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Prototype Toolkit for Water Quality User Manual

1. Prototype Toolkit Manual A major problem is the estimation of adequate atmospheric model parameter values as specified in the panel Atmosphere Incorrect values of the atmospheric model parameters will yield incorrect R 0 images and therefore incorrect water quality maps Various scenarios may be used to estimate the atmospheric model parameters depending on the available information Such scenarios are described in the subsections below 5 2 1 Climatological information is available Here the term climatological information refers to average values of atmospheric model parameters for certain regions such as an aerosol climatology In a limited sense such an aerosol climatology is already incorporated in the MODTRAN 3 model because predefined types of atmospheric models and aerosol models are stored in the code If only climatological information on atmospheric model parameters is available one may try to estimate atmospheric model parameters by selecting pixels of which the reflection properties can be estimated e g lawns roads or a lake with known reflectance properties The procedure then consists of the following steps 1 Identify pixels in the image whose surface reflection properties can be estimated 2 Obtain target and background spectra for these pixels from the remote sensing image the so called pixel dumps and fill an EXCEL worksheet in a special format with these spectra 3 Use the import
2. Prototype Toolkit Manual 5 1 2 Editing adding or copying sessions Pressing the button add copy or edit results in the appearance of the main window for radiative transfer calculations This window contains several panels labelled General Atmosphere Surface Calculation Simulation Atmospheric Corr and Interface Corr 5 1 2 1 The panel General Fig 24 The panel General of the atmospheric and interface correction module The panel General is used to specify the type of calculations one wishes to perform Options are i atmospheric correction ii interface correction iii simulation of the remote sensing signal and iv simulation of the surface ir radiance see Fig 24 The user has to select between two basic procedures i calculating correction parameters or ii simulation of ir radiances as is represented by the two sub panels displayed in Fig 24 The simulation option may be useful in several cases For example simulation of surface irradiance can be useful to calibrate atmospheric model parameters when surface irradiance measurements are available Such a calibration will result in more accurate atmospheric correction parameters Further simulation of RS spectra may be useful to check the results of atmospheric correction or to develop water quality algorithms that are less sensitive to atmospheric influences 27 Prototype Toolkit Manual 5 1 2 2 The panel Atm
3. In the following subsections the human interface of the radiative transfer module is first discussed and then some scenarios are described as an aid for using the software 25 Prototype Toolkit Manual 5 1 The Human Interface The user may select the entry Atmospheric Radiative Transfer from the Tools menu which brings up a window entitled Atmospheric Radiative Transfer showing names of previous sessions within the project In the title bar of this window the project code has been appended to the title in Fig 23 the code is 320 5 1 1 Overview of sessions Fig 23 The window Atmospheric radiative transfer Listed are the names of a few sessions named Modell 19 and Model125 By scrolling horizontally one can inspect the settings of the sessions The user has the option to add a new session or to edit an existing session see Fig 23 Additional options are to delete or to copy a session A session stands for of a set of diverse data all tied to model calculations such as viewing direction atmospheric model type aerosol type and a set of calculated spectra Scrolling in the Atmospheric radiative transfer window makes these data visible except for the spectra Spectra can be viewed using the entry Spectra in the Data menu In a new session spectra of previous sessions can be made visible making it possible to compare spectra calculated for different atmospheric models
4. Or 226642 MO GAR E R Ministerie van Verkeer en Waterstaat Directoraat Generaal Rijkswaterstaat Meetkundige Dienst Prototype Toolkit for Water Quality User Manual Software supporting operational use of remote sensing or water quality mapping qu ES M7 Ue 2 4 LJ lo P Prototype Toolkit for Water Quality User Manual Software supporting operational use of remote sensing for water quality mapping J F de Haan September 1996 Rapport nummer MDGAR 9637 Uitgave Rijkswaterstaat Meetkundige Dienst afdeling Remote Sensing en Photogrammetrie Postadres Postbus 5023 2600 GA Delft Bezoekadres Kanaalweg 3b tel 015 2691111 Samenstelling J F de Haan Summary This user manual contains relevant information for operating the Prototype Toolkit software that supports processing of remote sensing images of inland and coastal water Major parts deal with 1 archiving selecting and viewing of spectra ii performing atmospheric and air water interface correction and iii developing evaluating and applying water quality algorithms Most of this manual consists of edited selections of relevant parts of two BCRS reports that will appear shortly see the references Apart from these selections it contains detailed information on installation and use of the software Prototype Toolkit Manual Table of Contents TABLE OF CONTENTS 1 INTRODUCTION
5. Water quality parameters shows only the water quality parameters that have a value in the database Water quality parameter edit 36 DE DEELEN amp petgat Fig 10 Editing or adding water quality parameter values 3 1 3 Spectrum The non spectral attributes of the spectra may be edited as well Adding spectra to the database is carried out by the import function described in Sect 3 3 In the Spectra window see Fig 11 a list of spectra is given based on the selection criteria set in the selection window see Sect 1 5 2 for the selection procedure An individual spectrum is selected by clicking on one of the cells yielding a grey highlighted row and by pushing the Edit button the user can then alter the attributes of the spectrum see Fig 12 15 Prototype Toolkit Manual Fig 11 The window spectra lists the selected spectra with identical units Fig 12 The non spectral attributes of each spectra can be edited 3 2 Plotting of spectra As was mentioned in Sect 1 5 2 in the Spectra selection window the user can choose between one of the four units denoted as radiance irradiance attenuation and reflectance using the radio buttons at the bottom of the window shown in Fig 5 This provides a set of spectra as shown in Fig 11 Next the user can select one or more of these spectra using procedures as described in Sect 1 5 1 Finally the user can fill in the option
6. function of the Toolkit to transfer the pixel dump spectra to a Toolkit database 4 Calculate atmospheric correction parameters with the Toolkit using rough estimates of the atmospheric model parameters and apply them to the pixel dump spectra If the known surface reflection properties are R 0 spectra instead of Rapp spectra one needs in addition to calculate air water interface correction parameters and to apply them to the calculated Rapp spectra 5 Compare the calculated Rapp or R O spectra with the known or estimated reflection properties Generally the spectra will differ because inaccurate values for the atmospheric model parameters have been used in step 4 Repeating step 4 but for other values of the atmospheric model parameters should eventually provide agreement between calculated and known or estimated surface reflection properties 6 Once the agreement mentioned in step 5 is satisfactory the atmospheric model parameters are fixed as well as the resulting atmospheric correction parameters and air water interface correction parameters If the agreement is satisfactory for not one but for several different pixels in the image each having different reflection properties one may safely apply atmospheric correction to the entire image 7 If no satisfactory agreement can be found it may be that the estimated reflection properties of the surface are incorrect that there are calibration problems with the Remote Sensing i
7. button opens a window for selection and retrieval of R 0 spectra from the database The result of this selection is listed in Data For each spectrum the sample point code and the spectrum code of the R 0 spectrum is shown In addition the measured value of the water quality parameter is listed if available Also the independent variable i e the band combination is calculated and shown in the column X1 Finally the separate bands are listed under R01 R02 etc Fig 19 The panel Data of the water quality tool 22 Prototype Toolkit Manual A distinction is made between in situ spectra and remotely sensed pixel dumps Since at one sample point R 0 spectra from different instruments may be present in the database the user can be easily confused if they are listed simultaneously The button Deselect can be used to remove spectra from the data panel 4 3 1 Select R 0 for applying algorithm and for estimating coefficients Only those spectra are listed which have values at the centre wavelengths of the bands specified in WQ algorithm If the coefficients of the algorithm are known the algorithm will be automatically applied on the selected R 0 data yielding a calculated water quality parameter shown in the column calc WQP If the coefficients are not yet specified R 0 and water quality parameters must be selected in order to estimate the coefficients by linear regression Th
8. otherwise correction parameters can and will not be calculated for all of the bands It is advised to use a step size of 1 3 nm Taking a smaller step size than 1 nm increases the calculation time but hardly changes the calculated spectra The reason is that the internal database with a resolution of 20 cm is used for molecular absorption data and for the spectrum of the incident sunlight Fig 27 The Calculation panel of the atmospheric and interface correction module 30 Prototype Toolkit Manual Finally the panel Calculation contains the button Calculate which starts the MODTRAN calculations when pressed A DOS window is presented on the screen and some messages are printed Warnings about temperature profiles may be ignored but it may happen that error messages are printed it is advised to contact the developers of the software in that case The last three panels are used to show the results of the calculations and to apply the results of the calculations to remote sensing observations made above sample points the so called pixel dumps These panels will be discussed now 5 1 2 5 The panel Atmospheric Correction The fifth panel is shown in Fig 28 and is used i to show atmospheric correction spectra ii to calculate band averages of atmospheric correction parameters and iii to apply atmospheric correction to target and background spectra of a pixel dump The upper part is used to
9. these only Project Information Spectra Water Quality Parameters and Import Spectra are active The other entries have not been implemented Selecting Project Information opens a window that enables the user to select a project and edit associated information that belongs to that project Note that all procedures such as viewing spectra and performing atmospheric correction occur within the scope of a project Thus when selecting Spectra the user is shown a lists of spectra that belong to the project that has been selected See Sect 3 1 1 Spectra provides a window showing all radiance spectra stored in the database for that project the project code is displayed in the header of the window Initially only radiance spectra are shown Other spectra reflectance attenuation or irradiance can be shown by pressing the select button and choosing another category See Sects 3 1 3 and 3 2 e Water Quality Parameters provides a window listing sample points denoted by a sample point code and the values of the measured or calculated water quality parameters for that sample point See Sect 3 1 2 e Import Spectra provides a file selection window which may be used to select an EXCEL file that contains spectra associated water quality parameters and some additional data After selecting the EXCEL file which needs to be filled in a special format see Sect 3 3 the toolkit starts i
10. 1 1 1 REMOTE SENSING OF WATER QUALITY 1 1 1 1 THE IVM METHODOLOGY 2 1 1 2 AN EXTENDED METHODOLOGY 3 2 QUICK START _5 2 1 HARD AND SOFTWARE REQUIREMENTS 5 2 2 INSTALLATION 5 2 3 PREPARING THE DATABASE 6 2 3 1 MAINTENANCE AND REPAIR OF THE DATABASE 7 2 4 THE TOOLKIT MENU 7 2 4 1 FILE MENU 7 2 4 2 DATA MENU 8 2 4 3 TOOLS MENU 9 2 5 SELECTION PROCEDURES 9 2 5 1 SELECTION IN A DATA WINDOW USING THE MOUSE 9 2 5 2 SELECTION OF DATA USING A SELECTION WINDOW 3 THE SPECTRAL DATABASE 13 3 1 MANUALLY FILLING AND EDITING THE DATABASE 13 3 1 1 SAMPLE POINT 14 3 1 2 WATER QUALITY PARAMETERS 15 3 1 3 SPECTRUM 15 3 2 PLOTTING OF SPECTRA 16 3 3 IMPORT OF DATA INTO THE DATABASE 17 4 THE WATER QUALITY ALGORITHM TOOL 19 4 1 THE WINDOW WATER QUALITY ALGORITHM 19 4 2 THE PANEL WQ ALGORITHM 20 4 2 1 THE IN DEPENDENT VARIABLES 21 4 2 2 SELECTION OF SENSOR AND ASSIGNMENT OF BANDS 21 4 2 3 ENDING A SESSION 22 4 3 THE PANEL DATA 22 4 3 1 SELECT R 0 FOR APPLYING ALGORITHM AND FOR ESTIMATING COEFFICIENTS 23 4 4 THE PANEL COEFFICIENTS 23 4 5 THE PANEL VIEW OPTIONS 24 Prototype Toolkit Manual 5 THE ATMOSPHERIC RADIATIVE TRANSFER TOOL 1 25 5 1 THE HUMAN INTERFACE 26 5 1 1 OVERVIEW OF SESSIONS 26 5 1 2 EDITING ADDING OR COPYING SESSIONS 27 5 1 2 1 The panel General 27 5 1 2 2 The panel Atmosphere 28 5 1 2 3 The panel Surface 29 5 1 2 4 The panel Calculation 30 5 1 2 5 The panel Atmospher
11. 2 Hoannekritte N OUDE VENEN 5 T Sleatten N OUDE VENEN 6 9 Med OUDE VENEN 7 40 Med _ POLDERHOOFDKANAAL Kanaeldyk noord POLDERHOOFDKANAAL Kai ROTTIGE MEENTHE ROTTIGE MEENTHE 5 petgat Z Veluwemeer8 _ Veluwemeer SCHA Waterleidingplas zuid Waterleidin an informatietechnologie L4 lt De MD heeft drie produktsectoren J 1 Topografische Geo informatie TG V Geo informatie in de vorm van kaarten en of be Verzorging en topografische Advisering en onderzoek op het gebi technologie o a remote sensing GIS Produkten en diensten op het gebied v Advisering over in Vervaardigen van Kanaalweg 3b 2628 Delft b FO 023 2600 GA Delft Telefon 015 2691111 lefax 015 2618962
12. Lrs spectrum is available When selecting an Rapp the available Rapp spectra are shown Fig 5 The selection window for selecting spectra Prototype Toolkit Manual 3 The spectral database In this section which is in part based on Appendix B of Dekker and Hoogenboom 1996 the current user interface concerning the spectral database will be concisely explained Four aspects of the functionality will be considered Manually filling and editing the database Import of data into the database Selection and plotting of spectra Data conversion and calculation tools The first three aspects are directly linked to the human interface The data conversion and calculation tools are hidden in the software and do not yet have a direct link to the user interface All activities concerning the database are entered via the Data at the main menu see Fig 6 In the next sections the first three aspects of the functionality are treated in more detail Fig 6 The database is accessed by Data in the main menu 3 1 Manually filling and editing the database Filling and editing of data require very similar user interfaces and are therefore considered together Here the key data of the database Sample Point Water quality parameter and Spectrum are elaborated 13 Prototype Toolkit Manual 3 1 1 Sample point Project information Fig 7 The panel Sample points gives a list of the s
13. box Plot spectra see Fig 11 which yields an overlay plot window as shown in Fig 13 Here the legend contains the sample point code and the type of spectrum The plotting facilities are still limited in the prototype version of the software and hence no further graphical adaptations can made to the graph Due to these limitations in the plotting facilities unwanted lines to the origin are drawn when the number of ordinates differ for two plots 16 Prototype Toolkit Manual ETE Fig 13 Selected spectra can be plotted in overlay In the legend the sample point code and the type of spectrum is shown 3 3 Import of data into the database All measured spectra are entered into the database using the import function of the Toolkit In the Import window the user can browse to a file of interest see Fig 14 Pushing OK activates the import and all data in the spreadsheet are converted to the corresponding fields of the database In the prototype software only an Excel 5 0 file can be imported and MS ACCESS has to be installed otherwise the import function will not work The Excel spreadsheet must be formatted according to a specific template which can be customised by the user In the first column a label is specified and in the second and further columns the data values are stored Table 2 gives the contents of such a template The name and location of the template file can be altered in the initialisation file o
14. of the line red but does not select the data for regression calculations see also Sect 4 3 1 2 5 2 Selection of data using a selection window Usually when a select button is pressed a selection window is shown on the screen Its purpose is to reduce the lines listed in a data window We note that in case of spectra a pre selection has already been made by the software These pre selections will be discussed now 1 If spectra is selected from the data menu only radiance spectra are listed default unless another spectrum type has been selected during the session Spectra with another dimension attenuation reflectance irradiance can be made visible using the selection window If a further selection is desired one might select for instance Lrs as spectrum type in the selection window After pressing OK the spectrum window then lists all available Lrs spectra One can return to a list of all radiance spectra by selecting clear as the spectrum type in the selection window it clears previous selections see Fig 5 2 In the atmospheric correction part of the software often an Lrs Lrs b or Rapp spectrum has to be selected When a Lrs or Lrs b spectrum is needed the user can select a spectrum from a list of all of the available Lrs and Lrs b spectra This freedom to select for instance an Lrs spectrum when a Lrs b is needed is intentional It enables the user to perform atmospheric correction even when only an
15. spectrum with other spectra such as Rapp spectra that resulted from previous calculations or a measured Rapp spectrum In the present version of Toolkit I the two functionalities i calculating atmospheric correction parameters and ii testing and optimising these parameters are combined That is one can not calculate atmospheric correction parameters without first selecting remote sensing spectra pertaining to a pixel dump An advantage of this approach is that the system automatically selects the correct band sensitivity curves that correspond to the image that is to be processed 5 1 2 6 The panel Interface Correction Fig 29 shows the panel interface correction which is used to view the air water interface correction parameters upper part to calculate band averages and to apply interface correction to a selected Rep spectrum lower part yielding a R 0 spectrum The use of this panel is similar to that of the atmospheric correction panel discussed above However three remarks might be made Y Fig 29 The panel interface correction of the atmospheric and interface correction module 1 Only Rapp spectra can be selected that are stored in the database Thus after performing atmospheric correction one first has to save the calculated Rapp spectrum by pressing the OK button before one can select this spectrum for air water interface correction 2 The Rap spectrum that is created by atmospheric cor
16. the correction parameters and the determination of the coefficients o and B can be done outside the image processing system However for testing purposes steps 4 6 and 7 are also implemented in the Toolkit software but only for a subset of special pixels as will be discussed later The general procedure listed above assumes accurate estimates of atmospheric parameters Often such estimates are not directly available and one needs to estimate atmospheric parameters from results of additional measurements performed at one or more locations see Sect 5 2 In order to estimate atmospheric model parameters and to test the performance of atmospheric correction we select a set of special pixels in the image The L and L spectra corresponding to these pixels are often called pixel dumps These special pixels pertain to certain surface areas for which additional information is available These surface areas are often called sample points because they usually correspond to locations where water samples have been taken to estimate water quality parameters If no such special pixels occur in the image we have to create them in an artificial manner by estimating additional knowledge for some of the pixels For example for a particular pixel of the image a R 0 spectrum might be selected from the spectral library that is expected to be representative for the water there In the radiative transfer module special attention is given to procedures tha
17. when following scenario 1 apply established algorithm see Table 3 Nothing of the algorithm can be changed in this scenario When the user wants to adapt an existing algorithm e g estimating coefficients using new data scenario 2 adapt algorithm in Table 3 the Copy button is pushed A temporary algorithm is opened in which the selected algorithm is copied The temporary algorithm can be saved under another name The third scenario development of a new algorithm is accessed by add A blank algorithm is opened which must be completely specified by the user With Delete selected algorithms can be deleted from the database and with Close the window is closed After pressing Add Copy or Apply in the overview window a new window is opened with four tabs WQ Algorithms Data Coefficients and View Options In the next sections each panel will be considered in more detail 4 2 The panel WQ Algorithm In the panel WQ algorithm the form of the algorithm is specified i e the water quality parameter the band combination and the instrument are selected Also the name of the algorithm can be changed except when the apply button was used and notes can be added The general formulation of the algorithms is see also Sect 2 2 water quality parameter dependent variable combination of R 0 bands independent variable Dependent variable Intercept Regression coef
18. 4 in the Toolkit directory which will contain a listing of the most recent simulated ir radiances in tabular form see Appendix A of the Toolkit I report Opening tape4 from within EXCEL seems to be the easiest way to get access to the data Presently it is not possible to simulate band averages of ir radiances of simulated spectra Calculation of band averages is only possible for the correction parameters Atmospheric radiative transfer edit 362 Fig 30 The panel simulation of the atmospheric and interface correction module 33 Prototype Toolkit Manual 5 1 3 Inactive sub panels of the Interface Depending on the selection made in the panel General some parts of the interface have been made inactive For example when the user selects atmospheric correction in the first panel surface reflection properties are irrelevant and the user can not modify entries in this panel In fact irrelevant subpanels are frozen by the software as a guide to the user see Table 7 Table 7 Scheme of the active and inactive parts of the interface depending on the selections made in the panel general general atmo surface calculation atmos interface simulation sphere corr corr atm corr active inactive active active inactive inactive interface active partially active active inactive active inactive corr lower part simulation active partially active active inactive
19. BAND13 763 00 517E 02 763 00 10 00 CASI95 BAND14 820 00 556E 02 820 00 12 00 195 BAND15 wvingth 413 00 820 00 wvingth 413 00 820 00 wvingth 413 00 820 00 wvingth 413 00 820 00 band average 195 01 1298 01 band average 951E 00 290E 00 band average 219E 00 143E 00 band average 630 01 390E 01 effect wvlngth 413 00 820 00 effect wvlngth 413 00 820 00 effect wvlngth 413 00 820 00 effect wvingth 413 00 820 00 Table 9 Same as Table 6 but for the air water interface correction parameters d and d d and d do not depend on the wavelength and are not listed cf Sect 2 4 2 of De Haan and Kokke 1996 Di cntr wvingth band average effect wvlngth 413 00 438 00 490 00 510 50 820 00 wvingth 413 00 820 00 110E 01 103E 01 901E 02 856E 02 472E 02 band average 166 00 253E 00 413 00 438 00 490 00 510 60 820 00 effect wvlngth 413 00 820 00 When satisfactory results have been obtained one collects the band averages written on the text files bandsim out and renamed copies i e the parameters for atmospheric and air water interface correction transports them to an imaging system and uses these parameters to create R 0 images for the various wavelength bands Next one may apply existing or newly developed algorithms to transform the R 0 images into water quality maps 35
20. Manual 6 Apply air water interface correction to the R images created in step 4 using d d Ripp Ros The result of this step is a subsurface irradiance reflectance R 0 image for each wavelength band Asa last step one has to interpret the R 0 data using water quality algorithms such as W f R 0 R 0 R 0 where W is a water quality parameter fis a function of the subsurface reflectance in various wavelength bands The coefficients a and B may be derived using regression analysis employing known spectra R 0 and associated water quality parameters Examples of water quality parameters are the chlorophyll a pigment concentration the yellow substance concentration the total suspended matter concentration and the Secchi depth Specific forms of the function fare discussed in Sect 2 of Dekker and Hoogenboom 1996 see also Sect 4 of this manual Key quantities in this procedure are i the atmospheric correction parameters C2 C4 and cs ii the air water interface correction parameters d d d and d and iii the coefficients in the water quality algorithm and B The toolkit provides tools to calculate these key quantities Often calculation of the correction parameters will be performed at a different location than the actual correction of the images takes place Steps 1 2 4 6 and 7 need to be performed using an image processing system Steps 3 and 5 the calculation of
21. alisation file used for import MODTRAN 3 32 bits DOS extender transforms cm to nm averaging of wavelength bands surface reflectance spectra CORRECTION PARAMETERS input file for bandsim output from scan exe modtran3 input file modtran3 large output file modtran3 short output file Prototype Toolkit Manual Appendix B Spectra Table B 1 lists the spectra in the Toolkit database and their dimension see Table SpectrumType in the database tk info mdb in the toolkit directory Table B 1 A list of the spectra in the database 1 Clear r field E j 2 Rapp _ Apparent radiance reflectance 3 Lpanel upwelling radiance from panel W m 2 nm 1 sr 1 F 4 Lau upwelling radiance from target jWm 2nm1sri 5 Lpanel dif upwelling diffuse radiance from panel es 6 Ead dif diffuse downwelling irradiance j W m 2 nm 1 sr 1 fi In mET absorption phytoplankton _ 1 absorption aquatic humus m 1 erc my total absorption 1 cn _ total beam attenuation mi ground radiance W m 2 nm 1 sr 1 path radiance W m 2 nm 1 sr 1 single scattering albedo remotely sensed radiance pixel _ W m 2 nm 1 sr 1 reflectance of panel ud W m 2 nm 1 sr 1 LW m 2 nm 1 sr 1 subsurface irradiance reflectance subsurface upwel
22. ample points in a project The code of the project is given between brackets in the window bar Sample point edit 362 Fig 8 Similar windows are used for editing and adding data in a sample point In the window Project information data of the entities Project and Sample Point can be added and edited Fig 7 shows the panel Sample points which gives a list of the sample points within a project The project code is given between brackets in the top bar of the window e g 362 in Fig 7 and all actions relate to this project The button Add is used to assign a sample point that is available in the database see Sect 1 3 to the project The Edit button of the Sample points panel gives access to the window shown in Fig 8 When positions date or time are edited the software calculates the corresponding Sun zenith and azimuth 14 Prototype Toolkit Manual 3 1 2 Water quality parameters The window Water quality parameters shows only those water quality parameters that have a value in the database As an example Fig 9 shows three water quality parameters that have been measured in situ CHL DW SD and also the chlorophyll CHL that was calculated using the Water quality algorithm tool Values in this list of water quality parameters can be added or edited using the Edit and buttons this activates a new window see Fig 10 Fig 9 The window
23. ction parameter printed in the header 5 2 Use of the Atmospheric Radiative Transfer Tool In general one proceeds as follows In the first panel one specifies the type of calculations that are to be performed Next panels 2 4 are used to specify the atmosphere surface system the geometry and the calculation options One then presses the button calculate and waits until the calculations have been performed Finally one uses the last three panels to view the results and to compare the results with those of previous sessions 34 Prototype Toolkit Manual Table 8 A listing of parts of the file bandsim out showing the in band averages of atmospheric correction parameters c c5 In addition to the band averages central and effective wavelengths of each band and the Full Width Half Maximum of each band are listed ci cntr wvingth band average effect wvlngth FWHM 413 00 339E 01 413 00 18 00 CASI95 BAND1 438 00 313E 01 438 00 18 00 195 BAND2 490 00 293E 01 490 00 18 00 CASI9S BAND3 510 50 264E 01 510 60 17 00 195 BAND4 544 00 232E 01 544 00 10 00 CASI95 BANDS 564 50 213E 01 564 60 9 00 CASISS BANDE 585 50 193E 01 585 60 9 00 CASI9S BAND7 600 00 181E 01 600 00 10 00 CASI95 BANDB 625 00 168E 01 625 00 10 00 CASI95 BANDS 648 00 147E 01 648 00 10 00 CASI95 BAND10 676 50 136E 01 676 60 9 00 95 BAND11 691 00 109E 01 691 00 10 00 CASI95 BAND12 705 00 107E 01 705 00 8 00 CASI95
24. d the functionality of the radiative transfer module if the atmospheric optical properties are generally known with sufficient accuracy However these properties are generally not well established and have therefore to be estimated using the Toolkit software Hence the functionality was extended in the following manner e a facility to simulate surface ir radiances which can be used for calibrating atmospheric optical properties provided such surface ir radiances are measured during overpass afacility to perform atmospheric correction and air water interface correction for sample points which can also be used to calibrate atmospheric optical parameters provided R 0 spectra are known or can be estimated for these sample points These tasks are sufficient to calculate R 0 from calibrated remote sensing images and to produce water quality maps Finally the following task was added to the module simulation of the remote sensing radiances Lrs for different altitudes geometries different surface reflectances and different atmospheric conditions presently only for high resolution spectra Although not strictly required for the methodology listed in Sect 2 2 this option is useful to i select wavelength bands for new sensors ii detect possible calibration errors either for the atmospheric model or for the sensor iii to test internal consistency and iv to determine optimal viewing geometries and flight altitudes
25. develop new water quality algorithms Phase 6 application of remote sensing of water quality algorithms to the remote sensing data In phase 6 the application of the algorithms to the remote sensing data is carried out In practice it is usually found that initial application of the algorithm to the remote sensing data leads to anomalous results in the image Often it is required to backtrack along the phases two to five to find the source of error This backtracking is still a remote sensing expert task unfortunately 1 1 2 An extended methodology The phases listed above represent the IVM methodology as it existed at the start of the Toolkit project This methodology can be applied with more or less advanced forms of atmospheric correction If less advanced forms are used the algorithms have to be revised often because of the disturbing effects of the atmosphere This means that many in situ measurements have to be performed in each remote sensing campaign in order to validate or calibrate the algorithms One aim of the Toolkit project is to try to reduce the number of required in situ measurements Therefore we extended the methodology with an advanced atmospheric correction procedure This resulted in an explicit procedure for transforming remote sensing images into water quality maps as described below 1 Transform digital numbers of the image into spectrally averaged radiances for each wavelength band of the image using calibration co
26. efficients which yields the remote sensing radiance of the target pixel La 2 Determine for each pixel the spatially averaged background radiance L This spatially averaged radiance is used to take adjacency effects into account The averaging should correspond to a surface area of 0 1 1 square kilometre 3 Calculate atmospheric correction spectra using a model atmosphere that is representative of the actual condition of the atmosphere during the time the image was taken If the optical properties of the atmosphere or viewing directions differ for different parts of the image one should repeat the procedure for several locations of the image and interpolate to obtain correction parameters for the entire image The atmospheric correction spectra are denoted as C2 C4 and cs 4 Apply atmospheric correction to the image Specifically calculate the irradiance reflectance just above the water surface Rap for each wavelength band and for each pixel in the image from the remote sensing radiances er c Ly C bren REEL EIE ca tCsL p 5 Calculate air water correction parameters denoted as d d ds and d using calculated values of 1 the ratio of diffuse to total surface irradiance Fy the sky radiance in a direction so that it will later be reflected towards the remote sensing instrument Lag 8 and iii the total surface irradiance see the Toolkit I report for specifics Prototype Toolkit
27. elect some predefined surface reflectance spectra taken from the literature which are stored in the Toolkit database Alternatively the user can select a surface reflectance spectrum that has been imported in the non permanent database by first selecting Database spectrum and then pressing the button Select This will result in the appearance of a window listing available reflectance spectra one of which can be selected The lower part of the panel is available to change the index of refraction and the Q factor that accounts for bi directional reflection properties of the water body see also Sect 2 4 of De Haan and Kokke 1996 5 1 2 4 The panel Calculation The panel calculation Fig 27 is used to specify the solar and viewing geometry and some calculation options Presently the user first has to select an L spectrum from the database which includes associated geo information using the select button in the upper right part of the panel The geometrical parameters pertaining to the selected spectrum are then copied to the panel entries so that the user does not have to type the parameter values that are already stored in the database If desired the user may edit these geometries In the second subpanel the user can enter the wavelength range and step size for the MODTRAN calculations In case of atmospheric correction this wavelength range should cover the complete range spanned by the wavelength bands of the sensor
28. erived from 1 apply established database algorithm 2 adapt established database algorithm Specific types of water quality algorithms have been pre programmed in the toolkit These types are listed in Table 4 Here the symbols R2 and R3 represent values of A 0 for different wavelength bands The user can extend this list of algorithms types only by using ACCESS not by using the toolkit software see the tables IVFormula and FormulaVariables in the database tk info mdb in the Toolkit directory Table 4 Water quality algorithm types that have been implemented in the Toolkit 4 1 The window Water quality algorithm The water quality algorithm tool starts with an overview of all algorithms that are available in the current library as is illustrated in Fig 15 The number listed in the title bar denotes the project code of the current project Each algorithm is uniquely specified by its name which is listed in the column algorithm Specific information about these algorithms is shown in other columns such as the water quality parameter involved the type of algorithm used listed under indep var and values of the coefficients not visible in Fig 15 19 Prototype Toolkit Manual Fig 15 The overview window of the water quality algorithm tool After selecting an algorithm it can be applied to data from the spectral database by using the Apply button This is used
29. etter Minimal memory 8 Mb RAM Minimal 8 Mb hard disk space spectral library not included SVGA monitor driver Software requirements MS Windows 3 11 3 1 presently the stability under Windows 95 is not guaranteed MS Access 2 0 used to import spectra and to export results Stability Use of QEMM as memory manager is not recommended The DOS memory manager provides a more stable environment for Visual Basic applications such as the Toolkit MS Access operates in a stable manner for the following networks Microsoft LAN Manager Windows for Workgroups Novell Netware versions 2 x and 3 x Artisoft Lantastic Banyan VINES 2 2 Installation Insert the first of the three Toolkit diskettes into drive A and type A setup exe The installation program will ask you to specify the directory where the toolkit is to be installed The installation process performs the following tasks It copies files to the toolkit directory see Appendix A for a list of the relevant files e It copies the device driver dosxnt 386 to the C windows system directory This device driver is required for the radiative transfer calculations Itadds the following line to the file C windows system ini in the 386Enh section device c windows system dosxnt 386 It updates initialisation files Itcreates a program group in the program manager window and a Toolkit icon The user needs to restart windows to make the change
30. f the library So for each library a different template may be defined w Import 36 Ber projects C3 rsnorth toolkit Fig 14 With import data from an Excel spreadsheet can be imported using a Excel template 17 Prototype Toolkit Manual Table 2 An example of the template used for importing data in the database The template has a text format Project Sample Point SPCode SAMPLE POINT CODE Type SPTYPE SPCoordinateX LATITUDE SPCoordinateY LONGITUDE SPDate DATE SPTime LOCAL TIME SPBottomDepth DEPTH SPWindSpeed WIND SPEED SPWindDirection WIND DIRECTION SPWaveHeight WAVEHEIGHT SPHorizontalVisibility HORIZONTAL VISIBILITY SPCloudTypesCLOUDTYPE SPCloudThickness SPNote NOTES war WQField WQ NAME WOQValueField WO VALUE Spectrum SpectrumName SPEC NAME SpectrumTime SPEC TIME SpectrumType SPEC TYPE SpectrumHeight SPEC HEIGHT SpectrumStatus SPEC STATUS SpectrumNote SPEC NOTES SpectrumTarget SpectrumViewZenith SPEC ZENITH SpectrumViewAzimuth SpectrumintegrationTime INT TIME InstrumentCode INSTRUMENT Formats PositionFormat LAT LON TimeFormat UTC text only code max 8 characters t Remote sensing sample point In situ measurement def Fictive sample point 18 columns degrees integer neg S minutes integer seconds double 3 columns degrees integer neg W minutes integer seconds double formats dd mm yy dd mmm yyyy dd mmmm yyyy english formats hh mm ss hh mm AM PMI
31. ficient Independent variable 20 Prototype Toolkit Manual Vater Quality Algorithm copy 320 Fig 17 The combinations of bands implemented in the database 4 2 1 The in dependent variables All water quality parameters that are implemented in the database see Appendix C can be selected as a dependent variable This gives maximum flexibility for the user without changing the database The independent variables are a number of band combinations which are already stored in the database A list of band combinations currently implemented is given in Table 4 and shown in Fig 17 4 2 2 Selection of sensor and assignment of bands The bands in the band combination are not linked to a specific band position but are denoted with R1 R2 etc In case of adapting or developing an algorithm each band must be assigned to a position of a band by specifying the centre wavelength of the band If an instrument does not contain the given position an error occurs when the R 0 spectra are selected in the Data panel As a result the user might have to inspect the table SpectrumData of the project database e g ck data mdb or rsnorth mdb to find the precise values of the wavelengths as they are stored in the database NOTE the values stored in the permanent database inst rmnt mdb can not be used to obtain this information on the wavelengths 21 Prototype Toolkit Manual Suppose the user has calculated a water
32. hh mm double m double m s integer deg default 999 double default 999 double km tekst value from external table double default value supplied by CloudType but user can modify if needed text all unrecognised data are put in SPNotes text use codes of Toolkit in adjacent columns double value of WOP labelled in previous row text required max 12 pos SPCode number unique for project Format hh mm ss hh mm AM PM hh mm text required use types of Toolkit idouble m dist Validated None default text itext max 60 pos double deg double deg double sec text max 20 pos defaults Empty list LAT LON or RD or UTM list UTC or MEST Prototype Toolkit Manual 4 The water quality algorithm tool This section is based on Dekker and Hoogenboom 1996 Sect 2 4 3 and Appendix A The water quality algorithm tool can be used to develop validate and apply water quality algorithms Each algorithm calculates a water quality parameter from a combination of R 0 wavelength bands of a selected sensor The data needed to calculate the coefficients of the water quality algorithms are obtained from the spectral database Table 3 summarises the various uses that can be made of the water quality algorithm tool Table 3 Three scenarios were distinguished for use of the water quality algorithm module in the Toolkit band combination wavelengths is derived from of bands is d
33. ic Correction 31 5 1 2 6 The panel Interface Correction 32 5 1 2 7 The panel Simulation 33 5 1 3 INACTIVE SUB PANELS OF THE INTERFACE 34 5 1 4 CORRECTION PARAMETERS ON FILE 34 5 2 USE OF THE ATMOSPHERIC RADIATIVE TRANSFER TOOL 34 5 2 1 CLIMATOLOGICAL INFORMATION IS AVAILABLE 36 5 2 2 OR R 0 PERTAINING TO A PIXEL DUMP IS AVAILABLE 36 5 2 3 SURFACE IR RADIANCES ARE AVAILABLE 37 5 2 4 SIMULATION OF THE SENSOR SIGNAL 37 5 2 5 USE OF WATER QUALITY PARAMETERS 37 HERERENCE AL Prototype Toolkit Manual 1 Introduction This document is a user manual of the toolkit prototype software The toolkit is a set of software tools that provide key parameters needed for deriving thematic water quality maps from remote sensing images The toolkit software consists of three main parts an advanced radiative transfer module for simulation and atmospheric correction a water quality algorithm module for determining water quality parameters and a spectral library module not yet fully implemented which contains water quality parameters and associated spectra of the subsurface irradiance reflectance The combination of these modules in one software package yields an invaluable tool for quantitative interpretation of remote sensing images of coastal and inland waters As with any complicated task such as developing the toolkit software it takes time to do it right and o
34. ig 22 Either the calculated water quality parameter is plotted versus the band combination or the measured water quality parameters are plotted versus the calculated water quality parameters The user can plot the data selected for the coefficient estimation denoted by a V mark in the first column as illustrated in Fig 20 or all data that are shown in the Data panel In addition a line representing the water quality algorithm can be shown although this is only meaningful if the WQP versus independent variable is plotted Water Quality Algorithm copy 362 ld Fig 22 In View options the appearance of scatter plot can be changed Prototype Toolkit Manual 5 The Atmospheric Radiative Transfer Tool This section is based on Sect 4 of De Haan and Kokke 1996 The atmospheric radiative transfer module is an instrument that can be used to perform the following tasks to calculate the atmospheric correction parameters c cs for each wavelength band to calculate the air water interface correction parameters d d for each wavelength band These correction parameters can then be used to transform the radiance image L into a subsurface reflectance image R 0 Such a R 0 image can then be transformed into water quality images using water quality algorithms see Sect 2 2 and Sect 4 These tasks are sufficient to perform all of the steps listed in Sect 2 2 There would be little need to exten
35. inactive partially active RS upper part upper part simulation active inactive active inactive inactive partially active surface lower part atm and active partially active active active active inactive interf corr lower part RS and active partially active active inactive inactive active surface upper part simulation In the column surface the entry upper part pertains to surface reference spectrum and the entry lower part pertains to air water interface parameters In the column simulation the entry upper part pertains to remote sensing spectra and the entry lower part pertains to surface ir radiance values 5 1 4 Correction Parameters on File In this section the output written to the file bandsim out is briefly discussed see also Appendix B of De Haan and Kokke 1996 Examples for CASI spectra are shown in Tables 8 and 9 for atmospheric and air water interface correction parameters respectively The values listed in the tables were calculated using the following parameter values Sensor height 3 0 km midlatitude summer atmospheric model rural aerosols a horizontal visibility of 10 km no clouds or rain a solar zenith angle of 45 degrees a sensor zenith angle of 180 degrees a solar and sensor azimuth of 0 degrees a wavelength interval of 400 900 nm with a step of 1 nm and LOWTRAN as the number of streams The column band average lists the value of the corre
36. information that will be useful for understanding the toolkit software There is a substantial overlap between parts of these reports and this user manual Sections of these reports have been copied edited and added to this user manual The aim was to make a complete user manual so that the user is not forced to consult three documents this manual and two reports when working with the toolkit software This manual is structured in the following manner Section 2 is a mini manual which is expected to provide sufficient information for installing and using the toolkit software when the user is already familiar with the Toolkit I and Toolkit II reports Section 3 focuses on the spectral database module of the software Section 4 is devoted to the water quality algorithm tool Section 5 deals with the atmospheric radiative transfer tool The remainder of the section is a brief introduction to methods used for deriving water quality maps from remote sensing images 1 1 Remote Sensing of Water Quality This section deals with methods to derive water quality maps from remote sensing images It is based on Sect 1 3 of Dekker and Hoogenboom 1996 and Sect 4 1 of De Haan and Kokke 1996 The philosophy behind the Toolkit projects is to apply integrated RS algorithms applicable to all inland and tidal waters with minimal in situ measurements and to streamline the production of water quality images The Toolkit contains several modules for correction prod
37. is selection is carried out by clicking at the sample points of interest in the first column labelled s A V sign appears for the selected sample points as illustrated in Fig 20 Fig 20 Sample points that are used as input for estimating algorithm coefficients are selected in the first column 4 4 The panel Coefficients In the panel Coefficients the two coefficients of the water quality algorithm the regression coefficient and the intercept are shown see Fig 21 They can be estimated with linear regression or can be altered manually With Calculate a linear regression fit is carried out including some descriptive statistics After the coefficients are changed the WQ algorithm must be applied again to the data in order to calculate the water quality parameter from the R 0 spectra The coefficients cannot be changed or estimated if the apply button is used in the water quality algorithm window see Fig 15 Water Quality Algorithm 362 Fig 21 In the panel Coefficients algorithm coefficients are shown which can be estimated or changed manually Prototype Toolkit Manual 4 5 The panel View options In the panel View options the appearance of the plot of the data and or the algorithm can be altered the plot can be activated in the Data panel In the prototype version the user can choose between two types of graphs and can select the data that must be shown see F
38. kit software The main menu entries are File Edit Map View Data Tools Window and Help see Fig 1 Of these menu entries only File Data and Tools can be made active in this prototype version Hence the menus Edit Map View Window and Help will not be discussed further in this document 2 4 1 File menu The file menu initially has the entries New Library Open Library and Exit available After opening a file a database the additional entries Delete Library and Close Library can be activated Selecting New Library creates a new library which contains some basic information such as sensitivity curves of remote sensing instruments It does not contain spectra Selecting Open Library will provide a file selection window where the user can select an existing ACCESS database extension mdb Note that some of the Toolkit databases are reserved for Prototype Toolkit Manual private use by the toolkit contact mdb instrmnt mdb tk info mdb and tk leeg mdb The entries Exit Delete Library and Close Library speak for themselves TOOLKIT File Edit Map View Data Tools Window Help Fig 1 The start up window of the Toolkit software 2 4 2 Data menu The data menu contains the following entries Project Information Spectra Water Quality Parameters Instrument External Library Import Spectra Export Spectra and Options Of
39. l Perform atmospheric and air water interface correction using measured radiances pixel dump corresponding to the site where in situ measurements are available yielding R O values for the water sample site Here default values of the atmospheric model parameters may be used 2 Apply water quality algorithms to derive some of the water quality parameters from the calculated R O values 3 Compare the numerical values of these calculated water quality parameters with the measured water quality parameters and adjust the atmospheric model parameters until agreement between calculated and measured water quality parameters is obtained 4 Repeatthis procedure for various water quality parameters until a consistent set of atmospheric model parameters is obtained The accuracy of this procedure depends not only on the atmospheric correction procedure but also on the accuracy of the water quality algorithms and the accuracy of the analysis of the water sample 37 Prototype Toolkit Manual References Dekker A G et al 1996a Spectral Library of Dutch waters in preparation Dekker A G and Hoogenboom H J 1996 Operational Tools for Remote Sensing of Water Quality a Prototype Toolkit submitted as BCRS report Haan J F de Kokke J M M 1996 Remote Sensing Algorithm Development TOOLKIT I Operationalisation of Tools for Atmospheric Correction of Remote Sensing Data of Coastal and Inland Waters submitted as BCRS rep
40. ling radiance W m 2 nm 1 sr 1 ubsurface downwelling irradiance IWm 2nm 1 W m 2 nm 1 background remotely sensed radiance W m 2 nm 1 sr 1 atmospheric path radiance W m 2 nm 1 sr 1 background path radiance W m 2nm 1sr 1 o absorption coefficient tripton m1 _ total scattering coefficient m scattering coefficient phytoplankton mi lt scattering coefficient ag humus mi _ scattering coefficient tripton m1 downwelling irradiance at sensor level W m 2 nm 1 backscattering albedo reflectance at sensor level EE Prototype Toolkit Manual Appendix C Water Quality Parameters Table C 1 lists the water quality parameters in the Toolkit database and their dimension see Table WQ in the database tk info mdb in the toolkit directory Table C 1 A list of the water quality parameters in the database AR asrest img 1 1 CHL sum chlorophylla and chlorofyl a ug 1 1 chlorid chloride mg HT cec de cyanophycocyanin ug 1 1 CPE cyanophycoerythin cyanophycoerythrine s ug HT Dflow Apes algensamenstelling flowcytometer n ml 1 Dmic E algensamenstelling microscopisch n ml 1 DOC issolved organic carbon opgelost organische stof img F1 DW
41. mporting the data Note that this import function can also be used if water quality parameters not spectra are to be imported Prototype Toolkit Manual 2 4 3 Tools menu The Tools menu has two entries Atmospheric radiative transfer and Water quality algorithm e Atmospheric radiative transfer provides access to radiative transfer calculations using MODTRAN 3 It shows a window containing a list of so called sessions Each session corresponds to a set of diverse data all of which are related to radiative transfer calculations for a model atmosphere Performing radiative transfer calculations is regarded as editing or adding such sessions The interface to MODTRAN 3 can be reached by pressing the buttons add edit or copy See Sect 5 e Water quality algorithm provides access to a tool for developing and testing water quality algorithms See Sect 4 2 5 Selection procedures Selection procedures in the toolkit software will be described in this section First selection in a data window is discussed then selection in a selection window is addressed 2 5 1 Selection in a data window using the mouse In the toolkit software three different selection mechanisms are used for selection in a data window These are Inthe project information window a project is selected by clicking on that line A selected line is darker than the other lines For example in Fig 2 the project Wildeboe
42. n the database Apart from the sample points the user might need to modify the type of water quality algorithm see also Sect 4 of this manual Information on spectral bands and instruments are stored in the database instrmnt mdb This database contains three tables CalibrationSpectrum sensitivity curves of the spectral bands Instrument listing of the instruments in the database InstrumentBand lists the spectral bands for each instrument By editing these tables one may add a new instrument to the system or modify the sensitivity curves of the existing instruments 2 3 4 Maintenance and repair of the database It may happen in exceptional cases that a library e g the file tk data has been damaged Attempting to open such a damaged library gives an error One can often repair such a damaged library as follows 1 Start ACCESS Ifa database is open close it first Select repair database under the File menu In the file selection window select the database that is to be repaired Exit ACCESS wr As spectra are added to and deleted from the database database may become larger than strictly required The database may be restored to its minimum size by using compress database instead of repair database from the file menu Periodically compressing databases will improve the performance of the Toolkit 2 4 The Toolkit Menu In this section we will introduce the main menu entries of the tool
43. ne can never do it right in a straightforward manner Instead a twisted road is generally followed during the development The prototype software that is described in this user manual shows the signs of such a twisted road It is our intention that a second version of the toolkit software is more straightforward and easier to use As a result the software described here is rather difficult to use A second more fundamental reason why the use of the toolkit software is complicated is the following Not one fully standardised method has yet been developed to interpret remote sensing images of coastal and inland waters Therefore the toolkit software should be able to support different methods It might be useful to note that one can not first select the optimal method and then develop the toolkit software because one needs the toolkit software for evaluating various methods The resulting need for flexibility combined with time constraints which made it impossible to develop an elaborate user interface resulted in a non intuitive user interface This manual attempts to address problems resulting from a non intuitive user interface by providing background information and so called use scenarios Apart from this manual two other documents will be useful when working with the toolkit software These are the concept BCRS reports of the Toolkit 1 and Toolkit II projects De Haan and Kokke 1996 and Dekker and Hoogenboom 1996 These reports give background
44. nstrument or that the limited set of atmospheric parameters that can be changed in the Toolkit module are not sufficient to represent the optical properties of the atmosphere It depends on the circumstances what the best action would be in that case 5 2 2 Rap or R 0 pertaining to a pixel dump is available Essentially the same procedure as listed above in Sect 5 2 1 may be used if measurements of Rapp or R 0 are available Because measured values of Rap or R 0 are more reliable than estimated values one may expect to get more accurate atmospheric correction parameters in this case 36 Prototype Toolkit Manual 5 2 3 Surface ir radiances are available If measurements of surface ir radiances e g zenith brightness total or direct surface irradiance above water are available they can also be used to constrain the atmospheric model parameters In this case one can first calculate surface ir radiances using the simulation option in the panel general of the atmospheric and air water interface correction module Once the calculated spectrum agrees with the measured spectrum one may expect that the atmospheric model parameters will reasonably well agree with the actual parameters Using these model parameters one can calculate the atmospheric and air water interface correction parameters and apply them to the image 5 2 4 Simulation of the sensor signal In Sects 5 2 1 and 5 2 2 it was assumed that spect
45. odes locations ii water quality algorithms iii instruments and sensor band information Such editing can not be done using the toolkit itself but requires some editing from within MS ACCESS The user might need to consult documentation on MS ACCESS to perform these editing steps The toolkit software deals with spectra and water quality parameters at specific sites called sample points see also Sect 2 2 For identification purposes all spectra and water quality parameters are stored using a sample point code as label Because the software needs to know where to store imported data the user has to supply the appropriate sample point code whenever data are imported In practice projects involve a limited number of sample points where additional information is gathered and water samples are taken that are later analysed in the laboratory However for each user this set of sample points will be different A set of sample point codes used by the Institute for Environmental Studies IVM is available in the initial database This set might not be adequate for other users In that case these users will have to edit the location database called location mdb This database contains four tables StudyArea Prototype Toolkit Manual StudyAreaPosition e Waterbody WaterbodySP Using ACCESS the user may edit these tables and insert sample points relevant to his own projects Appendix F lists the sample points initially stored i
46. on presents an overview of the methodology currently used at the The IVM methodology for remote sensing of water quality was chosen for developing the prototype of the Toolkit software It is seen as a starting point which may be extended and improved in the future This methodology was designed for airborne remote sensing of inland waters but is also applicable to remote sensing of turbid coastal waters as well as to satellite remote sensing Satellite remote sensing data is easier to process because many tasks concerning acquisition and initial processing of data are carried out by the data provider In the IVM methodology five phases are distinguished which are described below Phase 1 preparation Starting point of the current IVM method is an airborne remote sensing flight over different study areas with numerous targets Such a complex remote sensing campaign requires a careful preparation The preparation of the remote sensing flight itself requires much attention Most important products in this phase are a flight scenario and a ground truth measurement protocol Phase 2 data collection Extensive ground truth measurements are required involving many persons and institutes In the execution phase the remote sensing flight and the ground truth campaign are carried out Ideally the instruments are cross calibrated using reference targets after which a large amount of raw remote sensing data is collected If available the raw rem
47. ort mei 1996 38 Prototype Toolkit Manual Appendix A Toolkit files Three categories of files are distinguished Data files Software files and Modtran files The data files are databases extension mdb that can be opened inspected and manipulated by using Access except for the initialisation file extension ini Except for the executables the Modtran files are text files that can be read using a text editor Data files lt library gt mdb lt library gt ini lt location data gt mdb lt organisation data gt mdb lt general data gt mdb lt instrument data gt mdb lt template database gt mdb Software files lt image gt exe lt image gt ini lt template gt tpl gsw exe cmdialog vbx cscapt vbx eschk vbx esconbo vbx csopt vbx cspict vbx cstext vbx csvlist vbx graph vbx msoutlin vbx qplist vbx threed vbx truegrid vbx vsvbx vbx Gswdll dll msabc200 d11 msafinx dll msajt112 a11 msajt200 dll qpro200 d11 vbdb300 dll vboa300 d11 Modtran files modtran exe dosxmsf exe scan exe bandsim exe refbkg bandsim out bandsim in tape4 tapes tape6 tape7 0000000 uuu tk data mdb tk data ini location mdb contact mdb user database initialisation file private database private database tk info mdb private database instrmnt mdb private database tk_leeg mdb private database 51090196 51090196 excel tpl 39 Toolkit executable initi
48. osphere Fig 25 The panel Atmosphere of the atmospheric and interface correction module The second panel Atmosphere is used to specify atmospheric model parameters such as aerosol type and horizontal visibility see Fig 25 Tables 5 and 6 list the entries that can be selected under model and aerosol type respectively The main difference between the various atmospheric models is their water vapour and ozone content The various aerosol types differ in their default horizontal visibility in the boundary layer and their optical properties These optical properties have not been listed here they are specified in the MODTRAN documentation see De Haan and Kokke 1996 for references Table 5 Atmospheric models in MODTRAN and the absorber amount of water vapour and ozone model name Water vapour g cm Ozone atm cm tropical atmosphere midlatitude summer midlatitude winter 686 0 3768 subarctic summer 653 0 3448 subarctic winter 327 0 3757 ON 1976 u s standard atmosphere Prototype Toolkit Manual Table 6 Aerosol models in MODTRAN aerosol type default horizontal visibility km no aerosol rural 23 or 5 maritime 23 urban 5 tropospheric Once a specific aerosol type has been chosen the default value for the horizontal visibility appears The user may edit this visibility if desired which will change the aerosol load in the boundary laye
49. ote sensing images may be preliminarily screened using quick looks For satellite remote sensing this phase may play an important role Phase 3 pre processing raw remote sensing and spectroradiometer data The data are corrected for the instrument characteristics yielding physical quantities such as remotely sensed radiance or reflectance Previous remote sensing campaigns have shown this to be a vital phase requiring much expertise for deriving successful end products Too often instruments are not as well calibrated as specified Therefore the intermediate results of the calibration need to be validated as soon as possible After validation if possible the amount of data is reduced by eliminating redundant data and by averaging thus yielding the most representative data Only properly reduced validated and calibrated data form a solid basis for further processing Prototype Toolkit Manual Phase 4 processing calibrated data In phase 4 the calibrated data is processed to obtain input parameters and variables for the determination of the algorithms These are used in phase 5 of the methodology to obtain the algorithms Phase 5 determination of remote sensing of water quality algorithms In this phase the subsurface irradiance reflectances R 0 are calculated and relationships between R 0 values and water quality parameters are established These relationships are used to validate existing water quality algorithms or to
50. quality algorithm based on in situ measurements of R 0 spectra and water quality parameter values The wavelengths corresponding to R1 R2 R3 of this algorithm will generally not coincide with those of a remote sensing instrument In order to apply the algorithm to the remote sensing data accepting small differences in wavelength the user may first copy the algorithm and then edit the wavelengths such that they coincide with those of the remote sensing instrument This modified algorithm can then be applied to the remote sensing data 4 2 3 Ending a session A session can be saved cancelled or closed with the three buttons at the bottom of the WO algorithm window see Fig 18 These buttons apply to the whole window and can therefore be used in every panel With the OK button all changes are saved in the database Until OK is used all results of that session are lost when the window is closed By using the Cancel button all temporary results are deleted and the last saved values are restored Close closes the window without saving results Fig 18 A session is saved cleared and closed by the buttons at the bottom By clicking in the plot option box a scatter plot of the selected data is presented 4 3 The panel Data In the panel Data see Fig 19 sample points can be selected for application or validation of an algorithm and for the estimation of algorithm coefficients The select
51. r with project code 2 has been selected The same selection mechanism may be used to edit and delete a single spectrum Fig 2 Project information window Prototype Toolkit Manual Fig 3 Spectra window For plotting a spectrum and for selecting more than one spectrum another mechanism is used In that case spectra are selected by placing the mouse pointer near the wide black line The mouse pointer then takes the form of a V Clicking the mouse then selects a spectrum and the letters denoting the spectrum change colour from black to red Repeating the selection procedure for a selected spectrum de selects the spectrum In Fig 3 the wide black line that borders the first and second column is clearly visible Near this line the mouse pointer changes shape and then a selection can be made The third type of selection is only relevant for the water quality algorithm tool Fig 4 Water quality algorithm window To determine coefficients for water quality algorithms linear regression is used Selection of data that are to be used for calculating regression coefficients is done by first selecting a line it then 10 Prototype Toolkit Manual turns grey and then clicking the mouse in the centre of the first column labelled 5 see Fig 4 A red V appears in this first column once the data is selected Clicking instead in the left part of the first column the mouse pointer is a Y then turns the letters
52. r of the atmosphere altitude from 0 to 2 km Often the user is only interested in results for clear skies corresponding to the string no clouds or rain However the user may select one of the two other options i a fixed altostratus cloud or ii a cirrus cloud The altostratus cloud can be used to model spectral signatures for a cloudy atmosphere Its main purposes is to simulate effects of clouds but no attempts have been made to give the user control over the properties of the altostratus cloud the altostratus cloud base is at 2 4 km and its top is at 3 0 km Thin cirrus clouds may be present for actual remote sensing images and the user can change the amount of cirrus by entering the thickness of the cirrus cloud The extinction coefficient of the cirrus cloud is 0 14 km at 0 55 jum and the cirrus cloud base is fixed at 10 km altitude 5 1 2 3 The panel Surface Atmospheric radiative transfer edit 362 Fig 26 The panel Surface of the atmospheric and interface correction module The panel surface is used to specify a reflectance spectrum of the surface and parameters relevant for the air water interface see Fig 14 The reflectance spectrum is used only for simulation of the remote 29 Prototype Toolkit Manual sensing signal and is treated as being the reflectance spectrum of a Lambertian surface Note that a Rapp Spectrum has to be selected here not a R 0 spectrum The user can s
53. ra Ry or R 0 pertaining to a pixel dump are known from measurements or can be estimated In those sections atmospheric model parameters are estimated by first performing atmospheric and or interface correction and then comparing the calculated results with estimated or known surface reflection properties Another way to estimate atmospheric model parameters is to compare calculated and measured L spectra If the R is known and stored in the database one may select this spectrum in the panel surface and calculate a high resolution spectrum of the radiance at the sensor An accurate comparison between measured and simulated radiances might be problematic for sensors with wide spectral bands because the calculation of band averages of L spectra is not yet implemented A disadvantage of this approach might be that no adjacency effects can be taken into account MODTRAN is not equipped to this whereas an advantage is that only one instead of three MODTRAN runs are needed to evaluate the atmospheric model parameters 5 2 5 Use of Water Quality Parameters If water quality parameter values of certain location are available one might identify that location in the image and obtain the spectrum L of that location from the image a so called pixel dump The combination of the water quality parameter values and the corresponding spectrum L can than be used to deduce the atmospheric model parameters One might use the following strategy
54. rection gets the instrument code that was associated with the L spectrum used for calculating Rapp The corresponding information on the spectral bands is used when the system performs band averaging Again the results are written to the file bandsim out only d and d are band averaged d and d are independent of the wavelength 3 In the present version of the software the file bandsim out is overwritten each time bandsim exe is executed Therefore the user has to take steps to prevent the loss of atmospheric correction 32 Prototype Toolkit Manual parameters when calculating air water interface correction parameters for example by renaming the file bandsim out 5 1 2 7 The panel Simulation Fig 30 shows the panel Simulation which is used to show graphical results of simulations The upper part pertains to simulation of the remote sensing signal and its two components Lpan and L groun Pressing the view button makes the spectra visible in a separate window The user may select Select spectra for comparison if the results are to be compared with results of previous calculations or with measured spectra stored in the database The lower part pertains to simulation of surface ir radiances and operates in a similar manner The calculated spectra are stored in an ACCESS database and can be exported to an EXCEL worksheet from within ACCESS Alternatively the user may inspect the text file tape
55. s made in the system ini file effective Prototype Toolkit Manual If the toolkit software has trouble finding a file an error message is given and changes in the initialisation files using a simple text editor are required As an example Table 1 shows a listing of the file SL220496 INT In this example the toolkit directory is C TOOLKIT3 and ACCESS can be found in the directory C ACCESS Table 1 Listing of the initialisation file SL220496 INI DATA DataFiles c Ntoolkit3 LocationFile c toolkit3 location mdb InstrumentFile c toolkit3 instrmnt mdb CommonListFile c toolkit3 tk_info mdb Contact File c toolkit3 contact mdb DefaultDatabase c toolkit3 tk_leeg mdb IMODTRAN ModtranFiles c toolkit3 mdtrn exe FORMAT PositionFormat LAT LON TimeFormat UTC TEMPLATE Templatelsc toolkit3 excel tpl ACCESS AccessPathec access AccessLanguage NL Wind fi The Toolkit software requires a specific setting of negative valuta values The setting of valuta values can be changed as follows a Double click on the Configuration Window in the Main Group in the Program Manager b Open the icon International c Select Change for the Valuta Notation The correct setting for negative valuta values is 1 22 F Other settings may give strange results 2 3 Preparing the database For optimal use of the prototype toolkit software the user has to prepare the permanent part of the database by editing i sample points c
56. select the atmospheric correction spectra that will be shown in a separate window Because the units of c gt and cs differ from those of c and c the check boxes are grouped in different subpanels Fig 28 The panel Atmospheric Correction of the atmospheric and interface correction module The lower part of the panel enables the user to select a L in the Toolkit software often denoted as Lrs and a Lr spectrum from the set of imported spectra The software then knows the instrument that was used to measure the spectra and this information is used to retrieve information from the database about the spectral bands of the instrument number of bands position and sensitivity of each band The button Calculate is then used to i write spectra and spectral band sensitivity data to the file bandsim in ii start execution of the program bandsim exe which calculates band averages for the atmospheric correction parameters iii storing band averages in the text file bandsim out see Appendix B and iv applying atmospheric correction to the selected spectra yielding an Rapp spectrum The band averaged correction parameters may be exported to an image processing system 31 Prototype Toolkit Manual For testing and optimisation purposes the calculated Ry spectrum can be viewed by pressing the View button Furthermore one can mark the check box Select spectra for comparison to compare the Rapp
57. seston dry weight zwevend stof gehalte mc wed mg ET EG i 3 electrisch geleidingsvermogen uS 1 Fe EA P totaal ijzer FEO feophytin feofytine vertical atten coefficient le verzwakkings coefficient m 1 Na natrium natrium mg ET NH4 ammonium Img 1 1 El orthofostaat mg 1 1 pH zuurgraad pH J Pigm z algenpigmenten SD Secchi depth doorzicht 5 x silicium Img H1 T temperature temperatuur totaal fosfaat Tmg ET 41 Prototype Toolkit Manual Appendix D Instruments Table D 1 lists the instruments in the Toolkit database see Table Instrument in the database instrmnt mdb in the toolkit directory Table D 1 A list of the instrument in the database Sensitivity curves for the spectral bands have been implemented Sor a few of these instruments denoted with a CAESAR CAESAR inland water mode CASI CASI BC CASI95 z CASI Clear Clear field Field pec FieldSpec 3 LANDSATE TM Thematic Mapper PR650_ Spectrascan 650 PSI Personal spectrometer Il 42 Prototype Toolkit Manual Appendix E Surface Reference Spectra Table E 1 lists the surface reference spectra in the Toolkit database see Table SRSpectrum in the database tk info in the toolkit directory Table E 1 A list of the surface reference spectra in the database Some of these have been implemented the implemented spec
58. t make it possible to use this additional information to estimate atmospheric model parameters for a sample point and thus to calibrate the correction parameters Calculation of coefficients for the water quality algorithms is based on linear regression using different sample points It is assumed that measured values of the water quality parameters are available at these sample points and that the corresponding R 0 spectra are available The R 0 spectra may have been obtained from in situ measurements using a spectroradiometer and a procedure for air water interface correction or from a remote sensing image that has been processed to an R 0 image In the latter case it is referred as an R 0 value pertaining to a pixel dump see Sect 4 3 Prototype Toolkit Manual 2 Quick Start This sections gives information about the installation and use of the Toolkit software If the user is familiar with the Toolkit I and II reports the quick start section provides sufficient information for using the Toolkit software If the reader is not familiar with these reports the user is advised to read the Sections 3 5 and Sect 1 1 of this manual The information in these sections should be sufficient for using the Toolkit Additional background information can be found in the Toolkit I and II reports 2 1 Hard and software requirements Hardware requirements for the prototype Toolkit software are e A PC with a 486 processor or b
59. tra are denoted with a 2 Spectrally grey surface with A 0 10 3 Spectrally grey surface wi Ocean water spectrum Amsterdam Rijnkanaal 8 Soil spectrum 9 Vegetation spectrum _ 10 Sand spectrum e g dunes Prototype Toolkit Manual Appendix F Sample Point Codes Table F 1 lists sample point codes stored in the database The table contains a part of the table WaterbodySP in the database location mdb Braassemermeer uitmonding noord Braassemermeer zuidwestpunt Braassemermeer midden Braassemermeer haven DE DEELEN 4 petgat DE DEELEN 6 petgat deelgebied 2 DE DEELEN 11 deelgebied 1 DE DEELEN 12 petgat DE DEELEN 13 petgat DE DEELEN 14 petgat Linde bij Linthorst Homansluis Oostelijke Belterwijde nabij landtong Belterwijde West bij springschans jBovenwijde bij palvioen Smits zuidingang Beulakerwijde achter eilandjes Beulakkerwijde bij ton 9 Duinigermeer Midden Giethoornsemeer Midd Hoofdpoldersloot Wetering Oost Petgat Meentegat Petgat Lokkenpolder Petgat Riethove jRonduite Beulakkerwijde Belterwijde Schutsloterwijde Midden Venematen West de Leijen de LEIJEN midden de LEIJEN ZW de LEIJEN ZO de LEIJEN NO de LEIJEN NW Oost Loenderveen zuid West Loenderveen standaard meetpunt Sample point for simulation spectra VEENSCHEIDING bij overgang in Nannewiid oost NANNEWID west dagrecr NANNEWIID Oudehaske ZANDMEER Oude Venen midden OUDE VENEN
60. uction and interpretation of Prototype Toolkit Manual RS images from which a suitable set can be chosen depending on the end user requirements instruments used the weather conditions and the GIS based knowledge of water targets The operational 1998 version Toolkit should make it possible to calculate pigment concentrations suspended matter transparency and vertical attenuation coefficients e g which can be easily adapted to other remote sensing instruments e g both SeaWiFS MERIS DAIS ROSIS CAESAR and CASI and to varying irradiance and viewing geometry atmospheric and water surface situations To achieve this aim a comprehensive Spectral Library is required which contains all relevant data from in remote sensing in situ and laboratory measurements of water quality and its associated optical parameters In order to produce water quality maps with remote sensing on an operational basis remote sensing consultants need a standard methodology for remote sensing of water quality Such a methodology should contain correction calibration methods measurement procedures analysis tools and algorithms It should be flexible since the selection or determination of algorithms depends on many factors which differ for each remote sensing project such as available time the required accuracy sensor weather conditions field measurements and additional information available for a given target 1 1 1 The IVM methodology This secti

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