menu whether the non detrended Non D or the detrended Detrended data set statistics are displayed The latter are available only after a mean trend has been estimated or after you have loaded a file with previously saved mean trend information about the current data set see step 3 below gt f you request statistics that are unavailable then the data statistics boxes display the message N A gt Data statistics are only available for display of values and cannot be edited Exploratory Analysis 4 DATA EXPLORATORY ANALYSIS Part Il of Ill Data Distribution and Detrending Soft Data are mapped below using the mid point value if in category A or their PDF mean categories B H An estimate of the variable s mean trend is extracted from the data by means of a Gaussian kernel smoothing No trend Data MAT file present gt o c E c o ic Main Menu lt lt ck gt gt BMElib Help Fig III B 1 2 If you are visiting this screen for the first time in a study specify the desired maximum search radius
3. 4 Covariance Analysis 5 COVARIANCE ANALYSIS SEKS GUI describes the variability of the Random Field in this study by means of covariance models Part of Il Empirical Covariance From Data To begin with please load existing data or specify characteristics and push the Get Empirical button You can adjust the number of computed points by modifying the range and lag parameters psn Cm NEL Al directions Data available for anisotropy option Al dir eee ia m All directions Empirical Max S Correlation Range S Lags Covariance Plot Empirical Covariance Al External figure You can save data in file s after individual anisotropy calculations or all at once after the last calculation Sag in s units T4ag in t units Main Menu Back Next gt gt BMElib Help Fig IIl B 9a Covariance Analysis 5 COVARIANCE ANALYSIS SEKS GUI describes the variability of the Random Field in this study by means of covanance models Part of Il Empirical Covariance From Data To begin with please load existing data or specify characteristics and push the Get Empirical button You can adjust the number of computed points by modifying the range and lag parameters Anisotropy Covariance in Ali directions Plotting stored data for this choice All directions Empirical Max S Correlation Range S Lags Covariance Plot Empirical Covariance All
4. Part Il 1 Push the Browse for Soft Data file button to locate your SD file Keep in mind the considerations of Paragraph III B 2 about eligible formats for soft data files in SEKS GUI Be prepared to navigate to the folder where your soft data file is stored and then select the desired file After a successful choice the data filename appears in the message area next to the Browse button Fig IIl A 11 shows an example where a file with Gaussian SD is specified gt Ensure you have a valid SD file at hand as instructed in Paragraph II B 2 earlier SEKS GUI can only perform a rudimentary check on the file content and warn the user about possible inconsistencies before taking the next step It is up to the user to provide a suitable input file Also be cautious to provide accurate information because SEKS GUI cannot guess from raw input what plain numbers may stand for gt f the Cancel button is pushed during navigation then no SD file is selected and a related message appears gt Ifa SD file is already chosen and the Browse button is pushed again and further the action gets cancelled using Cancel then the file formerly selected is cleared from memory and needs to be entered again using the Browse button gt f you return to this screen from a following one the SD filename info is kept in memory 2 IMPORT SOFT DATA WIZARD Gaussian PDF Part Il of Il You chose to use Soft Data SD al
5. gt Ensure you have a valid HD file at hand as instructed in Paragraph Il B 1 earlier SEKS GUI can only perform a nd DA seomsthattisan ascitestic rudimentary check on the file TERES SE HONESTOS content and warn the user about possible inconsistencies Possibly wrong file format before taking the next step ASCII text Excel format GecEAS format Fig Ill A 6 It is up to the user to provide a suitable input N file Also be cautious to provide accurate information Fig III A 6 because SEKS GUI cannot guess from raw input what plain numbers may stand for gt f the Cancel button is pushed during navigation then no HD file is selected and a related message appears gt If a HD file is already chosen and the Browse button is pushed again and further the action gets cancelled using Cancel then the file formerly selected is cleared from memory and needs to be entered again using the Browse button gt f you return to this screen form a following one then the HD filename is kept in memory 3 Is this a spatial only investigation If yes select the Space Only domain option If the button is pushed again then it is deselected The default is a deselected button and implies a spatiotemporal analysis gt A mistaken choice may cause errors and inconsistencies with the data at a later point Part of Il The Hard Data HD you wil be using needs to be provided in a file SEKS GUI acce
6. 11 The grid information in a file can be only one of the following types Grid limits and spacing between nodes in each dimension Grid limits and number of nodes in each dimension Lower grid limit origin number of nodes and node spacing in each dimension Coordinate information for an arbitrary number of nodes To show examples of grid specification by using the information types a c assume the imaginary spatiotemporal grid illustrated in Fig Il B 8 This grid features nx 4 nodes in the x axis ny 3 nodes in the y axis and nt 2 nodes in the f ymax temporal axis In addition the grid ranges from tmax LL AA xmin to xmax in the x direction from ymin to ymax dt S L A A in the y direction and from tmin to tmax in the tmin ymin temporal continuum Also for each of these xmin dx xmax directions the node spacing is dx dy and dt Fig II B 8 respectively Then you can specify this prediction output grid in any of the following ways Example 1 If you want to define the grid by providing type a information specify a text file that contains corresponding information in the following manner xmin dx xmax ymin dy ymax tmin dt tmax Example 2 If you want to define the grid by providing type b information specify a text file that contains corresponding information in the following manner xmin xmax nx ymin ymax ny tmin tmax nt Example 3 If you want to define the grid by providing ty
7. Extemal figure You can save data in file s after individual anisotropy calculations or all at once after the last calculation Lag in s units Main Menu lt lt Back Next gt gt BMElib Help Fig IIIl B 9b 42 If data for a request are unavailable a message appears in the message box on the screen Use the External figure button to display future plot requests in an external independent window when activated or to return to the in screen display when de activated gt When the External figure button is activated it enables complete control of the plot by making use of Matlab tools e g axes rotation renaming etc Also this feature enables you to print the particular figure using the independent window menu For more information on handling plots in separate figure windows see Matlab Help 8 When done push the Next button to proceed 43 Ill B 2 2 BME Covariance Analysis Screen Part II This screen Fig IIl B 10 guides you to fit a covariance model to the empirical covariance information you obtained in the previous screen This model may consist of one single pair of spatial and temporal model components or it may be a nested model of more than one such pair of components You can add as many pairs of components as you want The current version of SEKS GUI supports a model fitting approach based on visual inspection rather than an automated one such as a least squares fit To
8. GUlexamples 1 BME S T study of Total Ozone concentrations across the United States 1 All the information regarding this study is located in the folder GUlexamples 001 TotalOzoneUSstudy ST Please navigate Matlab into this folder first when requesting the input output files in the following 2 Start Matlab and SEKS GUI and when prompted for information at the appropriate screens provide the following files and input BME analysis The task choice in the Choose a Task screen is BME Spatiotemporal Analysis Highlight the task and push the Start button to continue Hard Data Use Ozone 1 Input HD txt in ASCII text format This study is in the space time domain Longitude x Axis in degrees is in data file column 1 Latitude y Axis in degrees is in data file column 2 Day temporal reference date in July 1988 in z Axis is in data file column 3 Ozone concentrations in Dobson Units are in data file column 4 ooft Data There are Gaussian PDF soft data in Ozone 2 Input SDGaussianPDF txt in ASCII text format and appropriately formatted as follows Longitude x Axis in degrees in data file column 1 Latitude y Axis in degrees in data file column 2 Day temporal reference date in July 1988 in z Axis in data file column 3 Mean of Ozone concentrations soft PDF in Dobson Units in data file column 4 Variance of Ozone concentrations soft PDF in Dobson Units in data file column 5 62 O
9. gt gt BMEib Help Fig lll B 8a Covariance Analysis 5 COVARIANCE ANALYSIS SEKS GUI describes the variability of the Random Field in this study by means of covanance models Part of Il Empirical Covariance From Data To begin with please load existing data or specify characteristics and push the Get Empirical button You can adjust the number of computed points by modifying the range and lag parameters Anisotropy Covanance in Load data Get Empirical Compute the empirical covariance first Max S Correlation Range S Lags 392 6161 Max T Correlation Range N A Plot Empirical Covariance All Extemal figure You can save data in file s after individual anisotropy calculations or all at once after the last calculation MainMenu lt lt Back Next gt gt BMEIb Help Fig IIIl B 8b 40 gt SEKS GUI prevents negative entries in the range boxes and allows entry values of arbitrarily high size To prevent specification of unlikely values by mistake SEKS GUI produces a message when your entry is in excess of your space time domain physical size as follows A warning is produced if the spatial range entry exceeds beyond 150 the distance between the data furthest apart in any spatial direction also a warning is produced if the temporal range entry exceeds beyond 150 the maximum data temporal span the temporal feature is not applicable in the purely spatial case gt n spat
10. is completed by saving the results you actually save all output to that point since visiting the BME prediction screen To save BME prediction results you can alternatively push the Save output button as explained in the following step 9 9 Push the Save output button to store the BME prediction results in a file It is strongly recommended that you save your results in suitably named files as you may later wish to return or re run a study The data are saved in a Matlab format which has the ending mat in the folder you specify and cannot be viewed independently unless they are loaded within the Matlab environment gt You can run multiple prediction tasks and then push the Save output button to store all prediction results to this point in a single file gt f you leave the screen without saving BME prediction results may be lost upon returning to this screen You can only save these results while you are at the present screen gt For computations with large data keep in mind that Matlab retains all prediction results in the background Whether you save it or not this information can accumulate and temporarily occupy disk space until you quit Matlab 10 When done push the Next button to proceed to the visualizations For instructions on this screen proceed to Section III D 53 Section III C Visualization in SEKS GUI IIl C 1 Visualization Screen SEKS GUI offers a bundle of mapping options
11. Box Cox transformation has been applied to detrended data the message box shows the value of the parameter A that was specified for the transformation see the discussion in the Introduction part of Paragraph III B 1 2 Visualization Wizard 7 VISUALIZATION c orrian me m nEeD a n 4 nic c n m u In this screen you can create a vanety of plots us ng ine SEKS GUI prediction output If you arrived at this screen after the prediction stage the display below indicates what information is available for visualization If you selected this screen directly from the SEKS GUI main menu please start by loading a SEKS GUI output file from a previous analy etrended results allowed range 64 5534 109 5627 Main Menu lt lt BMElib Help Fig IIl C 7 60 8 A more advanced feature for map presentations is plot masking which requires some knowledge of Matlab programming This is a useful feature if you would like to show the results that appear in part of your output area e g by masking out the portion of a map outside the borders of a country It is a more advanced operation because it requires that you provide a Matlab m code file with the masking information lf you can program in Matlab you can create a map that produces the desired mask over the output grid area by using suitable coordinates See also Paragraph V 3 in this manual for a basic utility provided with SEKS GUI to assist you in mask creation Keeping this in
12. CDF red line in plot against the normal CDF of mean 0 and variance 1 blue dashed line in plot e Comparison of the detrended Box Cox space data CDF red line in plot against the normal CDF defined by the detrended Box Cox space data mean and variance blue dashed line in plot e Histogram of the detrended non transformed data distribution as in the previous screen e Histogram of the detrended N score space data distribution Fig III B 7 e Histogram of the detrended Box Cox space data distribution Use the Bars drop menu to plot the histogram plots with more or fewer bars as desired Use the External figure button to display future plot requests in an external independent window when activated or to return to the in screen display when de activated gt When the External figure button is activated it enables complete control of the plot by making use of Matlab plot tools e g axes rotation renaming etc Also this feature enables you to print the particular figure using the independent window menu For more information on handling plots in separate figure windows see Matlab Help Exploratory Analysis 4 DATA EXPLORATORY ANALYSIS Part Ill of Ill Data Distribution and Transformation distributed data The detrended info is now screened for normality 1 PET zx eee ae ihosis or a Box Cox transformation before proceed ng further Use N scores If transformation is applied data wil be au
13. You can repeatedly load files with prediction information from different investigations 54 Visualization Wizard 7 VISUALIZATION n this s Ill you can create a variety of plots using the SEKS GUI prediction output t ediction stage the display below indicates what information is available for visualization ted this screen directly from the SEKS GUI main menu please start by loading a SEKS GUI output file from a previous analysis screen yo screen after the pred Load SEKS GUI output file Main Menu lt lt ck i BMElib Help Fig IIl C 2 3 Once prediction output data are available to the SEKS GUI you can choose from a series of maps from the drop down menu under Map Displayed Fig IIl C 2 Depending on the available results choose at any time to view one of the following maps the type of results necessary for the particular map is printed in italic The mean of the prediction posterior PDF at each output grid node see Fig Ill C 3 BME Moments PDF or Confidence Interval results required The mode of the prediction posterior PDF at each output grid node BME Mode results required The prediction error variance the variance of the prediction posterior PDF at each output grid node BME Moments PDF or Confidence Interval results required The prediction standard deviation the standard deviation of the prediction posterior PDF at each output grid node BME Moments PDF or Confidence Interval resu
14. after following step 8 above Upon successfully loading a suitable file the saved model details show in the corresponding boxes of the screen and the model plot is displayed in the plot area of the screen gt t is up to the user to provide a suitable input file Also be cautious to provide accurate information because SEKS GUI cannot guess from raw input what plain numbers may stand for If you load a wrong file by mistake try repeating again the process in this step If this does not work then repeat the covariance analysis steps by pushing the Back button to return to the previous screen 10 When done push the Next button to proceed gt You must specify a covariance model to fit your empirical covariance before you can proceed to the following screen gt The sum of sills must not exceed 1 in your model Otherwise SEKS GUI cannot proceed to the following screen until you modify the sill parameter to satisfy this condition eoo Ozone 6 CovarianceModellnfo Nsc txt SPATIOTEMPORAL MODEL TYPE Sill Pari Par2 Pars sphericalC exponentialcC 4 5588 14 6668 32 6668 exponentialC sphericalC 4 4588 5 8688 2 70808 Fig IIl B 12a eoo Arsenic 6 CovarianceModellnfo Nsc txt SPATIAL MODEL TYPE Sill Pari Par2 nuggetc 4 7568 sphericalt 4 2568 45 6688 Fig IIl B 12b 48 Ill B 3 BME Prediction Screen In this screen you can select and initialize the type of BME prediction to be performed by SEKS GUI
15. button is pushed again and further the action gets cancelled using Cancel then the file formerly selected is cleared from memory and needs to be entered again using the Browse button gt If you return to this screen from a following one the output info filename info is kept in memory Output Configuration 3 OUTPUT GRID WIZARD sked to provide an ASCII text or an Excel file with the grid specifications hould occupy one line in the file In Excel values for each dimension d m A m mw mam a PFY mmm mam s in the ine ASCII text files must contain space separated values Example In a 3 D case where the desired output gn as shown in the figure ymax nes uipu d s P am A 1 A A m mes mum A the proper menu choice is A An ASCII text file shouk ih tha Se ee 2 Se Se Seas E vain ihe numbers correspondang to ihe vanabies as positioned below Main Menu lt lt ck gt gt BMElib Help Fig III A 13 3 In the bottom part of the screen you are prompted to state whether the attribute in your study can take negative values or not SEKS GUI automatically scans the input information to provide an initial answer based on whether the user data contain negative numbers or not However if you know the attribute can span into negative values then specify this information explicitly by selecting the No button SEKS GUI uses this response to prevent predicted distributions of positive only a
16. cece eee eeaeeeeeeeeaeenes 39 2 2 BME Covariance Analysis Screen Part Il cece cece cece e eee eee eeeeeeenes 44 o BME Prediction SC elei i Det Gd cece inet td deaedieueen eater Ae edu used uta EE ee 49 Section III C Visualization In 9e EI SOUL tr t Ede He et ERE E dein cheer ovest eame dea tcl 54 Ax Visualization SCEN ose cue mit tnd eta a ence tenia E A 54 PART IV SENS OUILEXAMPLEESdootetmeE tieeelncc Mysuss induta ute EA R m ieisemott tes Pede Fetish uteisd sess 62 1 BME S T study of Total Ozone concentrations over the United States 62 2 BME Spatial study of Arsenic in Bangladesh drinking water ssssssse 64 PART V SEKS GUI UTILITIES INCLUDED IN PACKAQGE eeeeeeeeernmmm mmn 66 1 Data exchange with shapefiles Converting shapefiles into text 66 2 Data exchange with shapefiles Converting text into shapefiles 69 3 A start up set of files for the creation of masking files seeeeeseeesseeseeeessee 72 PART VI AcKnowledgelTielllS esie ane aidewr ute bien s ede ub eduL i Aser uc LAnuMe UE e Io EI E aed due 14 PART VII BIBEIOGIRADPLELDY ete a a Ee rp a vate eee eee wanna cee eee eres 75 PART VIII LIST OF ABBREVIATIONS eset teen tnt enseitehannde ETET 76 il PREFACE Welcome to the Spatiotemporal Epistemic Knowledge Synthesis Graphical User
17. empirical covariance is computed for each such class gt Based on the previous you can compute different values of the empirical covariance depending on the number of distance classes you assume in space and time However the computed covariance values depend on the amount of data neighbors that belong to each one of the lags you specify If no neighbors exist in a particular lag then a warning message appears in the Matlab Command Window to inform you that some space time classes contain no pairs of points This warning does not affect the use of the SEKS GUI as long as you can eventually adjust the parameters to obtain a satisfactory number of empirical covariance points to fit a model on The numbers of spatial and temporal lags to use are reasonably in a balance with the data sample size You are advised to proceed with caution at this point A good knowledge of your data and experimentation with the parameters for the correlation length and lag number can provide you with valuable insight for the purpose of computing the empirical covariance For the creation of the covariance model in stage b choose up to 2 individual models to nest in each other from a selection of permissible covariance functions and then adjust the covariance parameters for each of the selected nested models to achieve an optimal visual fit These parameters are the covariance sill and range The sill is the maximum value the model variance can take if you specify mo
18. fourth column attribute value 68 2 Data exchange with shapefiles Converting text into shapefiles Using this tool enables you to convert an ASCII textfile containing point data such as the input or output of SEKS GUI into Esri ArcMap s shapefile format Essentially this tool first creates a point layer based on X and Y coordinates and then transforms this layer to a shapefile Requirements For the conversion of a text file into a shapefile you will need the following 1 A text file that contains at least X and Y spatial coordinates of data that you want to put in the shapefile Each line must contain an entry for 1 datum and the coordinates must be consistent in all entries e g longitudes in 1 column latitudes in 2 column values in 3 column Spatiotemporal data may contain also temporal coordinates You need to know where this information is located in the text file and whether you want any such additional information to be included in the shapefile 2 The file named text2shape mxd is included in the SEKS GUI package and is located in the folder SEKS GUIv1 X X guiLibs Utilities 3 The Esri ArcGIS software or any other software that can perform this task The following example describes the process using ArcMap within ArcGIS Instructions 1 Create a folder on your computer where you wish to place the shapefile and associated files 2 o set things up open ArcMap select File Open from the menu bar an
19. in the original space b N scores transformation also known as Normal Scores or Gaussian Anamorphosis Olea 1999 The detrended data set is transformed to follow a Gaussian distribution of zero 0 mean and variance equal to 1 The transformed data values that will be used for prediction are in the N score space Back transformation is enabled by means of the transformation N score matrix that establishes corresponding values between the original space and the N score space lt is possible that some extreme values in prediction may not back transform correctly when using the N score matrix SEKS GUI addresses this issue by using the following commonly used technique Upper and lower value bounds are set in the transformation These bounds are set individually for each investigation depend on the data span in the particular study and provide a cushion on which possibly extreme predictions can back transform into the original space All of the above actions are performed automatically in SEKS GUI and are seamless to the user c Box Cox transformation The detrended data set is tested with a series of power transformations based on a parameter A that typically ranges in 2 2 The transformation eventually uses the value of A that brings the data distribution closest to a Gaussian one If A 0 then the Box Cox transformation is defined as the logarithmic transformation The resulting data values that will be used in the predictions are in the B
20. other lines in the same file e g if one line starts with the x coordinate then all lines in the file must start with the x coordinate too Finally you need to know the content of each column in your text file e g x coordinates are in the 1 column Il If you use an Excel file please ensure your information is in the first spreadsheet of the file if there are more than one spreadsheets in the file Values should be stored in neighboring cells and each row should contain information for exactly 1 datum The formatting rules are the same as in the previous case l When it comes to assimilating soft information SEKS GUI is a powerful tool that can accept and process a variety of types categories of soft data Only one type of soft data and one soft data file may be used in the same investigation i e different types cannot be mixed in the same soft data file gt f your study involves more than one soft data types you can convert them to the same single soft data type and store them in one soft data file for use in the investigation In particular types shown in the following in a and b1 can be converted e g into the soft data types exhibited in Examples 5 and 7 shown later in b2 interval soft data are essentially uniform distributions Given any of the fully described distributions presented in a or b1 the user can estimate in advance the distribution probability density p1A p2A pNA at a set of N values 11
21. recommended to have some general prior information in advance about the spatiotemporal correlations of the underlying field Alternatively it is strongly suggested to investigate earlier whether your domain is best examined by considering one correlation scheme throughout the domain or by considering multiple subdomains with an appropriately different correlation for each one of the subdomains In a subsequent step compare the results of the two approaches i e using a single grid with one covariance function versus using multiple subgrids within the same grid each with a covariance function of its own to conclude about the nature of the spatiotemporal correlations in the field The SEKS GUI covariance analysis for BME prediction covers the full extent of the specified output grid see Paragraph III A 8 in two stages as follows a Explore all data pairs on the basis of distances between them n particular classify all pairs in lags of spatial and temporal distances Then compute the empirical also known as sample or experimental covariance value for each one of the distance classes The user specifies how many of these classes to consider in space and time and then computes the empirical covariance in them b Fit a model over the individual empirical covariance points calculated in stage a to obtain an explicit covariance expression in space and time Similarly to the analysis in the detrending stage only single individual values ca
22. same as in previous screen e Detrended N score transformed data D NormSc in the menu e Detrended Box Cox transformed data D BoxCox in the menu Statistics about the transformed data are available because transformations take place before the screen appears In this way all available forms of transformed data are available for comparison so that you can make an optimal choice gt The data statistics are only available for display of values and cannot be edited 2 The message box in the upper part of the screen communicates useful messages and cannot be edited 34 3 Click on the drop down Transformation Menu on the right hand side of the screen to decide the form of data to use at the prediction stage The available options are e No transformation e N score transformation Use N scores in the menu e Box Cox transformation Use BoxCox in the menu gt This is an important selection in your investigation As stated earlier there is no absolute correct answer to your decision Instead one should rather consult the data in each individual study You can always repeat your study using a different transformation type and compare the prediction results in the end if necessary 4 If you select the Box Cox transformation there may be an issue with O values in the detrended data set in the original space The transformation may require calculation of the logarithm of O and this corresponds to o This is numerica
23. specify the grid origin lower limit number of nodes and the constant inter node distance for each of the dimensions used e For option D specify an arbitrary number of locations by means of their coordinates e For option E provide a polygon to obtain predictions inside specify the spatial coordinates of the polygon vertices and inter node distance of the prediction nodes gt Selection or re selection of an input format from the drop down menu will clear any output info file information previously provided by the user to prevent potential errors For that reason the user needs to always perform the current step 1 before proceeding to the following step 2 Output Configuration 3 OUTPUT GRID WIZARD SEKS GUI provides predictions at pre defined spatiotemporal locations In this screen specify these locations as an orthogonal prediction output grid You are now asked to provide an ASCII text or an Excel file with the grid specifications Information for each dimension should occupy one line in the file In Excel values for each dimension must occupy consecutive cells in the ine ASCII text files must contain space separated values 4 Please choose your input fromat from the following options A The file contains grid limits and node spacing lower limit node distance upper imit g ts and nu a e comans gna a a taino rejun oerdd Taon nmi rerio cnacew 5 pogon cooramnaies and node spa g To pup TEM VS er CA eS Oe
24. support to help you resolve the issue PART II INTRODUCTION TO SEKS GUI Section ILA The SEKS GUI Structure SEKS GUI implements the BME methodology for spatiotemporal analysis The following graph is a flowchart of how this analysis works in SEKS GUI SEKS GUI BME SEKS GUI Visualization of Existing SEKS GUI Help Files Spatiotemporal Analysis nto ERE pum Results Yes Specify Hard Import Hard Data Data Format No No data SEKS GUI No Terminated Import Soft Data Yes Specify Soft Data Format Specify Output Grid Check for Co located Data Data Detrending and Exploratory Analysis Option for Data Transformation Spatiotemporal Covariance Estimation BME Prediction Visualizations Section II B What information you need to run SEKS GUI The following information describes what you will need at hand before you begin working with SEKS GUI For your convenience please read the current section before running the software and prepare your material as described in the following guidelines gt f you only wish to test run the program there exist built in full scale examples in the SEKS GUI package so you do not need to have any additional files or information at hand The locations of the example files you will be asked for during execution of the SEKS GUI are provided in PART IV towards the end of this manual SEKS GUI enhances and facilitates your space time analyses by enabling you to use th
25. terminate the computations before the completion of the prediction process you can click on the Matlab Command Window outside the GUI window and subsequently press the sequence of keyboard keys lt CTRL C gt If you do so the Matlab Command Window displays some error messages related to the premature termination of the calculations in the GUI window the progress counter in the message box stops which indicates that prediction is halted gt The prediction progress counter in the message box might come to a halt before the Prediction completed message appears in the message box f error messages appear in the main Matlab Command Window or the counter indicates the task has Stalled then prediction computations have been probably interrupted SEKS GUI cannot inform or warn you explicitly if such an event occurs Sudden prediction interruption is most likely caused by unexpected numerical issues during computations You can try to resolve this issue by attempting to re adjust some prediction parameters Typical reasons for interruption can include 21 BME Prediction Wizard 6 BME PREDICTION ems the computations for BME prediction Please choose from one of the available prediction types set any available options and patiently wait for the outcome notification If a data transformation has been applied the output is automatically back transformed If you already have BME prediction information saved in file you can skip th
26. time These 2 components comprise the spatiotemporal model of choice in the specific example gt Accordingly in the spatial only case your need only specify at least one spatial model component Fig IIl B 11b shows an example where two nested spatial components are specified the first component is a nugget effect and the second component is a spherical model 45 Covariance Analysis 5 COVARIANCE ANALYSIS Part Il of ll Fit a Covariance model In this step you fit a model to the empirical covariance computed in the previous part You can specify a simple model with one component or a nested model with multiple additive separable model components Anisot Covari t Empirical and Modeled Covariances in selected direction otropy anance in All directions Spatial Component Temporal Component Select a Model Select a Model Remove Model spherncalC exponentialC Covariance Paramenter exponentialC sphencalC 0 55 14 Covariance Extemal figure Load model information T4ag in t units Sag in s units lt lt Back Next gt gt BMElb Help Fig II B 11a Covariance Analysis 5 COVARIANCE ANALYSIS Part Il of Il Fita Covariance model In this step you fit a model to the empirical covariance computed in the previous part I You can specify a simple model with one component or a nested model with multiple addi
27. to play with the values provided here and the sill range adjustment tools of the GUI to familiarize better with the interface The BME prediction output is stored in the Arsenic 7 Output BmeModeCI Nsc mat Matlab file The output file contains the results of two tasks namely the BME Mode and the BME Confidence Interval at the 68 percentile prediction tasks For these results a maximum of 50 hard data and 3 soft data have been used also a maximum spatial range of 250 km has been specified to define the prediction neighborhood You can use the output file contents directly by advancing to the Visualization screen or by loading the file at any time within the visualization screen to produce the Arsenic concentration BME study maps 65 PART V SEKS GUI UTILITIES INCLUDED IN PACKAGE 1 Data exchange with shapefiles Converting shapefiles into text The shapefile format is the standard way to manipulate maps in the proprietary ArcGIS software by Esri The SEKS GUI software requires that such information be in text format Below are directions for converting polygon shapefiles and related data for a single attribute into a text file that SEKS GUI can work with using a Python script called shape2text py Requirements 1 A binary Esri ArcGIS shapefile The points in the shapefile are converted by the script into entries points with spatial spatiotemporal coordinates in a text file 2 An attribute text file must be space delimited a
28. A 12A 1NA of the quantity of interest In this way following the guidelines in either of the Examples 5 or 7 below any soft data collection of mixed types can be stored in the same file for use in an investigation Each of the following examples describes one of the different soft data types that can be used with SEKS GUI These include a Interval soft data Information is provided in terms of the lower and upper bounds of each datum whose values may range uniformly anywhere in the given interval Each line in the interval soft data file must contain the datum coordinates followed by the lower interval bound and then followed by the upper interval bound Example xA yA zA 1A uA can be the line content that describes one datum A which is located on a plane at location xA yA at the temporal instance zA and its value has an equal probability of being measured anywhere within the interval 1A uA b Probabilistic soft data Each datum is provided in the form of a probability density function PDF that describes the attribute probability distribution across all of its valid values The PDF may be either fully known by virtue of its characteristics or may be described by the user in terms of individual probabilities assigned to a pre defined number of bins across the PDF span Each line in the interval soft data file must contain the datum coordinates followed by the appropriate description of the attribute input PDF Several differ
29. ATA EXPLORATORY ANALYSIS In the exploratory analysis section SEKS GUI reviews the input yo and helps you make arrangements for the prediction Currently SEKS GUI performs prediction on normally distributed variab In BME analyses this section helps you comply rompted to identify and isolate mean trends Then yo In GBME analyses the above steps are unn Part of Ill Check for Duplicates Data with identical coordinates or that are located too clo considered as coJocated observations Cotocated data can obstruct the covariance analysis in the following SEKS GUI deals with co located data as follows Values of co located Hard Data are averaged Soft Data that are co located with other Hard or Soft Data are slightly disp Yan E NN S esee uc puce COREL RUM i ave ces You are noi required to take any action dunng this step The outcome is provided below Soft Data Main Menu lt lt ck gt gt BMElib Help Fig III A 14 Section III B on the following page guides you on how to continue with BME investigations 26 Section III B BME Analysis Screens in SEKS GUI IIl B 1 BME Exploratory Analysis II B 1 1 BME Data Exploratory Analysis Screen Part II A Introduction BMElib operates correctly on normally distributed residual values of an attribute i e on detrended information that follows a Gaussian distribution The following 2 screens fulfill the objective of bringing your raw input information into the above su
30. BME prediction information saved in file you can skip this screen and proceed to the visualization screen using Next X Select a prediction type ranked by calculation speed BME Mode yields the BME posterior PDF Mode Faster BME Moments computes the BME Mean error variance and skewness Fast BME PDF obtains the full BME posterior PDF Slow BME Confidence Intervals obtains the full BME posterior PDF and Cl Slower Confidence Interval Options Set the probabiity confidence level as desired 151 99th percentile using the sider or the box Closest data to consider Spatiotemporal Ranges and Metric Options Max Hard Data Max Soft Data Max S Range Max T Range S T metric parameter 50 3 14 32 0 4375 Main Menu lt lt ck gt gt BMElib Help Fig IIl B 13 2 The message box on the upper part of screen communicates useful messages and cannot be edited 49 3 If you request the BME Confidence Intervals prediction use the Percentile slider or edit box to adjust the percentile for the computations The default SEKS GUI value is 68 which corresponds to the 68 percentile Only one confidence level can be specified for each prediction task in SEKS GUI To compute confidence level results at additional percentiles repeat computations for different percentile values in the slider or edit box 4 For the prediction computations adjust the number of closest data neighbors of every prediction node location Depend
31. If there are headers these are used as custom labels in the maps 64 Soft Data There are soft data of the interval type in Arsenic 2 Input SDintervals txt in ASCII text format and appropriately formatted as follows Northing x Axis in Km in data file column 1 Easting y Axis in Km in data file column 2 Arsenic concentrations interval lower bounds in ug L in data file column 3 Arsenic concentrations interval upper bounds in ug L in data file column 4 Output Grid The example prediction grid is a 2 D spatial grid and is described in terms of grid limits and node spacing It is stored in Arsenic 3 Input OutGrid txt Arsenic concentrations have positive only values The mean trend is stored in the Matlab file Arsenic 4 MeanTrend mat The default parameter values that appear on the detrending stage of the exploratory analysis screen have been used to obtain the trend he Arsenic concentrations in the present example have been subjected to an N scores transformation prior to proceeding to the covariance analysis For empirical covariance information use the Arsenic 5 SampleCovariance Nsc mat Matlab file The covariance estimate has been computed by specifying a maximum correlation range of 200 km and by requesting computation in 10 spatial lags A spatial covariance model has been fitted with 2 nested components The model details are stored in the text file Arsenic 6 CovarianceModellnfo Nsc txt Feel free
32. Interface GUI or SEKS GUI This is a freely available package it is currently the combination of the scientific software library BMElib Bayesian Maximum Entropy library and related GUI files BMElib is a stand alone software library for space time modeling prediction and mapping This library implements innovative approaches in space time statistics and introduce many new features for spatiotemporal analysis and Temporal Geographical Information Science TGIS see Christakos et al 2002 BMElib relies on correlating information to predict the attribute of interest at a specified set of spatial locations and time instances For a typical space time study BMElib processes data sets of observations with space time reference it provides explicit information about estimates of underlying data trends the user can model data correlations by fitting permissible ordinary covariance models to the raw data and eventually performs attribute prediction BMElib is a software library written in Matlab Therefore to use it as a stand alone package it is required that the user has a working knowledge of the Matlab command line SEKS GUI is built with the user in mind SEKS GUI provides a friendly interface for the BMElib library eliminates the need to know programming in order to use it e introduces a framework that unifies all individual steps for modeling prediction mapping e includes utilities to wire the analysis output to other popular
33. KS GUI cannot tell whether any such discrepancies might be due to mistakes in the data entry process 10 Il B 3 Output Format File This file contains information about the prediction grid Once you provide the input data you must then specify the nodes in space and or time where you want SEKS GUI to generate predictions The prediction area limits depend on your needs and are left for you to define The distance between the nodes depends on the scale at which it is sensible to obtain results The same is true regarding the number of nodes to consider in each direction It is common that the output area extends to a size that is similar to the spatiotemporal extent of the available data gt f you request a very dense grid then you request to see what happens at finer scales However specifying too many nodes between data locations might not reveal new information about the behavior of your attribute and can incur unnecessarily high computational load for the prediction f you specify nodes that extend farther away from the population of your observed data then prediction might yield no results at all beyond some case specific distance This could happen when output grid nodes are too distant from the data to be correlated with them according to the specifics of your study gt This version of SEKS GUI accepts orthogonal regular grids as output grids There may well be cases where your area of interest does not cover an orthogon
34. Se WR eS with the numbers corresponding to the vanables as positioned below Does the attribute of your study take positive only values Yes Current Output Info file o Output Info file present Browse for Output Info file Main Menu lt gt gt BMElib Help Fig III A 12 2 Follow up your choice in the previous step by specifying an ASCII or Excel text file that contains the necessary information in the appropriate format as discussed in PART II Section B 3 Push the Browse for Output Info file button Be prepared to navigate to the folder where your output grid configuration file is stored and select the desired file After a successful choice the output grid info filename appears in the message area next to the Browse button see Fig III A 13 24 gt t is up to the user to provide a suitable input file Also be cautious to provide accurate information because SEKS GUI cannot guess from raw input what plain numbers may stand for gt Selection or re selection of an input format from the drop down menu see previous step 1 will clear any output info file information previously provided by the user to prevent potential errors For that reason always perform step 1 before proceeding to the current step 2 gt If the Cancel button is pushed during navigation then no output info file is selected and a related message appears gt f an output info file is already chosen and the Browse
35. Shortcuts Z Howto Add 27 What s New main window and it should then appear on the side of E LL LJ SEKSGUIfolder D D the main window gt f this process has been performed once on a computer the following time you launch Matlab again on the same computer it is possible that the SEKSGUlfolder location has been stored Click the downward arrow on the right side of the Current Folder bar Fig 1 1 at the top of the Matlab Command window With this action a list of the most recently visited folders is shown so you can select the SEKSGUlfolder without having to navigate your way there again Fig 1 2 Name startup m 4 Once the Matlab path above the Command window indicates that you are in the SEKSGUlfolder type startup at the Matlab command line and then press the Enter or the Return key gt gt startup This is a SEKS GUI command It renders all of n the material in the SEKS GUI folders accessible in your session by adding them into the Matlab search path Fig 1 3 xa ag Command Window gt gt startup Search path set for SEKS GUI v1 0 0 on MATLAB If the command works correctly then a confirmation message should display in the Matlab Command window Fig 1 3 You are now ready to use SEKS GUI and the BMElib library on Matlab c Steps 3 and 4 above must be performed every time you start Matlab when you want to use SEKS GUI in a session Step 5 above may be skipped if you sta
36. Temporal row should contain values about the temporal component of the space time component that is currently highlighted in the model box The box on the left holds the temporal range value for all types of model components except for the following For the Mexican Hat the parameter is the first Mexican Hat model parameter For the Sine Hole and Cosine Hole models the parameter is the periodicity The box on the right holds the second Mexican Hat model parameter and is inactive when any other temporal component is selected gt The nugget effect model has only the sill parameter because the model represents the variance added to the data due to shorter range variation or measurement errors gt For each model that you specify SEKS GUI provides sample default initial values for the model parameters based on the maximum spatial and temporal ranges in the problem However initial values are only provided as a guide for your analysis and are no indication that SEKS GUI understands the actual correlation mechanism in your study Adjust the parameter values across all components of your spatiotemporal model to achieve an optimal fit by inspecting the covariance plot on the screen In the space time analysis example of Fig Ill B 11a the first of the 2 space time components is highlighted for which the sill is set to 0 55 variance units the spherical model range is specified as 14 spatial length units and the exponential model range is specifi
37. ab help command This screen makes all of these help pages easily accessible through SEKS GUI When you select one group topic or one function from the lists in the upper part of the screen the help text is displayed in the lower window In the example of Fig III A 3 the lower screen window displays help about the bmeprobalib topic group When done push Close Help to close the help window BMElib Help View help on one of the following BMElib topic groups OR choose a BME function for help with its syntax and use iolib BMELIB exploratory data analysis file input output graphlib BMELIB exploratory data analysis graphical functions BMECATLIBtest modeislib BMELIB analysis of space time variability vanogram and covariance models Spy statlib BMELIB analysis of space time variability statitics and estimation of vaniograms BMEPROBALIBtest bmeprobalib BMELIB spatiotemporal estimation using hard data and probabilistic soft data BMEcatHard bmeintlib BMELIB spatiotemporal estimation using hard data and interval soft data BMEcatPdf bmehrlib BMELIB spatiotemporal estimation using hard data only BMEcatSubset simulib BMELIB simulation of S TRF realizations BMEcat tocheck genlib Miscellaneous general functions BMEcategHardk mvnlib FORTRAN routines for the numerical calculation of multivariate integrals Eua ped pest Help with Group topic Help with function Close Help Fig III A 3 In the Ch
38. accepted in the Max Hard Data edit box However if you specify a value larger than 100 you are warned about the seemingly large number as a precaution to prevent potential typing errors gt Any positive integer is accepted in the Max Soft Data edit box However if you specify a value larger than 5 you are warned about the seemingly large number as a precaution to prevent potential typing errors 5 Adjust the spatial range parameter for the prediction in the edit box under Max S Range label This parameter regulates the maximum spatial distance from the current prediction location within which BME searches for contributing data neighbors SEKS GUI sets a default starting value for this parameter based on the spatial range of your covariance model component with the largest sill The initial value is only provided as a guide for your analysis and is no indication that SEKS GUI understands the actual spatial correlation mechanism in your study gt The Max S Range edit box accepts positive numbers Any different entry is unacceptable and produces an error message window gt Any positive number is accepted in the Max S Range edit box However if you specify a value larger than 150 of the output grid largest side size you are warned about the seemingly large number as a precaution to prevent potential typing errors 6 Applicable only in spatiotemporal analysis Adjust the temporal range parameter for the prediction in t
39. al area similar to the output grid type as e g when data are only provided on a stretch whose spatial coordinates cross the designated output grid diagonally It is likely then based on the previous remark that some nodes on the grid located further outside the data populated stretch may not be assigned an estimate if they cannot be correlated to the input information This is an expected event and it should not be alarming You can still make good use of the grid and obtain estimates on as many nodes as this field s correlation will allow on the grid Nodes without estimates can be masked out of the map at a later stage using image manipulation software This version of SEKS GUI supports information for a custom orthogonal grid whose characteristics should be provided by the user in an ASCII text file or a Microsoft Excel xls spreadsheet If you choose to use a text file values in the file should be space or tab separated occupy continuous lines and there should be exactly 1 line dedicated to the information on each of the dimensions used Il In case you use an Excel spreadsheet please ensure your information is in the first spreadsheet of the file if there are more than one spreadsheets in the file Values should be stored in neighboring cells and there should be exactly 1 row dedicated to the information on each of the dimensions used The following page has details on defining the grid information within your input file
40. ary developed by Prof Patrick Bogaert Universit Catholique de Louvain Belgium and Dr Marc Serre University of North Carolina at Chapel Hill USA SEKS GUI interface developed by Dr Alexander Kolovos SpaceTimeWorks LLC USA and Dr Hwa Lung Yu National Taiwan University Taipei Taiwan Additional contributions to SEKS GUI utilities for data exchange with Esri Shapefiles provided by Steve Warmerdam and Boris Dev San Diego State University CA USA 74 PART VII BIBLIOGRAPHY Box G E P Jenkins G M and Reinsel G C Time Series Analysis Forecasting and Control 3rd ed Prentice Hall Englewood Clifs NJ 1994 Christakos G Random Field Models in Earth Sciences Academic Press San Diego CA 474 p 1992 new edition Dover Publ Inc Mineola NY 2005 Christakos G and D T Hristopulos Spatiotemporal Environmental Health Modelling Kluwer Academic Publ Boston Mass 423 p 1998 Christakos G Modern Spatiotemporal Geostatistics Oxford Univ Press New York NY 304 p 2000 new edition Dover Publ Inc Mineola NY 2012 Christakos G P Bogaert and M L Serre Temporal GIS Springer Verlag New York N Y 220 p With CD ROM 2002 Deutsch C V and Journel A G GSLIB Geostatistical Software Library and User s Guide Oxford University Press New York 369 p and 1 compact disk 1998 Esri link on shapefiles current as of February 2013 http www esri com library whitepape
41. bf sbn sbx shp shp xml and shx 7 Optionally you may want to ensure that all your data was transferred to the shapefile Check for x y and attribute data plus temporal coordinates when applicable by a Right clicking on the newly created layer name located on the left side of your ArcMap screen b Selecting Open Attribute Table gt A table containing all your data and newly created ID values opens 71 3 A Start up set of files for the creation of masking files All the information about this section is located in the folder SEKS GUIv1 X X guiLibs Utilities applyMaskFiles Please navigate Matlab into this folder first when requesting the input output files in the following gt Some basic Matlab programming experience is required for the tasks in this section In the sections with the SEKS GUI screen descriptions it is mentioned that you can apply a mask on top of the GUl generated maps The above folder contains a simple example of such a mask that can be relatively easily modified to fit your needs 1 First you will need a text file that contains the masking element For example the masking folder contains a file of the borders of the state of California in the USA The file is called californiaBorders txt and is a collection of coordinate pairs each of them fully described in a separate line using its longitude and latitude coordinates in the 1 and 2 columns respectively gt Yo
42. bsection 2 3 below Then type on the command line gt gt version and press the return key The number you see should be 7 11 R2010a or higher Items related to the SEKS GUI package The following items are available for downloading 1 SEKS GUIvX Y Zpackage zip This is a compressed file that contains SEKS GUI The component vX Y Z of the file name stands for the software version The version numbering uses the following convention e X stands for major version e Y stands for main update Z designates an update with bug fixes over previous versions 2 SEKS GUIvX Y Zdoc pdf This is the present user s guide for the current SEKS GUI 3 SEKS GUlexamples zip A compressed file that contains the folder GUI Examples with working examples of SEKS GUI Installation notes For installation of the SEKS GUI package you need no administrative rights on your computer Simply follow the steps below to move the package files to a desired position in your documents Assume that you have downloaded the latest SEKS GUI version in the compressed file SEKS GUIvX Y Zpackage zip 1 Select a folder where the package will reside Example You can create a folder SEKSGUlfolder to store the package In the Windows OS this path can be C Your WindowsOS Path ToMMy DocumentsVSEKSGUlfolder In the Mac OS this path can be Users Your Home Folder Documents SEKSGuUlfolder In this manual we assume that you store the package in a folder cal
43. ck Fig III A 9 2 When done push the Next button to proceed 21 Hstogram Regular Gnd PDF data with constant value in each interval All intervals of equal size Linear Regular Gnd PDF data with linear change between values in each interval AJI intervals of equal size BMElib Help III A 6 Import Soft Data Wizard Screen Part continued This screen appears if only soft data and no hard data are used 1 Enter in the upper box the number of dimensions involved in the current study 1 2 or 3 in a space time analysis you must include the temporal dimension in this number 2 Designate whether your investigation is in space time or a spatial only task For spatial only tasks push the Space Only domain button Fig IIl A 10 If the button is pushed again then it is deselected The default is a deselected button and implies a spatiotemporal analysis gt f you make mistakes in your selections there might be errors and data inconsistencies at later points in the analysis Soft Data Wizard 2 IMPORT SOFT DATA WIZARD Part of Il continued You may use up to 3 dimensions total patiotemporal investigations in the SEKS GUI Time is one of the maximum allowed 3 dimensions nput your Soft Data Main Menu Back gt gt BMElib Help Fig III A 10 2 When done push the Next button to proceed 27 IIl A 7 Import Soft Data Wizard Screen
44. contains nodes of an orthogonal grid The node spacing is dx in the x direction and dy in the y direction Each vertex of the polygon has spatial coordinates in the x and y dimensions as illustrated in Fig II B 9 You want to obtain predictions at the nodes inside this polygon in a space time study where the temporal interval spans from instances tmin to tmax with temporal node P1 p1x ply P5 p5x p5y P2 p2x p2y tmax dt tmin P3 p3x p3y P4 p4x p4y dy dx Fig Il B 9 spacing dt Then you can specify this prediction output grid in the following manner Example 5 To specify the prediction grid with nodes that are included in the polygon P1 P5 as illustrated in Fig Il B 9 provide type e information Prepare a text file that contains one line for each polygon vertex Start with any of the polygon vertices and specify the vertex coordinates in the first line Continue in a cyclical manner by specifying the neighboring vertex coordinates in the following line until you have specified the coordinates of all vertices In the immediate following line specify the spatial node spacing in the orthogonal grid that is included in the polygon Each one of the above lines in the input file must contain 2 values one for each of the x and y axes If you perform a space time study provide one more line with the temporal grid information as follows Initial instance time step and final instance According to the info
45. ct the desired empirical covariance to be the working covariance on the screen As in the previous screen the options allow for covariances in e All directions e East West 0 axis e North South 90 axis 3 Push the Select a model drop menu under each one of the spatial and temporal component labels to add a corresponding component to your covariance model SEKS GUI offers the following options to use as individual model components e Exponential e Gaussian e Cosine Hole e Sine Hole e Mexican Hat e Nugget Spherical 4 Push the Add Model button after your selections in step 3 To add a model you must specify both a spatial and a temporal component If any of those components is not selected and the corresponding drop down menu displays Select a Model then no model is added and a related message displays in the message box on the upper part of the screen After you add a space time model the model components display as a new single line in the model box under the Add Model button To specify a nested model with more than one space time component follow the steps 3 and 4 from the beginning for as many nested space time components as you wish Fig Ill B 11a shows an example where two nested space time components are specified the first component consists of a spherical model in space and an exponential model in time and the second component has an exponential model in space and a spherical model in
46. d then locate and open the text2shape mxd file packaged with the SEKS GUI in the folder SEKS GUIv1 X X guiLibs Utilities text2shape mxd is an ArcMap project file that is empty except for the addition of the SEKS GUI Conversion Tool Text to shapefile 69 ASCIItoSHP mxd ArcMap ArcInfo File Edit view Insert Selection Tools Window Help D c amp X gexlocols o TA a o h 3 ArcToolbox ug 3D Analyst Tools ug Analysis Tools E up BMELib Conversion Tools ox OF ag Cartography Tools amp Conversion Tools BY Coverage Tools ug Data Interoperability Tools BY Data Management Tools Qj Geocoding Tools ag Geostatistical Analyst Tools ug Linear Referencing Tools Qj Network Analyst Tools ag Samples Qi Spatial Analyst Tools Bi Spatial Statistics Tools I IRISH RR DR PIRE DEURE 2 rap Kk k e d f Fig V 1 3 If the ArcToolbox is not open select Window gt ArcToolbox from the menu bar Underneath BMELib Conversion Tools you should see Text to shapefile Fig V 1 Double click this tool to open up the options window 4 A new window opens that provides a brief description of the tool and asks the user to enter particulars for the conversion requested Fig V 2 a Enter the directory and name of your text file or click on the folder icon to browse for your file within your directory structure b Select the column upon which your X coordinate res
47. e powerful BMElib software library in a user friendly manner Your investigation input is necessary to run SEKS GUI You can make optimal use of SEKS GUI by having the requested input information available before you start your analysis Depending on your available data and study types 3 files containing information can be asked at different times II B 1 Hard Data File Based on the Knowledge Synthesis framework hard data are exact measurements i e data without significant uncertainty in their values for the purposes of your case study This file should contain coordinates and attribute values provided in one of the following forms ASCII text file Microsoft Excel xls or GeoEAS formatted text file On the SEKS GUI screen where you are asked to provide hard data see following Paragraphs III A 3 and IIl A 4 it is required that you specify the data file type as one of the above The following notes and file formatting rules must be observed If you choose to use a text file values should be space or tab separated occupy continuous lines and there should be 1 datum information per line Each datum line should display up to 3 spatiotemporal coordinates up to 2 spatial coordinates in the purely spatial case or up to 2 spatial coordinates plus 1 temporal in the spatiotemporal case followed by the attribute value The display in each line must be consistent with those of the other lines in the same file e g if one line starts wit
48. e actions are queued and may result in unwanted events or errors after the calculations are done gt At the end of the computations you are prompted to save the outcome data in a file In case of computations in multiple directions you can opt to save the empirical covariance data of all computations upon the completion of the last directional computation If you consider the results satisfactory it is recommended to save them in a suitably named file as you may later wish to return or re run this study step 2 above explains how to evoke previously saved data The data are saved in a Matlab format which has the ending mat in the folder you will specify and cannot be viewed independently unless they are loaded within the Matlab environment Once prompted to save data you cannot save them at a later point unless you repeat the computations 7 After computation of the empirical covariance you can use the Plot drop down menu to view covariance plots Choose at any time among the following plots e Isotropic empirical covariance in all directions see Fig III B 9 e Empirical covariance in the East West direction Empirical covariance in the North South direction e All empirical covariance points in one plot e All directions East West or North South empirical covariances at s 0 available only in space time analysis e All directions East West or North South empirical covariances at t 0 available only in space time analysis
49. e results a maximum of 50 hard data and 3 soft data have been used also a maximum spatial range of 50 degrees and temporal range of 6 days have been specified to define the prediction neighborhoods and the spatiotemporal metric parameter value was set to 0 3 You can use the output file contents directly by advancing to the Visualization screen or by loading the file at any time within the visualization screen to produce the Total Ozone BME study maps 63 2 BME Spatial study of Arsenic in Bangladesh drinking water 1 All the information about this study is located in the folder GUlexamples 002 ArsenicBangldeshStudy S Please navigate Matlab into this folder first when requesting the input output files in the following For the Arsenic study there are masks to use when you produce maps of the prediction area The provided masks display the borders of Bangladesh and the surrounding countries You can use masking information for the mean trend maps and the prediction maps This information is stored in the folder Arsenic MapsMask Simply guide SEKS GUI to the Matlab file applyMask m in that folder to include this mask in your maps Note that the information therein relates only to the particular case study The script relies on knowledge of the individual coordinates of the borders represented as a series of points for the countries shown on the map You can create similar scripts based on this one to create masks for your o
50. e zA The datum PDF has 3 bins whose 4 limits are 11A 12A 13A and 14A Within each of these bins the PDF has corresponding constant values plA p2A and p3A The datum is described in 1 line and corresponding data file entry should be Fig II B 4 similar to the following line XA yA ZA 3 11A 12A 13A 14A plA p2A p3A Excel files should feature these values in consecutive cells in the same row When using data of this type you can include different data with variable number of bins in the same file That is you can specify different number of parameters in each line entry pA pa MA 25 BA WA Example 5 Case where PDF bins might have different sizes and the PDF value changes linearly within a bin A simple distribution of this type is portrayed in Fig Il B 5 Assume that this paa distribution corresponds to a probabilistic datum A that is located at xA yA on a plane and at temporal instance zA The datum PDF has 3 bins whose 4 limits are 11A 12A 13A and 14A Within each of P these bins the PDF changes linearly from the initial p4A value p1A and advances to values p2A p3A and HA I2A BA JAA p4A at the consecutive bin limits The datum is described in 1 line and corresponding data file entry PIGE Ee should be similar to the following line xA yA ZA 3 11A 12A 13A 14A plA p2A p3A p4A Excel files should feature these values in consecutive cells in the same row When using data of this type you can include different data wi
51. ed as 32 time units In the spatial only analysis example of Fig III B 11b the first of the 2 spatial components is highlighted This component is a nugget effect that has only a sill parameter Its value is specified to be 0 75 variance units 6 Push the Remove Model button to remove a spatiotemporal model you have added and is currently highlighted in the model box To have an effect at least one space time component must be present in the model box Simply highlight the model you want to remove in the model display box and push the Remove Model button c Accordingly in the spatial only case the Remove Model button has similar functionality 7 During model fitting every modification of the model components or parameters updates the plot on the screen accordingly This provides you with feedback to guide you in the fitting process At all times you can choose to view any map of the following e Empirical and modeled covariances e Empirical covariance only e Modeled covariance plot at lag s 0 available only in space time analysis e Modeled covariance plot at lag t 0 available only in space time analysis 47 Use the External figure button to display future plot requests in an external independent window when activated or to return to the in screen display when de activated This feature is particularly useful in covariance fitting because it enables you to inspect the fit quality in plot views that are no
52. ent soft data types fall in the probabilistic category The examples in the following pages cover the spectrum of the acceptable probabilistic soft data forms in SEKS GUI I b1 Probabilistic soft data with fully described PDF characteristics SEKS GUI accepts soft data in the form of Gaussian uniform or triangular distributions Example 1 Case where PDF is a Gaussian distribution with known mean and variance Assume a datum A that is a Gaussian distribution N mA vA with mean mA and variance vA and is XP XA VA located at coordinates xA yA in space and at zA NmA vA in time as portrayed in Fig Il B 1 The description of this datum in the soft data file should resemble the format of the following line XA yA ZA mA vA Excel files should feature these values in mA T consecutive cells in the same row Fig 11 B 1 Example 2 Case where PDF is a uniform distribution with known mean and variance Assume a datum A that is a uniform distribution PW U mA vA with mean mA and variance vA located at coordinates xA yA in a purely spatial 2 D case as portrayed in Fig Il B 2 The description of this datum in the soft data file should resemble the format of the following line XA yA mA vA Excel files should feature these values in consecutive cells in the same row Note that the same line above also describes a soft datum at xA at the temporal instance yA in a 1 D spatial and temporal case Fig II B 2 Uni
53. er 10 10 10 10 0 001 0 005 0 01 0 05 0 1 0 5 1 5 10 50 100 500 1000 10 10 10 and 10 56 Visualization Wizard 7 VISUALIZATION n this scree screen yo screen after the pred you can create a variety of plots using the SEKS GUI prediction output t ediction stage the display below indicates what information is available for visualization ed this screen directly from the SEKS GUI main menu please start by loading a SEKS GUI o Load SEKS GUI output file Main Menu lt lt ck BMElib Help Fig IIl C 4 Use the External figure button to display future plot requests in an external independent window when activated or to return to the in screen display when de activated as shown earlier in Paragraph III B 1 and Fig III B 5 gt When the Plot external figure button is activated it enables complete control of the plot by making use of Matlab tools e g axes rotation renaming etc Also this feature allows the user to print the particular figure using the independent window menu For more information on handling plots in separate figure windows consult Matlab Help 4 Use the Fixed color scale button to plot the eligible maps in a particular color scale so that e g maps of the same attribute can be compared at different temporal instances The button toggles between activation and de activation when pushed each time Upon activating the button the first time you have to set
54. er You can experiment with different values to define the case specific spatiotemporal distance as a function of the distances in space and time SEKS GUI sets a default starting value for this parameter as the ratio of the initial values of the maximum spatial range over the maximum temporal range Fig III B 13 The initial value is only provided as a guide for your analysis and is no indication that SEKS GUI understands the actual correlation mechanism in your study In the purely spatial case the corresponding box displays N A and cannot be edited gt The S T metric parameter edit box accepts positive numbers Any different entry is unacceptable and produces an error message window 8 Push the Begin Prediction button to start the BME prediction computations gt Be patient and wait until the computations come to an end Matlab and the SEKS GUI cannot respond during that time to any other commands It is recommended to refrain from pushing other SEKS GUI buttons at this time as these actions are queued and may result in unwanted events or errors after the computations are done Computations may take a lot of time depending on the volume of data in the data set and your computer specifications For your convenience the message box displays the progress in calculations Fig IIl B 14 No results can be viewed before the successful termination of the calculations and prior to advancing to the visualization screen gt f you need to
55. f existing SEKS GUI output View BMElib code help pages Choose any of the tasks above Push Start to proceed with selection Each screen will guide you to complete the necessary intermediate steps At any instance you can see information on the BMElib individual libraries and commands by pushing the BMElib Help button Fig II A 2 BME Spatiotemporal Analysis uses the BME methodology You can read information about the BME analysis and instructions for the BME related screens in Section B of PART III The Visualization of existing SEKS GUI output option takes you to the Visualization Wizard which is the last of the SEKS GUI screens f you have prediction results from previous SEKS GUI analyses then you can follow this path to reproduce maps of your results without having to go through all the analysis again You can find a description of this screen s features in Section D of PART III 16 By selecting the View BMElib code help pages task you access to the standard BMElib help pages When the option is highlighted and Start is pushed an external window is launched Fig III A 3 This option displays the default help files for the BMElib function libraries upper left hand window in Fig IIl A 3 and its individual functions upper right hand window in Fig IIl A 3 You can view the same help information when you ask for help about a specific BMElib function name in the Matlab Command Window with the Matl
56. f the file structure Line 11 is used to load the masking element text file e Line 12 defines the output grid map corners as discussed in the previous paragraph e Line 16 explicitly asks to take actions on an existing map in our case the ones already created by SEKS GUI If the specific command to hold on in this line is not used prior to any of the other following plotting commands the commands that follow will overwrite the pre existing map Line 17 plots the contents of the masking element text file as a solid line Line 18 fills the polygon defined by the above solid line with white color 12 The remaining lines add labels and define the plot limits based on the corner coordinates provided earlier You can specify more than 1 polygon to plot in the applyMask m file If the additional files reside in the same folder as the californiaBorders txt file then their content must be loaded in a similar manner as shown in the example line 11 of applyMask m If the additional files reside elsewhere then you must specify their name as part of their complete file path when you load their content in the example line 11 of applyMask m Any additional content can be plotted on top of the existing map by repeating the sequence currently shown in lines 16 18 in applyMask m Simply copy and paste these lines by adjusting them suitably according to your additional content 73 PART VI ACKNOWLEDGEMENTS BMElib libr
57. for space and time temporal maximum radius not available in purely spatial cases in the S radius and T radius boxes respectively on the right hand side of the screen These are the distances around each location within which the kernel smoothing algorithm searches for spatiotemporal neighbors to obtain a local average Then push the Begin detrending button to extract a mean trend from the empirical data Fig III B 1 Detrending may take a while to complete depending on the amount of data to process When you request to Begin detrending a confirmation window warns you that any existing unsaved trend data are ignored 28 gt Initial space and time radii as appropriate are automatically set by SEKS GUI upon visiting this screen on the basis of the output grid dimensions as specified in the Output Grid Wizard screen of Paragraph III A 8 Modify the default values as needed to achieve the desired degree of smoothness in the estimated mean trend gt The larger the radius value is the more smooth appears the trend estimate Keep in mind that there is no single actual trend to estimate The outcome of this stage depends purely on your judgment knowledge and intuition about your study problem gt Please be patient and wait until the calculations come to an end Matlab and SEKS GUI can not respond during the calculation time to any other commands Refrain from pushing buttons at this time as these actions are queued and may resu
58. form distribution soft data are very similar to soft interval data of the category a Indeed soft intervals as defined are uniform distributions for which their upper and lower limits are known rather than their means and variances Example 3 Case where PDF is a triangular distribution with known mean and limits Assume a datum A that is a triangular distribution T u1A mA u2A spans within the interval PW NAVA u11A u2A and has a mean mA The datum is l located at coordinates xA yA in space and at zA in time as portrayed in Fig Il B 3 The description of this datum in the soft data file should resemble the format of the following line XA yA ZA ulA mA u2A UIA MA u2A u Excel files should feature these values in consecutive cells in the same row T u1A mA u2A Fig II B 3 b2 Probabilistic soft data with user described PDF in terms of probabilities at pre defined bins This is a useful alternative when the soft datum PDF falls in any other than the previously described shapes you have PDF information in bins or range brackets the available uncertain information exhibits a more complex behavior or PDF form Example 4 Case where PDF bins might have different sizes and the PDF value is constant within a given bin A simple distribution of p2A this type is portrayed in Fig II B 4 Assume that this distribution corresponds to a probabilistic datum A that is located at xA yA on a plane and at temporal instanc
59. formation in mind you can push once the Add mask to plots button to activate this feature You are then prompted to locate a masking code Matlab file in your computer filesystem If you push this button accidentally you can cancel the file search If the button is activated you can push it again to de activate it 9 The visualization screen is the last one in the series of the SEKS GUI functions Push the Back button to return to the previous screen or push the Exit button to exit SEKS GUI gt f you arrived at the visualization screen after the prediction screen and in addition you loaded output from a different investigation then the Back button sends you to the Choose a Task screen of the SEKS GUI main menu 61 PART IV SEKS GUI EXAMPLES If you downloaded the file SEKS GUlexamples zip then you can run example test cases to get familiarized with the SEKS GUI environment The examples package features two examples that are presented in the following namely a spatiotemporal study of Total Ozone concentrations over the United States of which snapshots at various stages have been used as figures in this guide and a spatial only investigation of Arsenic concentrations in the Bangladesh groundwater In the following assume that you create a folder GUlexamples in the folder SEKSGUlfolder see Paragraph 1 3 Installation Notes and that you save the contents of the compressed file SEKS GUlexamples zip in
60. h the x coordinate then all lines in the file must start with the x coordinate too Finally you need to know the content of each column in your text file e g x coordinates are in the 1 column Il If you use an Excel file please ensure your information is in the first spreadsheet of the file if there are more than one spreadsheets in the file Values should be stored in neighboring cells and each row should contain information for exactly 1 datum The formatting rules are the same as in the previous case l IIl If you will be using the GeoEAS format then all you need to know is where your input file resides when asked and how the data are positioned within the file In particular SEKS GUI will ask you to specify the columns that contain the spatiotemporal coordinates and the attribute values I1 B 2 Soft Data File Based on the Knowledge Synthesis framework soft data are measurements associated with some known uncertainty Provide an ASCII text or a Microsoft Excel xls soft data file l In a text file values should be space or tab separated occupy continuous lines and there should be 1 datum information per line Each datum line should first display up to 3 spatiotemporal coordinates up to 2 spatial coordinates in the purely spatial case or up to 2 spatial coordinates plus 1 temporal in the spatiotemporal case followed by the attribute soft information The display in each line must be consistent with those of the
61. he eligible maps in the original space click on Original space or the transformation space if a transformation was used to obtain the estimates click on Transformation space When you enter the screen the default choice is map display in the original space gt The buttons Original space and Transformation space are mutually exclusive Only one of these two can be active at a time gt The maps in the original space are the back transformed estimates with the mean trends restored at the prediction locations The moments that are shown are based on the raw estimated PDF moments which have been back transformed and the mean trends at these locations have been restored The maps in the transformation space contain detrended data that come directly from the raw estimated PDFs Therefore in the transformation space maps the mean trend is not restored see Fig III C 6 and compare it to Fig III C 3 7 Use the Transformation Info button to review the transformation type and its characteristics if any has been applied on the initial data set that you used for prediction This button only causes information to be displayed in the message box gt f an N scores transformation has been applied to detrended data the message box shows the range of detrended data values that have been used to define the transformation see Fig IIl C 7 and the discussion in the Introduction part of Paragraph IIl B 1 2 gt f a
62. he message box on the screen Exploratory Analysis 4 DATA EXPLORATORY ANALYSIS Part Il of Ill Data Distribution and Detrending Soft Data are mapped below using the mid point value if in category A or their PDF mean categories An estimate of the variable s mean trend is extracted from the data by means of a Gaussian kernel smoothing Data used Non detrended all 1 3452 Detrended in 1211 5 3452 2500 Data Statistics i55 t Non detrended Detrended Coumt Minimum Maximum Frequency Main Menu gt gt BMElib Help Fig III B 3 30 Use the Bars drop menu to plot the histogram with more or fewer bars as desired Use the t slider or write a suitable number in the t box on the lower left hand side to view maps at a particular instance in time not available in purely spatial cases Fig III B 4 shows an example of displaying a trend map at time instance t 9 Activate or de activate as desired the Maps for all t button to see time aggregated maps of data locations and distributions or maps at user selected instances respectively not available in purely spatial cases or when requesting trend maps at individual instances Use the External figure button to display future plot requests in an external independent window when activated Fig III B 5 or to return to the in screen display when de activated gt When the External figure button is activated it enables comp
63. he edit box under Max T Range label This parameter regulates the maximum temporal distance from the current prediction location within which BME searches 50 for contributing data neighbors SEKS GUI sets a default starting value for this parameter based on the temporal range of your covariance model component with the largest sill The initial value is only provided as a guide for your analysis and is no indication that SEKS GUI understands the actual temporal correlation mechanism in your study In the purely spatial case the corresponding box displays N A and cannot be edited gt The Max T Range edit box accepts positive integer numbers Any different entry is unacceptable and produces an error message window gt Any positive integer number is accepted in the Max T Range edit box However if you specify a value larger than the time span of the data set you are warned about the seemingly large number as a precaution to prevent potential typing errors 7 Applicable only in spatiotemporal analysis Adjust the spatiotemporal metric parameter for prediction This parameter shows in the edit box under S T metric parameter and is used as a key to define how spatiotemporal distance is computed between two spatiotemporal coordinates This spatiotemporal distance is given by the relationship S T distance Spatial distance S T Metric Parameter Temporal distance There are no guidelines for setting this paramet
64. her de activate the button or define properly the color scale bounds in the boxes Visualization Wizard 7 VISUALIZATION In this screen you can create a variety of plots using the SEKS GUI prediction output If you arrived at this screen after the prediction stage the display below indicates what information is available for visualization If you selected this screen directly from the SEKS GUI main menu please start by loading a SEKS GUI output file from a previous analysis Displaying variable Mean Load SEKS GUI output file Map Displayed Mean of the variable estimation PDF t Instance 9 PDF scale Space to plot output vf Fixed color scale Original space Color Scale Min Transformation space Color Scale Max Transformat ion Info Piot external figure Save map data as text Add mask to plots Main Menu BMEIib Help Fig IIN C 5 58 5 Use the Save map data as text button in the lower left hand screen corner to export the current map data in a text file This way you can use results outside SEKS GUI When pushing the button be prepared to navigate in your computer to the location where you want to save this information and to specify a filename for the text file to save The output text file has 4 columns with the following format e Column 1 contains the X coordinates e Column 2 contains the Y coordinates e Column 3 contains the current temporal instance same number in all lines or the n
65. hical techniques The data used for prediction stage are not altered by this process Estimates of a mean trend rely on the use of single values which imply the use of hard data values In BME analysis it is possible that your data set could contain a limited amount or no hard data at all SEKS GUI resolves this shortcoming by employing the soft data in trend estimation as follows For the purpose of trend estimation the means of the soft distributions or the middle points of the soft intervals are used to produce hard value approximations from the soft counterparts This is a reasonable compromise to potentially insufficient information conditions This approximation is also used in the following stage of covariance modeling as will be shown in Paragraph III B 3 because covariance analysis cannot use soft information either However the BME prediction stage assumes no approximations and soft data are considered in full as specified to take advantage of the BME methodology unique features for integration of soft information Based on the output grid size the kernel smoothing radius is set by default to 1 10 of the shortest extent of all grid directions The maximum search radius for data to contribute to the trend in space time is adjustable by the user The default starting values on the screen are estimated by the input data and they correspond to half the size of the longest extents among all grid directions in space and time respectively
66. ial analyses the maximum temporal correlation range box is not editable Fig III B 8b 5 The lag sliders and edit boxes can be used interchangeably to define the number of lags at which empirical covariance values will be computed You can request covariance estimates at any number between 2 and 30 lags in space and time You must specify at least 2 lags The upper limit of 30 lags is arbitrarily set by SEKS GUI and is well above values used in a typical analysis For each one of the spatial and temporal directions SEKS GUI automatically distributes the lag distances logarithmically across the preset correlation range This uneven distribution serves to obtain closer monitoring of the covariance behavior closer to the origin point s 0 and t 0 as is commonly desired in covariance analysis see Olea 1999 gt n spatial analyses the temporal lag slider and edit box cannot be used Fig III B 8b 6 Start computation of the empirical covariance by pushing the Get Empirical button after specifying the correlation range and lags parameters in earlier steps 4 and 5 gt Be patient and wait until the calculations come to an end Calculations may take a while depending on the volume of data in the data set and the hardware you are using There is no indication on the screen regarding the calculation progress Matlab and SEKS GUI cannot respond during that time to any other commands Please refrain from pushing buttons at this time as thes
67. ib Help 6 A more advanced feature for map presentations is plot masking which requires some knowledge of Matlab programming This is a useful feature if you would like to show the results that appear in part of your output area e g by masking out the portion of a map outside the borders of a country It is a more advanced operation because it requires that you provide a Matlab m code file with the masking information lf you can program in Matlab you can create a map that produces the desired mask over the output grid area by using suitable coordinates See also Paragraph V 3 in this manual for a basic utility provided with SEKS GUI to assist you in mask creation Keeping this information in mind you can push once the Add mask to plots button to activate this feature You are then prompted to locate a masking code Matlab file in your computer filesystem If you push this button accidentally you can cancel the file search If the button is activated you can push it again to de activate it 7 When done push the Next button to proceed 32 I1 B 1 2 BME Data Exploratory Analysis Screen Part III A Introduction BMElib operates correctly on normally distributed residual values of an attribute i e on detrended information that follows a Gaussian distribution This screen continues the task of bringing the user data into the required form after detrending of the data in the preceding step In this screen you review the Cu
68. ides If your text file does not contain variable names in its first row you will need to know beforehand where this column is located If your text file contains variable names in its first row you may select the appropriate variable name from the drop down menu c Repeat Step b above for the column upon which your Y coordinate resides d Because shapefiles consist of both the shapefiles themselves and associated files you need to specify a folder where all these files will be placed Click on the folder icon to browse for your folder of choice This folder must have been created prior to this step e Choose a name for your shapefile and its associated files The created files will all have the same names with different extensions f Click OK 70 2151 xj Text File H BMELib ASCIItoSHP D ataS ample tt Name of Shapefiles X Field No description available Ix Y Field v Output Folder H BMELib ASCIItoSHP Output i Mame of Shapefiles Example l OK Cancel Environments lt lt Hide Help E Fig V 2 5 he process dialog will appear and inform you of the progress Close this process dialog after ensuring that the process was successful 6 Your data points should automatically appear as a layer in ArcMap If not you can open the shapefile by selecting File Add data gt f you check the contents within your output folder you will see six newly created files with extensions d
69. ing on the proximity and availability of hard and soft data the number of closest neighboring observations that contribute to the prediction can be specified in the boxes under Max Hard Data and Max Soft Data SEKS GUI sets by default a maximum of 50 hard data and 3 soft data Fig III B 13 gt You can edit the Max Hard Data and Max Soft Data edit boxes in the presence of hard and soft data respectively If one of these data categories is not present in an investigation the corresponding box displays N A and cannot be edited gt t is reasonable to consider as many neighboring observations as possible when you predict the attribute value at an unsampled location However considering too many data may significantly slow down the prediction computations This is particularly evident when you request to account for a large amount of soft data neighbors if soft data are present In general prediction may become significantly slower if more than a few about 4 5 soft data are considered at a time Adjust the maximum neighboring data number accordingly before you start the prediction computations You can also try repeated prediction computations with different parameter values to compare results and computation times gt The edit boxes for the Max Hard Data and Max Soft Data parameters accept positive integer numbers Any different entry is unacceptable and produces an error message window gt Any positive integer is
70. ion must be entered as the last of the coordinates i e in the y axis box in the spatial 1 D case or in the z axis box in the spatial 2 D case Hard Data Wizard 1 IMPORT HARD DATA WIZARD Part Il of Il only first two boxes for x y or x t data c In 3 D Accordingly as above for x y z or x y t data d If using distance x height z and time t fill the spatial part first by providing the columns of the x data in the x Axis the z data in the y Axis and last the t data in the z Axis boxes Main Menu lt lt ck gt gt BMElib Help Fig III A 8 2 When done push the Next button to proceed gt Ifthe Back button is pushed in the following screen then SEKS GUI returns to part of the hard data wizard Paragraph III A 3 In that case the last declared HD file name is kept in memory 20 HI A 5 Import Soft Data Wizard Screen Part In this screen you enter soft data information into the system According to the knowledge synthesis framework this is information that entails some degree of uncertainty within the scope of your study Such data and their associated uncertainty can be entered in one of the SEKS GUI acceptable formats see Paragraph II B 2 If you have no soft data in your study then push the Next button to skip Part Il and to be taken to output grid definition screen see step 8 ahead gt f no input is present of either hard or soft data and the user attempts to continue
71. ired e The map of the BME prediction PDF value at the confidence interval limits at each output grid node BME Confidence Interval results required Visualization Wizard 7 VISUALIZATION In this screen you can create a variety of plots using the SEKS GUI prediction output scree o uiput jou arrived at this screen after the prediction stage the d Spray betow indicates whai nformation is available for visualization eduction s jou selected this screen directly from the SEKS GUI main menu please start by loading a SEKS GUI output file from a previous analysis Load SEKS GUI output file BMElib He ip Fig IIl C 3 If data necessary for a particular request are not available a message appears in the message box on the screen Use the t Instance slider or write a suitable number in the t Instance box to view maps at any temporal instance from the ones included in the output grid specifications Fig H1 C 3 gt The t lnstance slider and the edit box are disabled in the purely spatial case Use the PDF scale slider the corresponding box is read only to scale the actual size of the displayed PDFs on the graph Fig IIl C 4 PDFs are projected on the map in a way that might cause the individual PDF plots to interfere due to their size With the scaling feature you can achieve an optimal visual result for presentation purposes Choose a scaling level by specifying one of the following factors in the slid
72. is screen and proceed to the visualization screen using Next BME Mode yields the BME posterior PDF Mode Faster Confidence Interval Options Set the probability confidence level as desired st 99th percentile using the slider or the box Closest data to consider Max Hard Data Max Soft Data E 7 Main Menu lt lt ck gt gt BMElib Help Fig IIl B 14 e Singularities in the covariance matrices n this case try revising your selected covariance model by revisiting the covariance analysis stage described in Paragraph IIl B 2 Limited amount of data for prediction In this case try increasing the maximum number of hard data neighbors you use and or decreasing the maximum number of soft data neighbors You can do this by adjusting the existing numbers in the Max Hard Data and Max Soft Data edit boxes then restart the prediction task gt After BME prediction is complete at all of the output nodes in your specified output grid SEKS GUI calculates the moments mean variance and skewness of the prediction PDFs if applicable Consequently SEKS GUI back transforms automatically all the prediction information into the attribute s original space if transformation has been applied to the initial data set All results are arranged in SEKS GUI variables that you are prompted to save in an output file upon completion of the computations gt f a transformation has been applied to the data and moments have been calculated
73. itable processing form The first action that is taken is detection and removal of mean or surface trends in the data set to obtain the residual data values In this screen the user obtains a mean trend from the data distribution gt You may choose to proceed to the following screens without going through the mean trend calculation and removal This option is not recommended by the theory and may affect the prediction calculations leading to distorted or no results at all Nonetheless skipping the trend removal may be useful for testing purposes Even if you do not remove a mean trend you can use other features on the current screen such as viewing the data distributions and statistics For the detrending Gaussian kernel smoothing is applied across the dataset In this version of SEKS GUI the kernel searches for neighboring data within user defined ranges in space time and extracts the trend by applying a smoothing moving window If any unusually high or low values exist in the data set then the moving window may be biased by these values In these cases the smoothing operation might produce artifacts caused by extreme values in the data and thus drastically affect the trend estimate SEKS GUI addresses this issue by identifying and isolating from the detrending process potential outliers in the user data In particular extreme outliers are excluded from the data distribution trend prediction using criteria based on the box plot grap
74. l of whose PDFs are normally gaussian distributed Please provide either an Excel or an ASCII text file that contains all your SD information Each single datum information should occupy one line in the file In Excel values for each datum must occupy consecutive cells in the line ASCII text files must contain space separated values Provide the info in the followng order Example Let us assume you want to enter info for 2 SD in 3 D located at XA yA at tA and xB yB at tB as shown in the side figures Given the means and vanances an ASCII text file should contain the numbers corresponding to the vanables properly positioned in the lines below Current Soft Data file Ozone 2 Input SDgaussianPDF txt Browse for Soft Data file lt lt Back BMElib Help Fig III A 11 2 When done push the Next button to proceed gt If the Back button is pushed in the following Output Configuration screen then SEKS GUI returns to part of the soft data wizard Paragraph III A 5 23 HI A 8 Output Grid Wizard Screen In this screen you are prompted to specify the spatiotemporal or spatial in the spatial only case locations to obtain predictions 1 Use the drop down menu shown in Fig IIl A 12 to choose one of the available options e For option A provide limits and node distancing for each of the dimensions used e For option B provide limits and number of nodes for each of the dimensions used For option C
75. le ones or the single spreadsheet of the file GeoEAS is one of the standard formats available for data files select this button only if your HD are so formatted Hard Data Wizard 1 IMPORT HARD DATA WIZARD If no Hard Data file is provided and you pro any other information entered below wil be ignored If you return to this screen later the settings last defined here wil appear ov c r m m c m m To skip Hard Data in this case push the Browse button below nm n nl A e mam gt a E m m a r aw nd ihen Lancer ihe action n the window to deseleci any chosen file Then push Next Part of Il The Hard Data HD you wil be using needs to be provided in SEKS GUI accepts HD information in one of the following fon Plain ASCII text where data are separated by white space or tabs Excel format one single spreadsheet or the GeoEAS standard Please choose the format for your HD ASCII text Current Hard Data file No Hard Data file present Browse for Hard Data file purely spatial that is if Time is not a variable please check ihe Dox Space Only Domain Main Menu lt lt ck gt gt BMElib Help Fig III A 5 18 2 Push the button Browse for Hard Data file Be prepared to navigate to the folder where your hard data file is stored and then select the desired file After a successful choice the data filename appears in the message area next to the button
76. led SEKSGUlfolder 2 2 Unzip the compressed file The contents are the following items i SEKS GUIvX Y Z Folder that contains all the graphical user interface GUI files li startup m A file with information so that the Matlab application can locate files It is possible that your uncompressing application may have a default folder to place items i and ii Ensure that these items are eventually placed in the SEKSGUlfolder If you downloaded the SEKS GUI examples add the GUI Examples folder into the SEKSGUlfolder too After you complete these moves you can delete if you want the zipped files you downloaded and any other folders that were created during this process 3 Start Matlab and navigate its current working folder to the SEKSGUlfolder using the bar on the top of the Matlab Command window which is the main window in the Matlab environment Use the buttons on the top right hand side to locate the desired folder within your filesystem Fig 1 1 t G te r Q9 Current Folder Users alexander Documents SEKSGUIfolder Shortcuts Z Howto Add 7 What s New xap an Lj SEKSGUIfolder gt 2 fe 4 fm Name startup m Fig 1 1 Alternatively you can perform the navigation using the Current Folder window Fig 1 2 to the left of the Matlab Command window If the Current Folder window is not showing you can find it U G e of and select it under the Desktop menu of the Matlab
77. lete control of the plot by making use of Matlab plot tools e g axes rotation renaming etc Also this feature enables you to print the particular figure using the independent window menu For more information on handling plots in separate figure windows see Matlab Help Exploratory Analysis 4 DATA EXPLORATORY ANALYSIS Part Il of Ill Data Distribution and Detrending Soft Data are mapped below using the mid point value if in category A or their PDF mean categories B H An estimate of the variable s mean trend is extracted from the data by means of a Gaussian kernel smoothing Data Statistics f Loum Display Options Maps for all t External figure Map Displayed Add plots mask Main Menu BMElib Help Fig III B 4 3l eoo i __Figure1l _ t ide h amp 0 9 dis AOA 300 250 L 4 DATA EXPLORATORY ANALYSIS 200 Part Il of Ill Data Distribution and Detrending 150 ped below using the mid point value if in category A or their PDF mean categories B H variable s mean trend is extracted from the data by means of a Gaussian kernel smoothing 100 f ow to provid d ad trend fi 50 Begin detren r Pe E T ra 0 60 60 60 S t mmm X Skewness 1 78 2 Display Options Kurtosis 10 452 Maps for all t v i External figure Bars 15 Map Displayed Detrended data distribution A is mas Main Menu lt lt Back Next gt gt BMEl
78. lly unacceptable so you are asked to provide a suitably small value to map O to in the original space for transformation purposes The approximation is left to your discretion as discussed in the Introduction part of the current screen A default mapping of O into the value 0 001 is assumed when the screen appears You can adjust this mapping value with the slider on the lower right hand side Fig III B 6 gt f you make a choice other than the Box Cox transformation then your investigation is unaffected by the 0 mapping feature and you can ignore the slider value Exploratory Analysis 4 DATA EXPLORATORY ANALYSIS Part Ill of Ill Data Distribution and Transformation BME analysis requires detrended normally distributed data The detrended info is now screened for non VA cn mra r nose A now fry nin nd neon u mu You can apply either a non score a k a anamorphosis or a BoxCox transformation before proceeding Data Statistics Normal Detr Non Trsf Data External figure Main Menu lt lt ck gt gt BMElib Help Fig III B 6 35 5 You can plot a variety maps from the Map Displayed drop down menu At any time you can choose to view maps of e Comparison of the detrended non transformed data CDF red line in plot against the normal CDF defined by the detrended non transformed data mean and variance blue dashed line in plot e Comparison of the detrended N score space data
79. lt in unwanted events after the calculations are done Calculations may require a lot of time to complete depending on the volume of data and the hardware you are using Upon completion of the calculations you are prompted to save the trend estimation data in a file If you consider the results satisfactory it is strongly suggested to save them in a suitably named file This action serves the case where you may later wish to return or re run this study see in the following how to load previously saved data The data are saved in a Matlab format which has the ending mat in the folder you specify and can not be viewed independently unless they are loaded within the Matlab environment If you decline to save the trend data but instead prefer to explore the detrending output first you can save them anytime you are still on this screen by pushing the Save trend data button 3 If you are returning to this screen or re running the same data set study you may wish to load a previously saved version of the mean trend You might have a saved version if you followed the preceding step 2 at an earlier time In that case when the screen appears push the Load trend file button You are then asked to navigate in your filesystem to find the Matlab formatted file ending in mat where you previously stored trend data Once Exploratory Analysis 4 DATA EXPLORATORY ANALYSIS Part Il of Ill Data Distribution and Detrending Soft Data are
80. lts required The skewness of the prediction posterior PDF at each output grid node BME Moments PDF or Confidence Interval results required The actual probability density functions PDFs produced by the BME predictions at pre selected output locations The PDFs are projected vertically on a map of the output grid Fig Ill C 4 The current SEKS GUI version supports display of PDFs at pre selected locations throughout the output grid to avoid cluttering the plot BME PDF or Confidence Interval results required The size of the BME prediction confidence intervals at the user selected interval level as specified at step 3 in Paragraph II B 3 The value at each output grid location on this map is the difference between the attribute values at the confidence interval bounds For each prediction location this map displays the width of attribute 55 values within which the predicted attribute is expected to be found at the selected confidence level BME Confidence Interval results required e The map of the lower limit values of the BME prediction confidence intervals at the user selected interval level as chosen on Screen 13 where 68 is the default at each output grid node BME Confidence Interval results required e The map of the upper limit values of the BME prediction confidence intervals at the user selected interval level as chosen on Screen 13 where 68 is the default at each output grid node BME Confidence Interval results requ
81. lues for the ranges as follows The initial maximum spatial correlation range is half of the eucledian spatial distance between the most remote data in the set the initial maximum temporal correlation distance is half of the maximum data time span Initial values are only provided as a guide for your analysis and are no indication that SEKS GUI understands the actual correlation mechanism in your study An example of default values in boxes when you arrive at this screen is shown in Fig III B 8 gt The importance of knowing well your data is stressed again here Observe the resulting empirical covariance plot to assess how well your range estimates approximate the correlation structure 39 Covariance Analysis 5 COVARIANCE ANALYSIS SEKS GUI describes the variability of the Random Field in this study by means of covariance models Part of Il Empirical Covariance From Data To begin with please load existing data or specify characteristics and push the Get Empirical button You can adjust the number of computed points by modifying the range and lag parameters Anisotropy Covariance in Alil directions Compute the empirical covariance first Max S Correlation Range S Lags 53 3518 Max T Correlation Range 3 Plot Empirical Covariance All Extemal figure You can save data in file s after individual anisotropy calculations or all at once after the last calculation MainMenu lt lt Back Next
82. m n ae rem eT as E Mu Sa SM MD E ERES 16 3 Import Hard Data Wizard Screen Part cece cccc eee seeceece ees eeeeeeeeeeeeeeeteeaesenes 18 4 Import Hard Data Wizard Screen Part Il ec cecc cece eeseeeeeeeeeteeeeeeeeeeaeenseeaees 20 5 Import Soft Data Wizard Screen Part Loo ccc cece ees eeeeeeceeeeeeeeeesseseeeeseteeeaeeees 21 6 Import Soft Data Wizard Screen Part continued eeeeeeeesesssss 22 T Import Soft Data Wizard Screen Part Ul ccc cecc cece sees eeeeeeeeeeeesseeeeeaseeeeeneeees 23 9 QUIDUMGHGVWVIZATE Sereefiasstasce phone ea rp kee Fee eret teta ta e Er ete bat dt a p n RR 24 9 Data Exploratory Analysis Screen Part l eeeesseeseeeenrerene 26 ii Section III B BME Analysis Screens in SEKS GUI esses eene nennen nennen nnns nnns na ns 27 T BME Exploratory ANGI SS reusoin tut baud exce Dati E E EE 2 1 1 BME Data Exploratory Analysis Screen Part ll eeseeeseeeseeusee 27 As NIMEFOGUICUIO Iara oneo ase a a E EE E 2f B Instiiellolis uiu e iuit debet eau iunt aem Dub esatta ds 28 1 2 BME Data Exploratory Analysis Screen Part Ill 0 0 cece cence eee ees 33 PAs TO CUCU ON Mg NEP 33 B TIS UPUCTIONNS ES 34 2 COVAlANCE ANALYSIS ise ewidenves concn arose Poele aki das desene tuos a aE E EAEE 37 2 1 BME Covariance Analysis Screen Part cece cece
83. mapped below using the mid point value if in category A or their PDF mean categories B H An estimate of the variable s mean trend is extracted from the data by means of a Gaussian kernel smoothing rend data from file Ozone 4 MeanTrend mat 800 Data Statistics 700 nm a und Vu 600 Frequency e Po cen e e e e e n2 e eo Main Menu lt lt ck gt gt BMElib Help Fig III B 2 selected the file name appears in the message box Fig III B 2 and the detrended data set Statistics appear in the boxes on the left hand side gt Please ensure you provide appropriate input because SEKS GUI cannot guess on the file contents 4 The message box on the upper part of the screen communicates useful messages and cannot be edited 5 Use the drop down menu next to the Map Displayed label to plot a variety of maps At any time you can request maps of e All data locations e Hard data locations e Soft data locations Markerplots of all data hard data and soft data approximations e Colorplots of all data hard data and soft data approximations e Non detrended data distribution Once trend data are available the following maps can also be created e Detrended data distribution e Non and detrended data distributions Fig III B 3 e Mean trend of variable in space or at a chosen t instance in space time Fig III B 4 If data necessary for a particular request are not available a message appears in t
84. mapping tools This is the manual guide for the latest version of the GUI For an initial familiarization or a quick start with SEKS GUI two examples are presented in PART IV towards the end of the manual The examples are available to download from the SEKS GUI website We hope that you find this manual guide helpful when using the SEKS GUI package in your projects We greatly appreciate your feedback on the ideas features functionality and aesthetics of SEKS GUI The current guide is an update of the original SEKS GUI user manual for the first official version 0 6 that was made available in June 2006 Since then SEKS GUI has had some features added and numerous bugs fixed The SEKS GUI package is free software that can be used within the Matlab environment Alexander Kolovos Ph D SpaceTimeWorks LLC l 1 PARTI INSTALLATION OF SEKS GUI PACKAGE BME Spatiotemporal Analysis Library amp SEKS Graphical User Interface System Requirements 1 Personal computer running Windows OS Mac OS X or Linux with Matlab version R2010a or newer pre installed As of 2013 the current version of SEKS GUI has been tested successfully on Matlab versions R2007 and newer It is possible that SEKS GUI might run without issues on even earlier Matlab versions however it will not run with versions earlier than Matlab 6 5 gt f you are unsure about the Matlab version you are using you can check this software version by launching Matlab see su
85. mulative Density Function CDF of the detrended data and you decide whether they need to undergo a transformation This data transformation aims to reshape the detrended data set from the original space of values original space into a space where their distribution resembles a Gaussian one transformation space The transformations are based on the detrended hard data and soft data approximations set If the study includes soft data the actual soft information used in the predictions is consequently translated into the transformation space based on the transformation choice Your detrended data CDF is compared to a Gaussian distribution CDF that has the same mean and variance as the detrended data The criterion to apply a transformation and to a satisfactory transformation is the measure of deviation of your detrended data CDF from the Gaussian CDF in the original space and the transformation space respectively For example consider the case of a logarithmic transformation of your detrended data The user data statistics in the log space are displayed on the left hand side of the screen The log transformed detrended data distribution is checked for normality by comparing its CDF to the Gaussian distribution CDF defined by the mean and variance of the log transformed detrended data In SEKS GUI you can choose among the following options a No transformation The detrended data set is unaltered and you proceed to the prediction stage with data
86. n be used in the covariance analysis n the presence of soft data SEKS GUI includes them in the correlation analysis by using the soft data approximations defined earlier as the means of soft distributions or the middle point of soft intervals This action is justified on the reasoning that the covariance of the soft data means is equivalent with the covariance of the soft data themselves Christakos et al 2002 The current version of SEKS GUI offers basic anisotropy analysis features Specifically in stage a you can choose among 3 different directions to explore the sample correlations namely the East West or 0 axis the North South or 90 axis and an all directional analysis that assumes isotropy You must consequently define an estimate of spatial and temporal ranges for the sample correlations You can approximate values for these ranges based on your knowledge of your data or the underlying process If you have no such advance a knowledge try repeated estimations of the empirical covariance for a series of range values This experimentation can help you reveal how far the sample correlation extends across the spatial and temporal distance axes To help you in this task SEKS GUI offers the convenience of setting variable numbers of space and time lags At each one of these distance classes correlations are investigated by means of the number of data neighbors to any other given datum that are found within the class One value of
87. nd must have rows referring to cross sectional units and columns to time periods if there are multiple time periods The attribute data can either be cross sectional or panel data time series The coordinates in the shapefile are consolidated with the attribute data into a single file that SEKS can use as input 3 To run the script you must have Python www python org installed and within your system path Instructions The following instructions are given in the form of an example where a shapefile and an attribute text file are selected using the script 1 Place all key files in a single folder and navigate your way to it in this example local 2 Run the python script provided in the SEKS GUI package The script is the file shape2text py and is located in the folder SEKS GUIv1 X X guiLibs Utilities You can run the script after you copy the script file to the folder with the other key files Then type the executable for Python in your system and use the script file as an argument Slocal python shape2text py 3 Choose the shapefile to be converted from the list of shapefiles with a postfix shp in current directory kansas shp newyork shp california shp 66 Enter the shape file name to be converted to X Y but do not include shp Scalifornia 4 Choose the attribute or data file to be merged with shapefile information from a list 2 bmepy py california xyz xyz shape2text py Gis py california cst
88. ns whose lower limit is 11A its upper limit is 12A and the distance between consecutive bins is dsA Starting E from the lower limit the datum PDF changes linearly MA dsA I2A from the initial value p1A and advances to values p2A p3A and p4A at the consecutive bin limits The Fig II B 7 datum is described in 1 line and corresponding data file entry should be similar to the following line XA yA ZA 3 11A dsA 12A plA p2A p3A p4A Excel files should feature these values in consecutive cells in the same row When using data of this type you can include different data with variable number of bins in the same file That is you can specify different number of parameters in each line entry gt Based on the PDF definition in the previous examples 4 7 the values used to describe the probabilistic nature of soft data are the PDF values at the corresponding bins and not the actual probabilities for the bins Instead probabilities are geometrically represented by the area under the PDF in bins gt The total area under a PDF must be equal to the total probability of the occurrence of each datum i e it must be equal to 1 If you provide probabilistic data whose total probability is different from 1 then a warning is produced about such discrepancies SEKS GUI renormalizes the data in question to comply with the rule and continues the investigation It lies in the user s discretion to provide meaningful data in the sense that SE
89. ontents 2 The message box on the upper part of the screen communicates useful messages and cannot be edited 3 Make a choice about anisotropy in your analysis by selecting an option from the Anisotropy Covariance in drop down menu Fig III B 8 You have the following 3 anisotropy options e All directions isotropy assumption e East West anisotropy along the 0 axis e North South anisotropy along the 90 axis The default selection is an all directional isotropical analysis gt Once the empirical covariance has been calculated in any of the direction options you can choose to store the computed data immediately or cancel saving and continue for the covariance in a different direction After each calculation you are prompted to save the results You can compute the empirical covariance in all available direction options and then save all the results upon the last computation 4 The maximum spatial correlation range box and the maximum temporal correlation range box can be edited by the user These fields regulate the spatial and temporal extent of covariance computations and indicate your guesses about the correlation space time distance from any given location Adjust the range values in repeated covariance calculations until the data based covariances provide you with insight about likely values of the actual correlation ranges in space time gt When you first visit this screen SEKS GUI applies default starting va
90. oose a Task screen the About button provides brief information about the SEKS GUI version and contact information Use the Exit button in the Choose a Task screen to terminate the SEKS GUI session Before SEKS GUI exits you are asked to confirm Fig IIl A 4 eo Confirm Exit Please confirm Exit the SEKS GUI Yes No Fia III A 4 17 IIl A 3 Import Hard Data Wizard Screen Part In this screen you enter hard data information into the system According to the theoretical knowledge synthesis framework this type of information should consist of individual values or measurements that are considered to be accurate for the scope of your study You are now asked to enter this information If no such data are available then push the Next button to skip Part Il of the Hard Data Wizard and to be taken to the Soft Data Wizard screens see details in following Paragraph III A 5 1 The hard data HD file can be an ASCII text file an Excel xls file or a GeoEAS preformatted file as explained in Paragraph II B 1 earlier If your study involves hard data then you have to choose the data file type by selecting the appropriate one from the three available buttons ASCII text Excel format and GeoEAS format Only one of them can be selected at a time Fig IIl A 5 If you opt to go for the Excel format your data need to be saved in the first spreadsheet if there are multip
91. ox Cox space Backtransformation depends on the optimal A value that was selected for the specific data set 33 The Box Cox transformation is only defined for positive data values Since this transformation is applied on the detrended data set it is highly likely that the detrended data will feature negative or zero 0 values In the case of negative values SEKS GUI adds a constant to the detrended set so that all values to be transformed are positive This constant is removed later from the predicted values prior to their back transformation to the original space All of the above actions are performed automatically in SEKS GUI and are seamless to the user Finally if under some scenario there exist values equal to zero 0 in the set these must be approximated by an adequately small number before being subjected to transformation This action prevents any numerically unacceptable requests to compute the logarithm of O Towards this goal SEKS GUI approximates by default any O values to 107 if the Box Cox transformation is selected SEKS GUI enables you to modify this default mapping of O values anywhere into the range between 10 to 10 instead so that you can adjust this mapping according to your data set Example If your data values range between 0 and 1 then it might be a wiser choice to map O as an even smaller number than the default 10 e g you can specify 0 values to be mapped as 10 gt The above options are based on s
92. pe c information specify a text file that contains corresponding information in the following manner xmin nx dx ymin ny dy tmin nt dt If you use an Excel file as input then represent each line as a different spreadsheet row and place the line values into consecutive cells by starting at the first column By selecting the output grid information type d you can specify an arbitrary number of locations to obtain prediction at The benefit of type d specification is that output nodes need not be on a grid In this case prepare a text Excel file where each line row contains the prediction node coordinates First specify the spatial coordinates in the x axis and y axis as necessary If you perform a space time analysis then specify the temporal instance too Example 4 Assume that you want prediction at two space time locations A ax ay at and B bx by bt If you specify a text file with type d output grid information it should contain the following two lines with the coordinates of the locations A and B ax ay at bx by bt 12 Alternatively you might want to obtain predictions within a specific area bound by a polygon Select the output grid information type e to specify the polygon vertices and node spacing in all dimensions For an example of grid specification by using the information type e assume the imaginary spatiotemporal grid illustrated in Fig Il B 9 In the figure a polygon with vertices P1 P5
93. pts HD information in one of the following formats Plain ASCII text where data are separated by white space or tabs Excel format one single spreadsheet or the GeoEAS standard format Please choose the format for your HD e ASCII text Current Hard Data file rone 1 Input HD txt Browse for Hard Data file Space Only Domain Main Menu lt lt ck gt gt BMElib Help Fig III A 7 4 When done push the Next button to proceed Fig III A 7 19 Il A 4 Import Hard Data Wizard Screen Part II 1 In this screen you enter details about your hard data file to continue This screen appears only if a HD filename has been specified in the previous screen i e only when hard data are used Following the choice of the HD file you now provide the column numbers where your attribute observations and their coordinates are found in the file as Fig IIl A 8 shows Provide a number in a box only if the corresponding coordinates are used otherwise leave unused boxes empty gt A maximum of 3 dimensions time if considered must be included as the last of the reported dimensions is currently supported by SEKS GUI gt Please make sure you have a valid HD file at hand as instructed in Section Il B 1 earlier Also be cautious to provide accurate information because SEKS GUI cannot guess from raw input what plain numbers in a file may stand for gt f you work on a spatiotemporal investigation the time column informat
94. re than one model to nest then the sill is the sum of the nested models partial sills The spatial and the temporal ranges are measures of how far the correlation spans in space and time respectively In case of nested models the covariance model range is based on a combination of the nested components gt You must provide SEKS GUI with covariance information to proceed to following screens gt The covariance has a natural maximum at O space time lag To understand this intuitively think that each datum has a maximum correlation with itself and this correlation reduces as one moves farther away in space and time The covariance value at lag 0 equals the data set variance 38 H1 B 2 1 BME Covariance Analysis Screen Part 1 If you are returning to this screen or re running the same data set study you may wish to load a previously saved version of the empirical covariance information You might have a saved version if you followed steps 3 6 below at an earlier time In that case when the screen appears push the Load data button Fig IIIl B 8 You are then asked to navigate in your filesystem to find the Matlab formatted file ending in mat where you previously stored empirical covariance data Upon successfully loading a pre existing empirical covariance file for the current investigation a message appears to acknowledge the action gt Please make sure you provide proper input because SEKS GUI cannot guess on the file c
95. rmation shown in Fig II B 9 the output grid file should look as follows pix ply p2x p2y p3x p3y p4x p4y p5x p5y dx dy tmin dt tmax If you use an Excel file as input then represent each line as a different spreadsheet row and place the line values into consecutive cells by starting at the first column 13 Section II C Starting a SEKS GUI Session 1 Start Matlab The Matlab Command Window should appear Ensure Matlab has the BMElib and SEKS GUI packages in its path perform steps 3 and 4 in earlier Paragraph 1 3 2 Once you know Matlab has the SEKS GUI components in its path you can navigate Matlab elsewhere and still run commands in these components from any other folder Assume that you choose to remain within the SEKSGUlfolder 3 You can start a SEKS GUI session by typing seksgui in the command line of the Matlab Command Window as below Fig II C 1 and then press the Enter or the Return key gt gt seksgul The SEKS GUI splash screen will automatically appear thus starting a new SEKS GUI session see Paragraph III A 1 in the following gt All steps 1 3 in this paragraph must be performed every time you start Matlab if you want to use SEKS GUI in a session eoo MATLAB R2012a cC eB 5 ry Imi Users alexander Documents SEKSGUIfolder Shortcuts z Howto Add 7 What s New x ar xaon Command Window xawy SEKSGUIfolder 4 gt gt WURELUP m w ay LD sel v Search path se
96. rs pdfs shapefile pdf Olea R A Geostatistics for Engineers and Earth Scientists Kluwer Acad Publ Boston MA 303 p 1999 Olea R A A Six Step Practical Approach to Semivariogram Modeling Stochastic Environmental Research and Risk Assessment 20 5 307 318 2006 75 PART VIII LIST OF ABBREVIATIONS BME Bayesian Maximum Entropy CDF Cumulative Density Function N A Not applicable not available NaN Not a number quantity PDF Probability density function S T opace time spatiotemporal SEKS GUI Spatiotemporal Epistemic Knowledge Synthesis Graphical User Interface 76
97. rt Matlab from within the SEKSGUlfolder This option is available for Windows OS users if you define a Matlab shortcut that starts from within this folder when invoked This option is also available for Mac OS and Linux users if you start Matlab from the command line of a terminal while in the SEKSGUlfolder This information is slightly more advanced Unless you are certain about your setup follow step 5 to start and ensure the correct path to SEKS GUI is set 1 4 Testing BMElib This is not a necessary step in the SEKS GUI installation It is a recommended action though the first time you ever run BMElib on a computer to ensure that important BMElib functions work properly on the particular hardware 1 Start Matlab The Matlab Command Window should appear Make sure that Matlab already has the SEKS GUI package in its path steps 4 and 5 in previous Paragraph I 3 2 Type MVNLIBtest in the command line of the Matlab Command Window and then press the Enter or the Return key gt gt MVNLIBtest Wait a brief moment for some testing calculations to appear on the Matlab Command Window You should see the message test complete at the bottom of the window soon afterwards This message informs you that BMElib functions correctly on the computer gt f any errors should appear this is evidence that some key BMElib functions are not properly compiled for your computer architecture software In that case please contact the SEKS GUI
98. s filelOprac py shape2text2 py Gis pyc california shp junk txt shapereader py addition california txt saybye py arcv2stars py california xyz sayhi py Enter file holding attribute Z2 values california csts 5 Enter CS if the data is just for one year or CSTS for multiple years CS cross sectional data CSTS cross sectional time series data Enter CS or CSTS CSTS The output from the above procedure is shown below Sample data from final file 116 0556175 33 752874 4 33 752874 119 7219885 34 01836 4 34 01836 120 3837255 34 045747 4 34 045747 120 109372 33 9667205 4 33 9667205 119 399344 34 009645 4 34 009645 117 764832756 33 6671330053 4 33 6671330053 116 838523677 33 0195905 4 33 0195905 118 453602 33 3885865 4 33 3885865 115 28455427 33 0261927617 4 33 0261927617 119 5042505 33 2501805 4 33 2501805 118 4800315 32 918273 4 32 918273 Name of output file ends in xyz output x y points to california xyz 67 Miscelleneous Summary Information on Shapefile Shape File Name california shp Type Polygon Number of records 68 Polygons of multiple parts Bounding box Xmin Ymin 124 40959100 32 53415600 Xmax Ymax 114 13442654 42 00951800 Number of Attributes or Z values 1 The file structure of the output xyz file based on time series data is simply as follows The first column x coordinate The second column y coordinate The third column time period The
99. san Diego State University Department of Geography National Taiwan University Dept of Bioenvironmental Systems Engineering SpaceTimeWorks LLC SEKS GUI v 1 0 x User s Guide January 2013 CONTENTS Wilclcit NEIN RTT em 1 PART I INSTALLATION OF THE SEKS GUI PACKAGE diit sesecucirs Felt re Geta et e RU ved 2 BUSES csi 2 I 2 Items Related To the SEKS GUI Package seeesseeseeeneenneem nemen nnn nnn 2 3 Installation NOLES uon de o da a reu e a aces 2 LA TESNO BMELUD ebat svi bai eiu In eH sateen a cuan eeER S ev bdru ee dae adeni Mele deo raala isa a Eo edi bein 4 PART Il INHEESODUGCTION TOSEISSGUL su bisce ma ur E p do te cR RU Rte de eo eat 5 Section ILA TAGS EK 3S eiii T as 5 Section 1 B What information you need to run SEKS GU1 0 ccc cece ceccc eee ceeceeeeaeeese esse nemen nnns 6 Ua EB 6 2 SOIL DatatFllei sacscib v t v rt su verbs Eu lat Pat pat p yt Vi uu dee Eus E dut rd 7 9c utbut Format FIG esas ire rater rtr oet nate cmd eee Ru ER t ete ioe adage erator 11 Section II C Starung a SEKS GURSES SOain ied i edu veto Dos Aa et aedoe tamtn rid ho nate oes 14 PART Ill SENRS GUIFSCREEBDNSuiteteriiattoivi tokens enum aep ditus ea tina dosds def obediant a deus ic 15 Section III A Bruselas 15 T plas Sore Tosentu ci ki vn veto reat ru tpa oaa ou ee er c x EN EE I MT 15 2 NOE X il bs
100. t for SEKS GUI v1 0 0 on MATLAB Name fx gt gt seksgui Name Value ave dirBME Users alexande L SEKS GUlIv1 0 0 startup m Select a file to view details 4 Start Fig II C 1 4 To exit SEKS GUI at any instance while it is running you can push the Main Menu button on the SEKS GUI window Then push the Exit button in the Main Menu screen see Paragraph IlIl A 2 in the following You need to confirm the exit action because exiting results in erasing all your data stored in the memory of that session data saved in files are not affected 14 PART III SEKS GUI SCREENS Section III A Data Input IIl A 1 Screen 1 Splash Screen Some general information is displayed Fig IIl A 1 The screen shows for 4 seconds and then it automatically closes At this time the program proceeds to Screen 2 so that the user may choose a task Welcome to SEKS GUI Welcome to 7 SEKS GUI The Graphical User Interface for Spatiotemporal Epistemic Knowledge Synthesis Space Time Data Analysis Software featuring Advanced Statistics and TGIS Functions Version 1 0 0 January 2013 Fig III A 1 15 Ill A 2 Screen 2 Choose a Task You are presented with a list of available tasks Make a choice by clicking on a line in the list and the line will be highlighted Then push the Start button to begin Fig III A 2 Choose a Task What would you like to do with SEKS GUI Visualization o
101. t visible from the Matlab default plot viewing angle gt When the External figure button is activated it enables complete control of the plot by making use of Matlab tools e g axes rotation renaming etc Also this feature enables you to print the particular figure using the independent window menu For more information on handling plots in separate figure windows see Matlab Help 8 Push the Save model information button after you have fitted a model to save your model details in a text file You are prompted to choose a location to save this file Its contents are similar to those shown in Fig IIl B 12a for analysis in space time and Fig III B 12b for spatial only analysis Retain the file intact if you would like to re use its saved content at a later time The file contains information about one specific fitted model You can fit different models and save their corresponding information in different text files gt The sum of sills must not exceed 1 in your model Otherwise model information is not saved until you modify the sill parameter to satisfy this condition 9 Push the Load model information button to navigate your file system and find a previously saved text file with space time covariance information for SEKS GUI The file you load must be suitably formatted for SEKS GUI to understand it correctly It is recommended that you only load text files that you previously created by saving information in this screen
102. th variable number of bins in the same file That is you can specify different number of parameters in each line entry SD at IXA yA Example 6 Case where all of the PDF bins have the same size and the PDF value is constant within a given bin A simple distribution of this type is portrayed in Fig Il B 6 Assume that this P2 distribution corresponds to a probabilistic datum A that is located at xA yA on a plane and at temporal instance zA The datum PDF has 3 bins whose lower limit is 11A its upper limit is 12A and the distance between any two consecutive bins is dsA Within each of these bins the PDF has corresponding dSA eA constant values plA p2A and p3A The datum is Fig II B 6 described in 1 line and corresponding data file entry should be similar to the following line XA yA ZA 3 11A dsA 12A plA p2A p3A Excel files should feature these values in consecutive cells in the same row When using data of this type you can include different data with variable number of bins in the same file That is you can specify different number of parameters in each line entry p1A pa WA Example 7 Case where all of the PDF bins have the same size and the PDF value changes linearly within a bin A simple distribution of this type is portrayed in Fig II B 7 Assume that this distribution corresponds to a probabilistic datum A that is located at xA yA on a plane and at temporal instance zA The datum PDF has 3 bi
103. the lower and upper bounds of the color scale Inspect your maps choose the desired bounds and specify the lower bound in the box next to the Color Scale Min tag and the upper bound in the box next to the Color Scale Max tag The following map you request will display within the color scale you specified Fig Ill C 5 has an example of setting the color scale to range within the attribute values of 290 and 350 Compare to the attribute default illustration in Fig Ill C 3 In this example any attribute values lower than 290 are shown in the color scale bottom color white and attribute values higher than 350 are shown in the color scale ceiling color black When the button is de activated by pushing it again when activated bound indications disappear from the boxes and the boxes are disabled However if bounds have been previously defined they remain in the memory Then if you re activate the Fixed color scale button the last bounds set earlier reappear in the boxes You can modify the bounds values as desired when the button is activated and boxes are enabled 24 gt t may occur that the button is activated and one or both of the bound boxes does not contain any value In this case if you request a map that makes use of the fixed color scale then an error message appears to indicate the issue still the requested map is created and the color scale for the map is automatically set to the default You have the option to eit
104. then a warning screen appears and the user is prompted to start anew by choosing a task figure II1 A 2 or to exit SEKS GUI 1 As discussed in PART II Section B 2 the soft data SD handled by SEKS GUI can be interval data or probabilistic data Choose among the SD options offered by SEKS GUI by using to drop down menu shown in the upper right hand part of Fig III A 9 Probabilistic SD can be probability density functions Gaussian uniform or triangular alternatively the SD probability densities can be provided as a series of constant values histogram form that define equal or variably sized bins also SD can be a series of values at the limits of equal or variably sized bins where the values are assumed to change linearly between consecutive limits 2 IMPORT SOFT DATA WIZARD If your study has no Soft Data please continue by pushing the Next button at the bottom Part I of Il Soft Data should all be of the same type They can be in the form of a distribution Gaussian uniform or triangular or explicity defined as in the diagrams below Please select your Soft Data type Interval Data range within oven upper and lower Doundanes Values in any interval are uniformly distnbuted Hstogram PDF data with constant value in each interval Interval sizes not necessanly equal Linear PDF data with linear change Detween values in each interval interval sizes not necessarily equal lt lt Ba
105. this purpose simply select the components to assemble your model and adjust their sill and range parameters In general it is recommended to fit a form as simple as possible that provides a satisfactory fit Overfitting the empirical covariance is unnecessary because the empirical covariance itself is only an estimate of the underlying correlation structure gt Accordingly in the spatial only case your covariance model may consist of one single spatial model component or it may be a nested model of more than one component gt You must provide SEKS GUI with a covariance model to proceed with your analysis Either fit a model according to the steps 3 5 in the following or load a previously saved model step 9 in the following Covariance Analysis 5 COVARIANCE ANALYSIS Part Il of Il Fit a Covariance model In this step you fit a model to the empirical covariance computed in the previous part n specify a simple model with one component or a nested model with multiple additive separable model componen No Covariance Models Covariance Save model information Sag in s units T4ag in t units Main Menu lt lt ck gt gt BMElib Help Fig III B 10 44 1 The message box on the upper part of screen communicates useful messages and cannot be edited 2 If you have simultaneously empirical covariances in different anisotropy directions you can use the Anisotropy Covariance in drop down menu to sele
106. tive separable model components Empirical amp Modeled Covariances in selected direction Anisotropy Covariance in Aj drectons Spatial Component Temporal Component Select a Model Remove Model All directions Empirical Covariance Model Covariance Paramenter Covariance Lag in s units lt lt Back Next gt gt BMElib Help Fig III B 11b 46 5 Specify positive values for the component parameters in the corresponding boxes inside the Covariance Parameter area to the right of the model box In particular e The sill box should contain the value of the space time component sill that is currently highlighted in the model box Sill values are normalized Therefore when you are done adding models adjust the sills of all components of the covariance model so that their sum is 1 e The boxes in the Spatial row should contain values about the spatial component of the space time component that is currently highlighted in the model box The box on the left holds the spatial range value for all types of model components except for the following For the Mexican Hat the parameter is the first Mexican Hat model parameter For the Sine Hole and Cosine Hole models the parameter is the periodicity The box on the right holds the second Mexican Hat model parameter and is inactive when any other spatial component is selected e he boxes in the
107. to display the BME prediction results This screen can be accessed from the prediction screens Paragraph I B 3 for the BME analysis or directly from the Choose a Task screen Paragraph 1II A 2 if you have prediction output saved from previous investigations 1 The message box on the upper part of the screen communicates useful messages to the user and cannot be edited Upon loading this screen the message box indicates whether there is any prediction output available in Matlab memory If no such output is available you are prompted to load a suitable file with previously prediction information Fig III C 1 You can create such files according to steps 8 or 9 in Paragraph II B 3 for the BME analysis Visualization Wizard 7 VISUALIZATION In this screen you can create a variety of plots using the SEKS GUI prediction output t this screen after the prediction stage the display below indicates what information is available for visualization d this screen directly from the SEKS GUI main menu please start by loading a SEKS GUI output file from a previous analysis Color Scale Min Color Scale Max Main Menu lt lt ck BMElib Help Fig III C 1 2 By pushing the Load SEKS GUI output file be prepared to navigate to the folder where your SEKS GUI prediction output file is stored and then select the desired file After a successful choice the message box informs you about the available prediction data to work with gt
108. tomatically backtransformed in the end gt o E E c o ic Main Menu lt lt ck gt gt BMElib Help Fig III B 7 6 When done push the Next button to proceed 36 IIl B 2 Covariance Analysis In covariance analysis the goal is to investigate correlation patterns among the data gt The following refer to space time investigations For purely spatial cases ignore references to the temporal component It is crucial to stress that correlations may differ at different spatiotemporal neighborhoods due to the nature of the field under investigation In that sense for example a pattern that is modeled through a particular covariance function and applies in a specific spatial neighborhood may be inappropriate for another neighborhood on the same output grid Correlation patterns also differ when one changes the scale of observation For example correlations among data in a large grid do not exhibit in general the same behavior as correlations in a more localized scale within the same grid The effects of upscaling or downscaling are very important for prediction Exercise caution if your investigation includes action in different scales see also Christakos et al 2002 If this is the case then you can address these considerations in SEKS GUI by splitting your area of interest in spatial subdomains within each of which a single correlation scheme can be assumed to apply throughout the subdomain Clearly it is highly
109. ttributes to extend to negative numbers 4 When done push the Next button to proceed 25 III A 9 Data Exploratory Analysis Screen Part In this screen you are not required to take any action SEKS GUI performs an initial assessment of your data set A check for duplicate observations takes place because duplicate or co located coordinates result in covariance matrix singularities The same adverse effect also occurs when data points are very close spatial neighbors The current version of SEKS GUI automatically detects close proximity and handles it as co location The definition of close is assessed individually for each separate investigation it is independent of the spatial measurement units and is rather estimated on the basis of the output grid dimensions according to your specification in the previous Paragraph III A 8 In this version of SEKS GUI co located hard data in space time are averaged whereas soft data co located with other hard soft data are dealt with by slight random spatial displacements i e soft duplicates are not removed from the set Once the check has been performed the results are displayed in the corresponding boxes on the screen At this point you can push the Next button to proceed Fig III A 14 gt Please wait until the calculations are finished Do not proceed to the next screen while the Please wait messages display in this screen s boxes Data Exploration 4 D
110. u must provide the coordinate pairs in a sequence that outlines the mask you want to create When Matlab plots the corresponding points on a map it does so by joining the coordinates in any two consecutive entries with a line gt The last entry in the file must be the same as the first one so that there is a closed polygon to plot You can specify more than 1 polygon in separate files and then have them all plotted within the Matlab applyMask m file gt The file must also contain some reference to the output grid corner coordinates In case you wish to mask out the surroundings of an area as is the case with the California borders the outer grid coordinates are used together with the masking element coordinates to form a closed area that surrounds the actual part of the map you want to show This closed area can be filled with some color e g white in the applyMask m file to allow only the desired area to show in your final maps In the californiaBorders txt example file we assume that the output grid ranges within 125 114 longitude and 32 42 latitude Notice how the coordinates of the 4 grid corners have been incorporated in the state borders information in the file lines 53 57 Similar approaches can be used in a variety of cases 2 The second step is to properly modify the Matlab M file applyMask m that you will invoke from within the SEKS GUI to be the masking file your application The following is a brief tour o
111. ubjective criteria your knowledge of your data and your experience in this type of analysis There are no absolute correct options so you might need to try repeated analyses with different selections to understand better how a specific system functions Each transformation type forces your original space detrended data set into becoming a set of different values Typically the data in the transformed space have different set characteristics and dynamics than the data in the original space Among other concerns this might be a source of numerical issues at later stages Ideally explore whether it is meaningful enough to perform your analysis without transforming your data If you need to do so then SEKS GUI provides you with practical options to handle transformation with a minimum amount of effort c SEKS GUI suggests by default the use of a transformation when the maximum observed deviation between the detrended data CDF and the Gaussian CDF is larger than 10 B Instructions 1 The left hand side of the screen displays statistics on the data set Fig III B 6 Depending on the presence of hard and or soft data these statistics are based on the hard data and the soft data approximations You can choose from the Data Statistics drop down menu the form of the data that statistics refer to In this screen options include e Non detrended data Non D in the menu same as in previous screen e Detrended data Detrended in the menu
112. umber 1 if this is a spatial only case e Column 4 contains the value of the map attribute at the corresponding coordinates The number of lines in the file is equal to the number of output nodes on the spatial prediction grid In a spatiotemporal case you can export a time series of the output in text files by repeating the exporting process for a range of temporal instances gt The Save map data as text button is available for all types of maps in the visualization screen except for the BME prediction PDF maps at pre selected output locations gt When Matlab cannot obtain an estimate at a node it produces a result for that node that is called a NaN acronym for not a number quantity If NaNs are detected in the results during the exporting process SEKS GUI replaces them with the value 99999 gt f for any reason the output at a prediction node is a complex nonreal number SEKS GUI exports only the real part in the text file and skips the imaginary part Visualization Wizard 7 VISUALIZATION In this screen you can create a variety of plots using the SEKS GUI prediction output t this screen after the prediction stage the display below indicates what information reen directly from the SEKS GUI main menu please start by loading a SEKS GUI Mean of the variable estimation Main Menu lt lt ck BMElib Help Fig IIl C 6 59 6 Use the 2 buttons under the tag Space to plot output to choose whether to display t
113. using any of the choices b c or d of the earlier step 1 the following apply for each prediction node e The first moment mean of the raw results in the original space is the backtransformed mean of the BME mean in the transform space e The second moment variance in the original space is based on the BME variance in the transform space but it is not the direct backtransform of the BME variance In particular the variance value in the original space is rather a measure of the variance in the transform space This measure is obtained by backtransforming the standard deviation value from the transform space into the original space 32 e The third moment PDF skewness cannot be meaningfully backtransformed into the original space and it is therefore unavailable in the original space when you request only the BME Moments choice b in step 1 above If you specified the BME PDF or Confidence Intervals prediction types c or d in step 1 respectively then the BME posterior PDF is included in the results and can be backtransformed into the original space In this case skewness values are available in the original space and they are calculated based on the backtransformed PDF Upon completion of prediction computations you are prompted to save the outcome in a file You can do so or you can skip this action and run additional prediction tasks Matlab retains prediction results in the background At any point after a prediction task
114. utput Grid The example prediction grid is described in terms of grid limits and node spacing It is stored in Ozone 3 Input OutGrid txt Ozone has positive only values The file requests prediction in a temporal span of 5 consecutive days from July 6 to July 10 1988 The mean trend is stored in the Matlab file Ozone 4 MeanTrend mat The default parameter values that appear on the detrending stage of the exploratory analysis screen have been used to obtain the trend The Total Ozone data in the present example have been subjected to an N scores transformation prior to proceeding to the covariance analysis For empirical covariance information use the Ozone 5 EmpiricalCovariance Nsc mat Matlab file The covariance estimate has been computed by specifying maximum correlation ranges of 30 degrees in space and 5 days in time and by requesting computation in 8 spatial and 7 temporal lags A spatiotemporal covariance model has been fitted with 2 nested components The model details are stored in the text file Ozone 6 CovarianceModellnfo Nsc txt Load this model information but also play with the values provided here and the SEKS GUI sill range adjustment tools to familiarize better with the interface The BME prediction output is stored in the Ozone 7 Output BmeModCI Nsc mat Matlab file The output file contains the results of two tasks namely the BME Mode and the BME Confidence Interval at the 68 percentile prediction tasks For thes
115. wn case studies Some modest Matlab programming skills are required for this task In addition to the files in the folder Arsenic MapsMask you can also find a simple start up set of related files in the folder SEKS GUlv1 X X guiLibs Utilities applyMaskFiles There is some related information in Paragraph V 3 of this manual 2 Start Matlab and SEKS GUI and when prompted for information at the appropriate screens provide the following files and input BME analysis The task choice in the Choose a Task screen is BME Spatiotemporal Analysis Highlight the task and push the Start button to continue Hard Data Use Arsenic 1a Input HD txt in ASCII text format Alternatively you can see the structure of an Excel input file by equivalently using the Excel file Arsenic 1b Input HD xls instead It is important to check on the Hard Data Wizard screen the box that designates this is as a spatial only study Northing x Axis in Km is in data file column 1 Easting y Axis in Km is in data file column 2 Arsenic concentrations in ug L are in data file column 3 f you enter wrong information by mistake there might appear an error in the Matlab Command window In this case try to correct the error on the SEKS GUI screen and attempt to continue e Your Excel file can have a header for each column like file Arsenic 1b Input HD xls or it can contain only numeric columns like file Arsenic 1c Input HD NoHead xls

January 2013

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