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OFGT User Manual

1. 3 The script oft crossvalidate prints the average RMSE and bias on screen using the input data file sample landuse txt Lets take a closer look at the input file space or tab separate head sample_landuse txt User Manual 114 10557 00 772650 00 2404770 00 5 00 53 00 26 00 28 00 54 00 81 00 131 00 39 00 94788 00 773490 00 2431680 00 1 00 51 00 24 00 25 00 45 00 65 00 127 00 33 00 201536 00 774750 00 2439390 00 1 00 54 00 25 00 27 00 50 00 71 00 130 00 35 00 88531 00 771450 00 2431110 00 1 00 47 00 21 00 18 00 37 00 48 00 126 00 21 00 123374 00 774150 00 2433990 00 1 00 54 00 24 00 30 00 35 00 75 00 132 00 42 00 97345 00 776220 00 2431950 00 1 00 52 00 23 00 24 00 42 00 60 00 131 00 30 00 199041 00 773190 00 2439120 00 1 00 51 00 23 00 23 00 52 00 58 00 130 00 28 00 144276 00 775860 00 2435400 00 1 00 49 00 22 00 21 00 45 00 59 00 125 00 30 00 180961 00 772680 00 2437890 00 1 00 49 00 21 00 21 00 36 00 61 00 126 00 28 00 185386 00 772410 00 2438190 00 1 00 49 00 21 00 18 00 43 00 51 00 126 00 22 00 Explanation of the columns pixel_id x y class band1 band2 band3 band4 band5 band6 band7 4 Lets run oft crossvalidate defining our inputfile with i in front number of neighbours k 10 v defines the column of the variable we want use only to exemplify the tool we use column 1 containing the IDs as our input data has no additional column with values bands defines the num
2. Figure 18 Original input image forestc tif Figure 19 Reclassified output raster reclassforestc img User Manual 96 2 Second example for oft reclass Lets run oft reclass again with a different input image Input landsat_t1_min50 tif input_reclass txt input_reclass txt Output reclass_min50 img oft reclass oi reclass_min50 img input_reclass txtlandsat_tl_min50 tif Again the tool will ask you for further information Input reclass file name input_reclass txt Nbr of out bands per input channel 3 Col of input value 1 Col of output value 1 Col of output value 2 Col of output value 3 NODATA value 0 AUN Open QGIS and load your result image reclass min50 img and zoom into the top left corner You can see that the original classes 1 6 and 99 of landsat_t1_min50 tif were reclassified the way we defined it in the lookup table input_reclass txt User Manual 97 Figure 20 Zoom into the top left corner of our final result reclass_min50 img User Manual 98 7 32 oft shrink NAME oft shrink to be combined with oft trim 71 33 oft stack NAME oft stack Create a muti band image stack OFGT VERSION 1 25 4 SYNOPSIS oft stack oft stack lt o outputfile gt lt inputfiles gt oft stack ot Byte Int16 Ulnt16 Ulnt32 Int32 Float32 Float64 CInt16 CInt32 CFloat32 CFloat64 um lt maskfile gt lt o outputfile gt lt inputfiles gt o outputfile The name of th
3. 0 13 feature s selected id v colour newcol name 0 1 red 11 1 1 2 green 22 2 2 3 blue 33 3 3 4 orange 44 4 4 5 pink 55 5 5 6 red 66 6 6 7 blue 9999 7 7 8 orange 88 8 8 9 green 99 9 9 10 orange 1000 10 10 11 red 1111 11 11 12 red 1222 12 12 13 orange 1333 13 Figure 4 Left Attribute table of landuse shp Right Zoom of output raster forestc tif in QGIS using the colourmap Pseudocolour User Manual 37 Forestc tif is the base raster to create some masks files by extracting those pixels that contain values which were previously in the shapefile and then burned into the raster oft calc forestc tif maskl tif 1 1 55 0 1 f the pixel values is 55 in forestc tif then give it in maskl tif the value 1 otherwise 0 oft calc forestc tif mask2 tif il Al ML 0 2 Y f the pixel values is 11 in forestc tif then give it in mask2 tif the value 2 otherwise 0 oft calc forestc tif mask3 tif 1 el so 0 8 f f the pixel values is 33 in forestc tif then give it in mask3 tif the value 3 otherwise 0 oft calc forestc tif mask4 tif it 1 44 0 4 f the pixel values is 44 in forestc tif then give it in mask4 tif the value 4 otherwise 0 oft calc forestc tif mask5 tif il a A2 015 a f the pixel values is 22 in forestc tif then give it in mask5 tif the value 5 otherwise 0 Again check in QGIS if the masks contain the extracted value for the same l
4. Open your working directory using cd home The script oft sigshp bash is able to create a signature file for both data types numerical and factorial depending on the stored data in your shapefile In the next steps we will lead you through an example exercises for each data type id v colour newcol o red 11 1 2 green 22 2 3 blue 33 3 4 orange 44 4 5 pink 55 5 6 red 66 6 7 blue 9999 7 8 orange 88 8 9 green 99 9 10 orange 1000 Figure 11 Attribute table of polyN20 shp User Manual 66 1 oft sigshp bash creating signature file with numerical values First we run in the command line oft sigshp bash with the input rasterlandsat_t1 tif and your input shapefile landuse shp id stands for the shapefile_id_fieldname newcol refers to the shapefile cover class fieldname If you look at the attribute table of your anduse shp you will see that under newco numerical data is stored Output sig_newcol txt Note the extension shp of your shapefile is not included in the command line only the basename Run in terminal oft sigshp bash landsat t1 tif landuse id newcol sig_newcol txt EPSG 32620 EPSG 32620 Lets take a look at the first lines of our output sig_newcol txt head sig_newcol txt 1 11 52 097317 23 696463 24 919711 45 321753 65 427785 129 033459 32 060358 2 22 54 157159 25 348832 28 176561 48 805278 72 468158 129 166550 34 397944 4 44 53 864419 25 231642 27 932243 51 411361 71 9
5. lt nodata gt EPSG code DESCRIPTION oft combine masks bash is a UNIX bash script that allows the user to use both mask images and mask shapefiles as input and the script combines them into one mask file The first inputfile is the base and it must be an image not shapefile The following input files will be written on only if there is nodata user defined value The extent is defined by the first input image If the projection is not given by the user all files are assumed to be in same projection Concerning the shapefiles the last field is assumed to be the one containing the mask values At least 2 files and nodata value are needed OPTION The projection can be defined by the user Parameters EPSG code User Manual 36 EXAMPLE For this exercise following tools are used oft combine masks bash oft calc gdal_rasterize Open your working directory using cd home STEP 1 CREATE MASKS To run oft combine masks bash we need to create some mask files To do so we burn the attribute values of the column mask from the shapefile landuse shp into the raster forestc tif gdal_rasterize b 1 a mask I landuse landuse shp forestc tif forest tif Verify in QGIS if your pixel values of forestc tif match the polygon values of landuse shp Note if the raster output is black click on it s Properties gt Style gt Colour Map and chose Pseudo Colour Attribute table polyN20
6. 2454134 000000 50 000000 3374 000000 4 000000 730785 000000 2453134 000000 50 000000 3341 000000 5 000000 730785 000000 2452134 000000 50 000000 3308 000000 6 000000 730785 000000 2451134 000000 50 000000 3274 000000 120 User Manua 7 41 oft his NAME oft his computes image histogram by segments OFGT VERSION 1 25 4 SYNOPSIS oft his oft his i lt infile gt o lt outfile gt oft his i lt infile gt o lt outfile gt um maskfile hr compact maxval val OPTIONS i specify input image file specify output text file 0 um specify mask file hr use human readable output format compact use compact output format maxval give maximum input value h print out more help DESCRIPTION oft his extracts histograms for the different bands of an input image to an output text file You need to give at least the input image file option and the output file o Typically you also give a mask file um Each mask value gets own histogram except 0 which is treated as nodata If no mask file is given a common histogram is computed for whole image Maximum input value needs to be given to allocate enough memory for the histogram table If the maxval parameter is not given in the command line it will be asked For example for a 8 Bit Landsat image the maximum value parameter would be 255 The output format is mask value frequency of
7. OFGT VERSION 1 25 4 SYNOPSIS oft segstat oft segstat lt maskfile gt lt input gt lt output gt oft segstat std shape lt maskfile gt lt input gt lt output gt DESCRIPTION oft segstat Extracts segment level shape size bounding box edge pixels and spectral averages and standard deviations to a text file Mask file is an image consisting of pixels with integer values Pixels having value 0 are not processed For all other mask values the statistics are reported separately The output The basic usage outputs the following space separated columns 1 Segment ID 2 Size 3 3 n Segment averages pixel values for all n input image bands OPTIONS std adds standard deviations for all input bands in the end of each record shape changes the output format to follwoing 1 Segment ID 2 Size 3 of neighbours 4 xmin User Manual 129 5 xmax 6 ymin 7 ymax 8 edge pixels 9 9 n Segment averages pixel values for all n input image bands OTHERS This script can also be used after oft seg EXERCISE For this exercise following tools are used oft segstat For this exer cise we use the Landsat imagery andsat_t1 tif landuse shp Further you need to run oft seg in a first step to calculated the segmentation file landsat_t1 tif 2 Open your working directory using cd home 1 oft segstat Now we run oft segstat with Input landsat_t1 tif landsat_t1_min50 tif
8. Output segstats_std txt oft segstat std landsat_tl_min50 tif landsat_t1 tif segstats_std txt Again lets take a look at the first 10 lines of our result segstats std txt head segstats_std txt 49 60 49 183333 20 366667 18 883333 36 800000 47 866667 126 500000 20 700000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 89 56 47 714286 20 053571 18 428571 37 125000 49 035714 125 571429 20 660714 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 26 132 49 310606 20 295455 18 651515 35 840909 46 863636 126 833333 20 257576 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 220 54 51 203704 22 629630 23 666667 38 592593 58 777778 131 370370 28 685185 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 User Manual 131 231 132 56 416667 27 325758 34 606061 43 409091 82 636364 134 871212 45 454545 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 236 55 46 200000 19 272727 16 290909 41 963636 39 927273 124 654545 15 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 7 53 48 886792 20 056604 18 339623 37 207547 45 698113 125 698113 19 396226 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 52 105 49 580952 20 866667 19 666667 38 161905 53 990476 126 361905 22 847619 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 114 51 46 960784 19 470588 16 235294 41 294118 37 725490 124 764706 15 039216 0 000000
9. User Manual 141 7 46 oft kmeans NAME oft kmeans for kmeans clustering OFGT VERSION 1 25 4 SYNOPSIS oft kmeans oft kmeans i lt infile gt o lt outfile gt oft kmeans i lt infile gt o lt outfile gt OPTIONS DESCRIPTION oft kmeans carries out unsupervised classification with k means al gorithm By default the program asks user to input two parameters 1 input text file 2 number of classes The input text file is a collection of signatures from the input file It contains at minimum the greyvalues of each band It can be done with oft gengrid bash and oft extr The program uses it to establish the cluster centres and pro ceeds by assigning each pixel the Class ID of the closest cluster centre The proximity of the cluster centres is computed using Euclidean distance in the spectral feature space If the auto option is used the program divides the data automati cally and the number of clusters is not requested If the aw option is used the programs asks user to provide weight for each of the input bands OPTIONS ot Byte Int16 UInt16 UInt32 Int32 Float32 Float64 um specify mask band User Manual 142 auto automated division of data aw ask weights for input bands h print out more help NOTES For the benefit of users running scripts using the older version based on order of files instead of option the program can still be used that way EXAMPLE For t
10. 00 2447134 00 52 00 23 00 21 00 53 00 61 00 127 00 27 00 Explanation of values for each column e Coll pixel ID e Col2 x coordinates Col3 y coordinates Col4 pixel ID Col5 x coordinates Col6 y coordinates Col7 Col13 center pixel value for bands 1 7 User Manual 153 7 49 oft normalize bash NAME oft normalize bash Script for preparing a training data text file for oft nn analysis OFGT VERSION 1 25 4 SYNOPSIS oft normalize bash oft normalize bash lt i image gt oft normalize bash lt i image gt t training data f 1 2 m mask OPTIONS i image give the Landsat image with 6 or 7 bands to be normalized t training data give a text file containing ground truth and image bands in last columns f 1 2 normalization will be based on the distribution present in the image 1 or the training data file 2 m mask give a mask file showing areas to be processed with 1 and others with 0 DESCRIPTION Image grey values in both files are converted to mean 0 and std 1 based on the selected source of distribution image or training data file Procedure for converting each grey value on each band in the image and or training data file is value average std It is possible to e Normalize just the image based on it s grey value distribution on each band e Normalize also the training data text file using the same distri bution or User Manual 154 e Normalize both files u
11. 00 53 00 85 00 00 730785 00 34 00 45 00 00 730785 00 35 00 47 00 10 00 730785 00 35 00 45 00 2456134 00 128 00 29 00 2451134 00 124 00 20 00 2446134 00 127 00 26 00 2441134 00 124 00 19 00 2436134 00 125 00 19 00 2431134 00 128 00 23 00 2426134 00 136 00 45 00 2421134 00 126 00 19 00 2416134 00 125 00 20 00 2411134 00 125 00 18 00 50 50 50 50 50 50 50 50 50 50 3441 3274 3108 2941 2774 2608 2441 2274 2108 1941 bye 47 52 49 47 51 62 48 49 49 24 19 23 20 20 21 29 21 20 20 00 00 00 00 00 00 00 00 00 00 24 18 227 17 18 20 38 18 19 18 2 Unsupervised classification oft kmeans Now we run oft kmeans with Input andsat_tl tif and Output my_kmeans tif oft kmeans o my_kmeans tif i landsat_tl tif The program will ask you for Input signature Number of clusters file name 25 choose 25 clusters my extr txt For this example we Load your result my_kmeans tif in QGIS User Manual ts l YA mai e al ES Figure 25 shows the classified image my_kmeans tif with pixel values between 1 and 25 User Manual 145 7 47 oft nn To be tested NAME oft nn is a nearest neighbour
12. 14 oft cuttile pl IA SS ete Sok Aes bee 27k 6 be BY Oho E GPS OTTER Se a ada aa ed A de a 7 16 oft gengrid bash 2 2442 2 2 don a e de 7 17 oft getcorners bash 2 2 a User Manual 7 18 7 19 7 20 7 21 7 22 oft polygonize bash ira a a a oft sample within polys bash 0 0 0 0 oft shptif bash A A aaa de A A IR eee eae Points losdivares py wc A ot Belin 6 eS Image Manipulation 1 23 7 24 7 25 7 26 1 27 28 7 29 7 30 7 31 7 32 7 33 7 34 7 35 multifillerThermal bash 2 0 0 020202020222 2 220008 Ofcar eA O a Bag ot A Age Ae et E oft chdet bash 02 2 2002 02 00 000 0008 OSGI Ple fad Oe 8 aom Bnd dude rad B Bod Sach She of Bate oft combine images bash a a a Qbear ssn Tie e E E a te BSE BEE OftNAVEi bash z cra Bod Sela hs Shh ee al Sh sl EA oft prepare images for gapfill bash OfereclaSS eri rre A AA A Se a oft shrink 2 a A O Be oe ae ang Se ae eee eggs ae ar ee A EA OEI os e te ee RO A a a oft trim maks bash Statistics 7 36 1 37 7 38 7 39 7 40 7 41 7 42 7 43 7 44 Oftasestat aWwk e A A AS A BAe be ee ee ke oft countpix pl a s 24 Sea ous oe Sf es de ok al Sak amp oft crossvalidate 0 00000000002000008 A ON ee PP a a Se a a a NE ONIS aaa fas Se A et teed E ee otek OM a ds do A tnd Acie tet siete Peat te wh OftsegStat woes A ho ee So ee ee ais ke Se i Ost pt ch crete
13. 2 Now we run oft avg with input images landsat_t1 tif output results oftavg tif mask images segments tif The output text file will be named as the output image plus in this case oftavg tif txt txt oft avg i images landsat_t1 tif o results oftavg tif um images segments tif 3 Print the first 10 lines of the output text file in terminal head results oftavg tif txt 1 135 49 051852 20 081481 18 370370 36 785185 46 674074 126 059259 20 192593 2 54 49 351852 20 370370 18 407407 37 500000 46 555556 125 925926 19 870370 3 716 48 578947 19 828947 17 710526 36 657895 43 881579 125 907895 18 881579 4 194 49 005155 20 077320 18 268041 37 530928 46 000000 125 670103 19 721649 5 221 49 090498 20 176471 18 574661 37 542986 47 565611 125 728507 20 339367 6 82 48 878049 20 304878 18 695122 37 243902 48 097561 125 597561 20 780488 7 53 48 886792 20 056604 18 339623 37 207547 45 698113 125 698113 19 396226 8 120 48 991667 20 216667 18 583333 36 908333 47 200000 126 041667 20 283333 9 154 48 980519 19 993506 18 389610 32 474026 45 000000 125 987013 20 337662 10 150 49 540000 20 220000 18 853333 32 260000 47 233333 125 973333 21 433333 User Manual 109 Explanation of values for each column Coll ID value for zone segment Col2 Number of pixels Col3 col9 Average value of band1 band2 band7 4 Open the output file results oftavg tif in QGIS Use Identify Features that can be c
14. 255 Be 4b 259 255 209 22 1227011227255 11 255 0 0 255 4 122 122 122 255 250 2s 0 2s 2 200 200 200 255 6 0 255 0 255 Important Make sure that the text file does not contain any empty lines Run oft addpct py oft addpct py images forestc tif results forestcolor tif The command will ask you about the colortable file Give LUT file name Enter the path to your color table file and hit enter txt coltable txt You can visualize the result in QGIS qgis results forestcolor tif User Manual 24 Figure 2 Example of using oft addpct py to define the colour table User Manual 25 7 oft admin mask bash NAME oft admin mask bash this script prepares a mask of administrative areas within a satellite image OFGT VERSION 1 25 4 SYNOPSIS oft admin mask bash oft admin mask bas lt mask for Landsat image gt lt administrative area image gt ID of wanted administrative area DESCRIPTION If no ID is given the script just clips and re projects if needed the admin image to match the Landsat image mask If an ID is given the admin area with this ID is added to the base mask and other areas are set to 0 The input administrative image does not need to be of the same size and projection script utilises oft clip pl for clipping and re projecting EXERCISE For this exercise following tools are used oft admin mask bash oft shptif bash Open your w
15. 500 In case of norm the normalization parameters are computed from the field data NOTE you may also normalize your features image and training data BEFORE using oft nn Just be sure that the values come from the same distribution In case of or the output text file contains the target variable and collected weight for each training data observation User Manual 147 If the u option is given only observations from the same land use category class will be used for estimation EXERCISE For this exercise following tools are used oft nn oft sigshp bash 1 You will need for this exercise the following data textitlandsat_t1 tif and textitlanduse shp which was digitized manually in QGIS 2 Create the signature file using oft sigshp bash cd home OFGT Data oft sigshp bash images landsat_tl tif shapefiles landuse id newcol txt sig_landuse txt 3 Take a look at the input signature file sig_ anduse txt more txt sig_landuse txt 14 4 54 872263 26 561314 28 113869 58 320438 75 259854 129 021898 33 874453 15 4 58 635842 29 131097 35 067535 50 379166 86 387111 131 054293 47 649746 16 4 58 217101 29 102204 34 695057 54 351035 82 787575 130 169673 43 795925 17 1 54 840000 25 463590 29 768205 43 720000 80 614359 132 413333 42 431795 18 2 54 172608 25 085366 28 419325 48 404315 74 633208 131 336773 37 128518 19 3 55 198990 26 094949 30 674747 49 970707 76 598990 131 734343 36 209091 20 2 57 269
16. Manual 30 For this exercise following tools are used oft classvalues plot bash Input data deriving from exercise oft classvalues plot bash Change your working directory to the one of the previous exercise oft classvalues plot bash cd home Use oft classvalues compare to create a comparison plot of band2 and band3 Output to be found in folder plots_ LT52_CUBO0 tif_bands_3_4 cre ated after running oft classvalues plot bash Output Comparison1_3 png oft classvalues compare bash 1 3 Class comparison plots 100 Class1 90 Class3 x 80 70 60 Bandb 50 40 30 20 10 User Manual 31 Now compare band1 band2 and band3 Output Comparison1_2_3 png oft classvalues compare bash 1 2 3 Class comparison plots 100 A Class1 Class2 x te Class3 80 70 60 Band b 50 40 30 20 10 10 20 30 40 50 60 70 80 90 100 110 Band a User Manual 32 7 10 oft classvalues plot bash To be tested NAME oft classvalues plot bash creates scatterplots of pixels within train ing classes given in a shapefile OFGT VERSION 1 25 4 SYNOPSIS oft classvalues plot bash oft classvalues plot bash lt input image gt lt shapefile_basename gt lt shapefile_class_fieldname gt lt image band for x axis gt lt image band for y axis gt DESCRIPTION oft classvalues plot bash This script creates scatterplots of image grey values in different classes o
17. OFwiki index php Open_Foris_ Geospatial_Toolkit 1 2 What is OFGT OFGT Open Foris Geospatial Toolkit is a a collection of prototype command line utilities for processing of geographical data The tools can be divided into stand alone programs and scripts and they have been tested mainly in Ubuntu Linux environment although can be used with other linux distros Mac OS and MS Windows Cywgin as well Most of the stand alone programs use GDAL libraries and many of the scripts rely heavily on GDAL command line utilities The OFGT project started under the Open Foris Initiative to develop share and support software tools and methods for multi purpose forest assessment monitoring and reporting The Initiative develops and supports innovative easy to use tools needed to produce reliable timely information on the state of forest resources and their uses The command line tools aim to simplify the complex process of transforming raw satellite imagery for automatic image processing to produce valuable information These tools contain radiometric harmonisation image segmentation and image arithmetic as well as image statistics feature extraction and other image processing analysis Overview of OFGT versions currently available e OFGT 1 25 4 continuously updated e OFGT 1 0 User Manual 5 1 3 The great potential of OFGT The toolkit comes to its own when dealing with large data sets e First of all the processing itself takes a fract
18. OGC WKT projection definition files for user defined UTM S or N zones in WGS84 from http spatialreference org ref epsg Creates directory ogcwkt if does not exist otherwise uses the existing Copies the downloaded files there and can be viewed with a text editor EXAMPLE For this exercise following tools are used oft getproj bash 1 Run the oft getproj bash for the UTM zone 20N oft getproj bash 20N 2 Fetching the projection definition for several zones oft getproj bash 21N 22N 25N 31S 3 Change your working directory to cd ogcwkt User Manual 167 4 Here you can find the downloaded projection definition file for the UTM zone 20N WGS84_UTM_20N ogcwkt Open it with any text editor program such as gedit PROJCS WGS 84 UTM zone 20N GEOGCS WGS_84 DATUM WGS_1984 SPHEROID WGS 84 6378137 298 257223563 AUTHORITY EPSG 7030 AUTHORITY EPSG 6326 PRIMEM Greenwich 0 AUTHORITY EPSG 8901 UNIT degree 0 01745329251994328 AUTHORITY EPSG 9122 AUTHORITY EPSG 4326 UNIT metre 1 AUTHORITY EPSG 9001 PROJECTION Transverse_Mercator PARAMETER latitude_of_origin 0 PARAMETER central_meridian 63 PARAMETER scale_factor 0 9996 PARAMETER false_easting 500000 PARAMETER false_northing 0 A
19. Open your working directory using cd home OFGT data Run the command line for generating the grid of 1000 x 1000 m distance between the points in X and Y directions on the input User Manual 54 image landsat_t1 tif with an output text file consisting of three columns for lt ID gt lt X gt lt Y gt oft gengrid bash images landsat_t1 tif 1000 1000 results grid_points txt Look at the first ten lines of your result head results grid_points txt 1 730785 2456134 2 730785 2455134 3 730785 2454134 4 730785 2453134 5 730785 2452134 6 730785 2451134 7 730785 2450134 8 730785 2449134 9 730785 2448134 10 730785 2447134 Load the data in QGIS using Add Delimited Text Layer and see if it overlays on your Landsat image Figure 9 Zoom of the result overlayed on the original Landsat image in QGIS User Manual 55 7 17 oft getcorners bash NAME oft getcorners bash gets the coordinates of corners of a raster image or OGR vector layer OFGT VERSION 1 25 4 SYNOPSIS oft getcorners bash oft getcorners bash lt inputfile gt ul Ir min_max OPTION Where lt inputfile gt is a GDAL raster layer or OGR vector layer ul_ lr ulx uly Irx Iry default min_max xmin ymin xmax ymax ulx Iry Irx uly DESCRIPTION oft getcorners bash outputs the corner coordinates for a GDAL raster layer or OGR vector layer The user can choose the order of
20. QGIS and you will see that stack tif has 13 bands landsat_t1 tif contains 7 bands and landsat_t2 tif 6 bands Or print the raster information on your screen by typing in your terminal gdalinfo stack tif User Manual 100 7 34 oft trim NAME oft trim erosion filter producing binary output OFGT VERSION 1 25 4 SYNOPSIS oft trim oft trim um lt maskfile gt lt inputfile gt lt outfile gt oft trim ws WindowSize origval um lt maskfile gt lt inputfile gt lt outfile gt DESCRIPTION oft trim analyses the content of the spatial neighbourhood of each pixel If all the pixels within the window are less or equal to zero output is zero Else output is one OPTIONS Parameter um maskfile ws window size origval original value EXERCISE For this exercise following tools are used oft trim 1 Open your working directory using cd home 2 Lets run oft trim with the input file landsat_t1 tif with the option ws set to 3 to create the output file trim tif oft trim ws 3 landsat_tl tif trim tif User Manual 101 3 Verify in QGIS that all the values of your output image are all trimmed to 1 User Manual 102 7 35 oft trim maks bash NAME oft trim maks bash This script makes a 0 1 mask of a 6 or 7 band Landsat image OFGT VERSION 1 25 4 SYNOPSIS oft trim maks bash oft trim maks bash lt image gt DESCRIPTION oft trim maks bash detects the margi
21. Ubuntu Debian etc The installer has been tested with various Ubuntu Linux versions and it should work with other Debian based distros as well 1 First make sure that you have installed all the necessary gdal and gsl libraries and tools If you do not have them download and install them by using following commands sudo apt get install gcc sudo apt get install g sudo apt get install gdal bin sudo apt get install libgdall dev sudo apt get install libgsl0 dev sudo apt get install libgslOldbl sudo apt get install python gdal sudo apt get install python gdal sudo apt get install perl sudo apt get install python scipy sudo apt get install python tk 2 Then download the OpenForisToolkit run installer wget http foris fao org static geospatialtoolkit releases OpenForisToolkit run sudo chmod u x OpenForisToolkit run sudo OpenForisToolkit run 3 To accept the license terms type 1 and hit enter 3 2 Linux rpm based systems PCLinuxOS RedHat SuSE etc Open Foris Toolkit is tested on and we recommend PCLinuxOS Always ensure that your system is fully updated Open Synaptic click Reload to get a current file list click Mark All Upgrades click Apply User Manual 7 If you do not have gdal and gsl libraries and tools installed install them via Synaptic e Open Synaptic click Reload click Search then search for the following packages and and mark them for installa
22. a training data text file for oft nn analysis OFGT VERSION 1 25 4 SYNOPSIS oft nn training data bash oft nn training data bash lt i image tif gt lt f field_data txt gt lt x col gt lt y col gt oft nn training data bash lt i image tif gt lt f field_data txt gt lt x col gt lt y col gt m mask tif d dem I lu give the landsat image where grey values are to be picked for the field plot locations f give the field data text file x give the column where x coordinate resides in the text file y give the column where y coordinate resides in the text file OPTIONS m give a mask with values 0 and 1 where O tells that this location is not to be picked if a field plot falls here d give a digital elevation model file from which the elevations at field plot locations are to be added to the training data lu give a land use land cover etc image file from which this information is to be added to the training data DESCRIPTION Picks field data in a text file based on the extent of given image Image may contain 6 or 7 bands Extracts image values based on field data locations User Manual 151 If a mask is given pixels with mask value 0 are dropped At this point the materials must to be in the same projection The text file is preserved as such Image grey values are added to the end of each row If lu and or dem are given they appear between the original field data and grey valu
23. an image keeps the original values of the image but ensures that classes are shown in pre defined colors no matter which application is used to open the image After defining the first line the command will ask for the text file containing the color table Give LUT file name lt colortable gt Where lt inputfile gt is an image file lt outputfile gt is an image file if it is the same as lt inputfile gt lt inputfile gt will be overwritten lt colortable gt is a text file with 4 or 5 columns containing the color table in the following format e ist column class value e 2nd 4th column RGB values e optional 5th column for alpha if not set it is assumed to be 255 e Important The lt colortable gt must NOT contain any empty lines User Manual 23 e see Wikipedia for more information on RGBA color space The lt colortable gt could look like this t 0S D I 206 2 254 0 0 255 30 0 254 255 4 0 255 0 255 EXAMPLE For this exercise following tools are used oft addpct py Create the colortable for the file images forestc tif If you do not know which classes are present in images forestc tif you could use oft stat with images forestc tif both as input and mask file The first column of the mask file shows all present classes besides 0 Create a text file called txt coltable txt with the first column indicating all possible classes It could look like this 10000 44 122 122 0 255 SS Os Bil ak
24. if mm is chosen maximum if mm is chosen average standard deviation If the input image has several bands the parameters are given for all bands User Manual 137 CLASSIFICATION 7 45 oft cluster bash NAME oft cluster bash clusters raster images OFGT VERSION 1 25 4 SYNOPSIS oft cluster bash oft cluster bash lt input img gt lt output img gt lt nbr_clusters gt lt sampling_density gt oft cluster bash lt input img gt lt output img gt lt nbr_clusters gt lt sampling_density gt mask DESCRIPTION oft cluster bash clusters input image into a given number of clusters The clustering process is as follows 1 generate a systematic sample using the given sample density and covering the area of input img For more details please have a look at oft gengrid bash 2 extract spectral or other information for every point of the grid using oft extr 3 cluster the grid points into given number of clusters using k means algorithm oft kmeans 4 classify each image pixel in one of the generated clusters using NN classification with Euclidean distance in the feature space The mask values are 0 do not classify User Manual 138 1 classify OPTION Parameters mask use maskfile and process only areas having mask value gt 0 NOTES If you re using LEDAPS input you can generate the mask using trim_ledaps bash EXAMPLE cluster bash LT51650672009351JSA00_stack img 50classesl0percent img 50
25. image2 img gt lt mask1l img gt lt mask2 img gt lt grid_spacing gt EPSG img1 Give the spacing in metres 1000 1 km Give the last parameter in format EPSG 32637 replace number with your own this is for UTM 37 N DESCRIPTION Meant for evaluation of the brdf correction of 2 images but other imagery can be compared as well The second image is projected to the same projection as the first if the projections differ In that case user gives the projection of first image ad EPGS code And both images need to have a projection defined although it differs Similar number of bands must exist Masks must be given for both images to exclude cloud shadow areas They must be of same size and in same projection as their corre sponding images Only areas where mask has value 2 are used in comparison you may give a mask full of 2 if needed User gives the spacing of the sampling points as well User Manual 41 EXAMPLE For this exercise following tools are used oft compare overlap bash oft calc gdal_translate oft trim mask bash Open your working directory using cd home Convertlandsat_t1 tif into 6 bands as both need to have same nr of bands Output landsat_t1_6bands tif gdal_translate landsat_tl tif landsat_tl_6bands tif b 1 b 2 b 3 b 4 b 5 b 6 Create mask for landsat_t1_6bands tif automatic output andsat_t1_6bands_mask tif oft trim mask bash landsat
26. landuse shp is 9999 This is due to the fact that there was no value 7 in the first column of the lookup table In that case the corresponding value is not present in the lookuptable therefore the newcol value for that record becomes 9999 User Manual 21 id v colour newcol o Area n 1 2 green 22 2 3 blue 33 3 4 orange aa 4 5 pink 55 5 6 red 66 6 7 blue 9999 7 8 orange 88 8 9 green 99 9 10 orange 1000 Figure 1 Attribute table of landuse shp containing the new column called newcol with values HOW TO CHANGE THE DATA TYPE OF THE VALUES IN THE ATTRIBUTE TABLE IN QGIS Add plugin Table Manager 1 Click on the top bar Plugins gt click Fetch Python Plugins 2 Type in the filter Manager gt then you should find Table Manager Manages the attribute table structure 3 Install it Close and re open QGIS 4 On top bar click Plugin gt click Manage Plugins gt tick box for Table Manager 5 On top bar click Plugin gt you should now see Table some where under Manage Plugins click it and the option Table Manager can be chosen 6 From there you can edit your attribute table add a new colum and choose the data type User Manual 22 7 6 oft addpct py NAME oft addpct py adds pseudo color table to an image OFGT VERSION 1 25 4 SYNOPSIS oft addpct py oft addpct py lt inputfile gt lt outputfile gt DESCRIPTION oft addpct py adds a pseudo color table to
27. mask value and number of band User Manual 121 The rest of the columns values are frequencies for each image pixel value NOTES For the benefit of users running scripts using the older version based on order of datafiles instead of options o and um the program can still be used that way Example with typical parameter setting oft his i input img o histogram txt um mask img hr maxva 255 The output file will contain nbr_bands lines for every input mask value The output format is mask value frequency of mask value and number of band the rest of the columns values are frequencies for each image pixel values For example in the following output 1 657846 1000000000000100000000000000 000000000000000000015 205 2166 10162 29145 70813 136848 145398 117541 82955 40937 14060 4255 1618 707 345 208 140 103 83 48 42 15 17 13632031000000 000000000000000000000000000000 0000000000000000000000000000000 000000000000000000000000000000 0000000000000000000000000000000 000000000000000000000000000000 00000000000000000000 1 1 Mask value 2 657846 Frequency of mask value 1 3 1 Number of band 4 0 frequency of value 0 in input image 5 0 frequency of value 1 in input image 6 0 frequency of value 2 in input image User Manual 122 7 0 frequency of value 3 in input image 8 Os 10 An alternative output format is provided by the compact option 1 657846 1 12 1 46 1 47 5 48 205 4
28. onde ee eh tas ea dae oe dead Classification 7 45 7 46 7 47 7 48 7 49 7 50 7 51 oft cluster bash tdi el a A eae as eee OL KMCANS a a Ged Beto Ge eee ee ee eS oe oft nn To be tested o oo a a da e oft nn training data bash o aa a e oft normalize bash e cig a a Cha eee oe oft prepare image for nn bash ooa oa oft unique mask for nn bash ooa a User Manual 101 103 105 106 108 111 113 117 121 127 129 134 137 138 142 146 151 154 156 158 Segmentation 160 az OEM ib ek GE eh Ge SE EME SS BS 161 LOS PONES e slds Sak ete a rita ds de 163 Projection 166 7 54 oft getproj bash cocina ra e eS 167 User Manual 4 1 Introduction 1 1 About this manual The user manual is developed to help getting into spatial analysis using the Open Foris Geopsatial Toolkit It gives basic explanations of how OFGT functions It is not attempted to explain the theoretical background on how to do geo spatial analysis using remote sensing or GIS but rather will guide you through hands on examples for each tool next to some general areas such as the installation Further the manual will link to relevant man pages and other documentation In addition the user manual is written in a way that it can be under stood by people who are experienced Windows or Mac users but have not used Linux or OFGT much before Sources and documentation for OFGT can be obtained here http km fao org
29. resolve the related dependencies 13 Click Next 14 The installation may take some time 15 Choose whether or not to create a Desktop and a Start Menu icon 16 Click Finish To compile the Open Foris Geospatial Toolkit you need to compile GDAL manually 1 Download the installer from the gdal official repository e g gdal 1 10 1 tar gz 2 Save it in your CygWin home folder e g C cygwin home or C cygwin64 home or in another destination of your choice 3 Run CygWin NOTE FOR INSTALLATION RUN CYGWIN AS ADMIN Right click on Start gt All Programs gt CygWin gt CygWin Terminal and Run as admin credentials 4 Install GDAL using the following commands the last two can take some time to complete cd folder containing gdal 1 10 1 tar gz e g cd C cygwin home mind the simple slash tar xvzf gdal 1 10 1 tar gz cd gdal 1 10 1 configure make make install User Manual 10 Now you can install OpenForis Still in CygWin run the following commands wget http foris fao org static geospatialtoolkit releases OpenForisToolkit run chmod u x OpenForisToolkit run OpenForisToolkit run 4 Get Info After the first installation you can check the current version info with the command sudo oft info bash 5 Update the tools Update to the latest version use follwoing command sudo oft update bash 6 Uninstallation You can also uninstall all the tools To d
30. similar and adjacent class values in the input image and gives each area an own id OPTION Parameters b band use determined band of the image um maskfile use maskfile and process only areas having mask value gt 0 h help opens the help manual in the terminal NOTES User Manual 161 For the benefit of users running the script using the older version where the datafiles are based on the file order instead of options i and o the program can still be used that way After clumping pixels with identical class values but are not spatially connected will have different id EXAMPLE For this exercise following tools are used oft clump Open your working directory using cd home To run the oft clump we use the Input andsat_t1 tif Output clump tif oft clump landsat_tl tif clump tif User Manual 162 7 53 oft seg NAME oft seg Image segmentation tool OFGT VERSION 1 25 4 SYNOPSIS oft seg oft seg lt input gt lt output gt oft seg lt input gt lt output gt OPTIONS OPTIONS aw ask weights automin use automatically computed minimum distance threshold 4n Describes the pixel connectivity Default is 8n automax use automatically computed maximum distance threshold um maskfile use mask initial segment file If 4n is indicated the neighbourhood is reduced to consider only top bottom left and right pixels Additio
31. 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 138 55 45 690909 19 272727 16 054545 40 672727 40 036364 123 563636 14 909091 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 0 000000 Explanation of the values of each column Coll Segment ID Col2 Size Col3 Col9 Segment average pixel values of band3 band9 Col10 Col16 standard deviation value for each band 3 oft segstat including option shape For this exercise we want to create in a first step a mask file that is needed to define which pixels of the satellite image will be included in the calculation In this case we exclude all pixels that were 0 Input andsat_t1 tif Output landsat_t1_mask tif oft calc landsat_t1 tif LT52_CUBO0_mask tif create mask same dimension same location 1 10 10 Now we run the segmentation statistic not with the segmenta tion file we created before using oft seg but using a shapefile instead Input landuse shp landsat_t1_mask tif landsat_t1 tif Out put segstats_shp txt oft segstat shape landuse landsat_tl_mask tif landsat_t1 tif segstats_shp txt User Manual 132 Again lets take a look at our result segstats_shp txt head segstats_shp txt 1 10500000 0 0 2999 0 3499 6000 48 742120 21 032891 19 848100 41 126436 50 192329 126 019212 21 810292 Explanation of the values of each column Coll Segment ID Col2 Size Col3 of neighbours Col4 xmin Col5 xm
32. 10 mask_LT51650672009351JSA00 img This example will create an output image 50classes10percent img were every pixel has been assigned a class from 0 to 50 except the pixels of value 0 in the mask image EXERCISE For this exercise following tools are used oft cluster bash oft clump gdal_polygonize to compute clusters and convert them into polygons Open your working directory using cd home 1 oft cluster bash Let s run oft cluster with Input landsat_t1 tif Output cluster50 tif for 50 classes and 10 percent Note it takes some time computing so be patient oft cluster bash andsat_t1 tif cluster50 tif 50 10 Load the result in QGIS and see that all the pixel values are between 1 and 50 corresponding to the 50 classes we defined in the command line User Manual 139 Figure 23 Cluster50 tif 2 oft clump bash Now we will run oft clump This tool is meant for separating uniform regions in a class image Get detailed information under oft clump Input cluster50 tif Output clump_clus50 tif oft clump cluster50 tif clump_clus50 tif 3 oft cluster bash In the last step we want to create polygons using the Input clump_clus50 tif Output clump_clus50 shp gdal_polygonize py clump_clus50 tif f ESRI Shapefile clump clus50 shp User Manual 140 Figure 24 Left Zoom into the cluster image Cluster50 tif Right Corresponding zoom into the shapefile clump_clus50 shp
33. 2404770 00 5 00 53 00 26 00 28 00 54 00 81 00 131 00 39 00 94788 00 773490 00 2431680 00 1 00 51 00 24 00 25 00 45 00 65 00 127 00 33 00 User Manual 106 201536 00 774750 00 2439390 00 1 00 54 00 25 00 27 00 50 00 71 00 130 00 35 00 88531 00 771450 00 2431110 00 1 00 47 00 21 00 18 00 37 00 48 00 126 00 21 00 123374 00 774150 00 2433990 00 1 00 54 00 24 00 30 00 35 00 75 00 132 00 42 00 97345 00 776220 00 2431950 00 1 00 52 00 23 00 24 00 42 00 60 00 131 00 30 00 199041 00 773190 00 2439120 00 1 00 51 00 23 00 23 00 52 00 58 00 130 00 28 00 144276 00 775860 00 2435400 00 1 00 49 00 22 00 21 00 45 00 59 00 125 00 30 00 180961 00 772680 00 2437890 00 1 00 49 00 21 00 21 00 36 00 61 00 126 00 28 00 185386 00 772410 00 2438190 00 1 00 49 00 21 00 18 00 43 00 51 00 126 00 22 00 Explanation of the columns pixel_id x y class band1 band2 band3 band4 band5 band6 band7 4 Lets run oft ascstat awk oft ascstat awk sample_landuse txt Result is printed on screen Col Min Max Avg Std 1 4923 220664 0 116318 43 6345 83 2 736440 787020 0 771921 0 798 10 3 2448000 2403090 2431097 6 1035 67 4 1 0 25 0 2 844444 0 519269 5 44 00 69 0 53 455556 0 491606 6 19 0 37 0 24 82 0 383203 7 16 0 48 0 27 02 0 691350 8 34 0 62 0 46 74 0 711611 9 42 0 103 0 69 455 1 450889 10 124 0 136 0 129 43 0 252272 Explanation of the columns same as before pixel_id x y class band1 band2 band3 band4 band5 b
34. 3 11 04261044223288 0 38 9938254776416 11 04262634062336 0 38 99415014990515 11 04300732377466 0 38 9941664064954 11 04303909164155 0 38 99466885692982 11 04319717791531 0 38 99473365203311 11 04319706202726 0 38 99479844656671 11 0431969461398 0 38 99515464117336 11 04310091874687 0 38 99518697983437 11 04306906417552 0 bushland2 39 00340243948988 11 04234996851613 0 39 00296537982829 11 04267663255115 0 39 00290506714792 11 04270636631092 0 39 00271044958266 11 04355103802362 0 39 00271058813281 11 04362510127527 0 39 00308922316352 11 04433543402553 0 39 0031345553759 11 04436497858972 0 39 00316485086498 11 04442417551431 0 39 00373863444808 11 04457127447502 0 39 00378391140981 11 04457119324793 0 Then run the actual command genericCsvloPolygon py input csv output shp The output shp is in geographic WGS84 but does not carry that information You can transform it e g into UTM 36S WGS84 with the following command ogr2ogr s_srs EPSG 4326 t_srs EPSG 32736 proj output shp output shp Where EPSG 4326 stands for WGS84 source system and EPSG 32736 for UTM 36S WGS84 target system You can select any target system and find the EPSG code see http spatialreference org ref epsg EXAMPLE For this exercise following tools are used genericCsv ToPolygon py genericGEkml2csv bash ogr2ogr User Manual 15 This s
35. 3374 00 57 00 28 00 33 00 50 00 82 00 131 00 44 00 4 00 730785 00 2453134 00 50 00 3341 00 55 00 26 00 29 00 52 00 72 00 129 00 34 00 5 00 730785 00 2452134 00 50 00 3308 00 60 00 28 00 35 00 54 00 87 00 129 00 45 00 6 00 730785 00 2451134 00 50 00 3274 00 47 00 19 00 18 00 37 00 47 00 124 00 20 00 7 00 730785 00 2450134 00 50 00 3241 00 46 00 19 00 17 00 38 00 44 00 123 00 18 00 8 00 730785 00 2449134 00 50 00 3208 00 59 00 28 00 33 00 60 00 84 00 129 00 43 00 User Manual 118 9 00 730785 00 2448134 00 50 00 3174 00 66 00 34 00 42 00 57 00 98 00 130 00 56 00 10 00 730785 00 2447134 00 50 00 3141 00 52 00 23 00 21 00 53 00 61 00 127 00 27 00 Explanation of values for each column Coll pixel ID Col2 x coordinates Col3 y coordinates Col4 pixel col coordinate Col5 pixel row coordinate Col6 Col7 center pixel value for bands 1 7 2 Exercise using option mm and ws oft extr ws 3 mm o extr_mm txt training txt landsat_tl tif head extr_mm txt 1 00 730785 00 2456134 00 50 00 3441 00 52 00 24 00 24 00 51 00 65 00 128 00 29 00 50 00 23 00 24 00 46 00 64 00 128 00 28 00 52 00 24 00 25 00 53 00 70 00 129 00 32 00 2 00 730785 00 2455134 00 50 00 3408 00 59 00 27 00 34 00 47 00 82 00 132 00 46 00 56 00 27 00 33 00 46 00 80 00 131 00 44 00 59 00 31 00 39 00 49 00 90 00 132 00 53 00 3 00 730785 00 2454134 00 50 00 3374 00 57 00 28 00 33 00 50 00 82 00 131 00 44 00 5
36. 36 39 927273 124 654545 15 000000 1 145038 0 449467 0 533081 0 961550 0 939948 0 479899 0 769800 7 53 48 886792 20 056604 18 339623 37 207547 45 698113 125 698113 19 396226 1 049915 0 534037 0 586495 0 947841 1 169893 0 463470 0 967543 52 105 49 580952 20 866667 19 666667 38 161905 53 990476 126 361905 22 847619 0 988209 0 555855 0 780368 0 951960 2 100802 0 482856 1 089998 114 51 46 960784 19 470588 16 235294 41 294118 37 725490 124 764706 15 039216 0 937247 0 542326 0 789639 0 807319 1 201306 0 428403 0 847603 138 55 45 690909 19 272727 16 054545 40 672727 40 036364 123 563636 14 909091 1 051854 0 449467 0 890655 1 155575 1 439697 0 739460 0 866511 The output is basically the same as in step 4 However now average and standard deviation are not given for the whole image but for each zone segment value of the mask file exception value 0 that is not processed Explanation of values for each column Coll ID in this case one as no mask file has been given Col2 Number of pixels Col3 Average value of band1 Col4 col9 Average value of band2 band7 Col10 col16 Standard deviation of band1 band7 7 Depending on the purpose you can now try the different options mm if you want to compute minimum and maximum values as well noavg if you do not want to output the average nostd if you do not want to compute the standard deviation The output will always be in the following order ID number of pixels minimum
37. 4 00 27 00 29 00 48 00 77 00 130 00 41 00 58 00 29 00 36 00 52 00 82 00 131 00 44 00 4 00 730785 00 2453134 00 50 00 3341 00 55 00 26 00 29 00 52 00 72 00 129 00 34 00 52 00 24 00 27 00 48 00 68 00 128 00 31 00 58 00 27 00 32 00 54 00 80 00 129 00 41 00 5 00 730785 00 2452134 00 50 00 3308 00 60 00 28 00 35 00 54 00 87 00 129 00 User Manual 119 00 56 00 129 00 36 00 00 90 00 730785 00 19 00 00 124 00 00 48 00 730785 00 19 00 00 123 00 00 27 00 129 00 2451134 00 18 00 45 00 19 00 18 00 125 00 2450134 00 17 00 46 00 17 00 46 00 18 19 00 39 124 00 60 37 49 38 49 31 00 51 00 76 00 00 30 00 37 00 48 00 50 00 3274 00 47 00 00 47 00 124 00 17 00 37 00 45 00 00 20 00 19 00 21 00 50 00 3241 00 46 00 00 44 00 123 00 17 00 37 00 40 00 00 20 00 18 00 21 00 Explanation of values for each column Coll pixel ID Col2 x coordinates Col3 y coordinates Col4 pixel x coordinated Col5 pixel y coordinates Col6 Col12 min values for bands 1 7 Col13 Col19 max values for bands 1 7 Col20 Col26 center pixel values for bands 1 7 3 Exercise using option csv and ws oft extr ws 3 head extr_3 txt CSV o extr_3 txt training txt landsat_tl tif 1 000000 730785 000000 2456134 000000 50 000000 3441 000000 2 000000 730785 000000 2455134 000000 50 000000 3408 000000 3 000000 730785 000000
38. 57973 129 559346 33 277298 5 55 54 367835 25 734659 28 453136 53 725893 74 190155 130 886716 36 174309 6 66 50 987633 23 044892 23 452312 52 655091 65 861426 128 754701 29 121125 7 9999 52 926014 24 353222 27 224344 48 176611 77 276850 132 054893 38 276850 8 88 54 133652 25 214797 28 140811 49 842482 74 985680 131 004773 37 408115 9 99 54 772519 25 961832 29 036641 52 786260 78 035115 130 658015 39 607634 10 1000 51 588723 23 134328 24 255390 45 487562 68 208955 130 310116 33 121061 11 1111 53 236948 24 644578 27 423695 48 779116 68 943775 131 594378 33 905622 The first column refers to the ID col2 refers to the numerical data that stored under newcol in the shapefile Col3 col9 contain pixel values of band1 band7 of the Landsat imagery User Manual 67 2 oft sigshp bash creating signature file with factorial val ues second we run the script using the id column called colour which stores factorial values Output sig_colour txt Output signature file sig_colour txt Run in terminal oft sigshp bash landsat_t1l tif landuse id colour sig_colour txt EPSG 32620 EPSG 32620 Again let s take a closer look at the first lines of the output file sig_colour txt head sig_colour txt 1 red 52 097317 23 696463 24 919711 45 321753 65 427785 129 033459 32 060358 2 green 54 157159 25 348832 28 176561 48 805278 72 468158 129 166550 34 397944 4 orange 53 864419 25 231642 27 932243 51 411361 71 957
39. 63985 5 47547080384603 32 63198971163985 5 47547080384603 32 63108751846197 108 Bushland Bushland_Thicket 2 Medium 2002 10 5 47461439045748 32 72136258245697 5 47461439045748 32 72226491949511 5 47551944746972 32 72226491949511 5 47551944746972 32 72136258245697 This is how you run the command python CsvToPolygon py inputdata csv output shp User Manual 13 71 2 genericCsvToPolygon py NAME GenericCsv ToPolygon py Program for creating polygons from text files OFGT VERSION 1 25 4 SYNOPSIS genericCsvToPolygon py genericCsv ToPolygon py lt input csv gt lt output shp gt DESCRIPTION GenericCsv ToPolygon py Program for creating polygons from text files The input file is a text file of the following format Polygon_id corner coordinates in WGS84 system Coordinate pairs are separated from others with a space and x y with a comma see under EXAMPLE NOTES The program is modified form the one by Chris Garrard http www gis usu edu chrisg python 2009 lectures ospy_ hw2a py SEE ALSO This input data is output from another script genericGEkml2csv bash and originally comes from Google Earth self digitized polygon kml s EXAMPLE The input file is a text file of the following format Polygon_id corner coordinates in WGS84 system User Manual 14 Bushland1 38 99408253760913 11 04146530113384 0 38 99380823486723 11 04205402821617 0 38 99380826389991 11 04206992654894 0 38 9938254486711
40. 81 47 2035039 48 1918290 49 1222961 50 558651 51 332962 52 287434 53 320286 54 311067 55 217529 56 180595 57 138396 58 93221 59 57114 60 38722 61 32169 62 25924 63 18311 64 12510 65 9783 66 7020 67 5022 68 3874 69 3116 70 2294 71 1647 72 1193 73 848 74 632 75 408 76 284 77 185 78 163 79 134 80 72 81 73 82 41 83 16 84 11 85 8 86 10 87 4 88 5 89 7 90 10 91 4 92 6 93 2 94 2 96 2 97 1 98 2 99 3 101 1 102 DOS 2 ioe 2 ios ik IMO it Moe OA aE Lali TET OSS Al SAO 22 2226228292130 132 1 138 1 139 1 144 1 147 1 152 1 156 1 165 2 168 1 169 1 174 1 176 1 180 1 187 1 196 1 206 1 208 1 220 1 246 1 255 2 AOS 000002 LA ESO ZAS 9 210 6 ie sis file 2 iy 26 16 646 17 8742 18 191086 19 2508329 20 4562947 21 718031 22 338584 23 429870 24 487321 25 333295 26 255746 27 231077 28 161926 29 99078 30 52656 31 Explanation 1 1 image value 2 10500000 Frequency of image value 1 3 1 Number of band After that the output consists of value frequency pairs More detailed the pair 20 1 means that 1 pixel of value 20 was found within the region determined by image value 1 Also a single pixel with value 27 was found and the number of pixels with value 28 was again 1 User Manual 126 7 42 oft mm NAME oft mm computes minimum and maximum values for each band of the input file OFGT VERSION 1 25 4 SYNOPSIS oft mm oft mm um maskfile lt input gt DESCRIPTION For the input image the command provides inline minimum and maximum values per
41. 874 26 903766 31 171548 42 291841 78 776151 133 120293 41 883891 21 5 55 277745 26 597769 29 771580 56 949501 76 772754 128 934234 36 727540 22 4 54 130526 24 966316 29 842105 42 627368 85 372632 134 662105 45 390526 23 4 54 960094 26 014085 28 808685 54 773474 75 338028 129 531690 34 167840 24 1 57 802077 27 928833 34 113622 48 773060 83 804520 132 198839 43 640501 25 3 58 298009 28 367690 33 835545 48 340315 82 241186 132 243467 45 336790 Explanation of columns col 1 ID of the polygon coll2 landuse class of the polygon User Manual 148 col 3 9 pixel values of bandl band7 of the Landsat imagery 4 Now run oft nn with oft nn i images landsat_tl tif o results my_knn tif Following variables will be asked Input signature file name sig_landuse txt Number of k 5 Nbr of output variables 1 Cols of 1 output vars in sig file Output var 1 2 Here we define col2 where the information on landuse classes is stored in sig_landuse txt Class Other 0 1 1 5 Load your result my_knn tif in QGIS You can see the polygons labelled corresponding to their landuse class on top of our result my_knn tif of which the pixel values vary between 1 5 eg 1 78283 as there are 5 landuse classes 1 2 3 4 5 User Manual 149 Figure 26 Result my_knn tif overlayed with landuse shp User Manual 150 7 48 oft nn training data bash NAME oft nn training data bash Script for preparing
42. 9 2166 50 10162 51 29145 52 70813 53 136848 54 145398 55 117541 56 82955 57 40937 58 14060 59 4255 60 1618 61 707 62 345 63 208 64 140 65 103 66 83 67 48 68 42 69 15 70 17 71 13 72 6 73 3 742 763771 where first three values are 1 1 Mask value 2 657846 Frequency of mask value 1 3 1 Number of band After that the output consists of value frequency pairs That is entry 12 1 means that 1 pixel of value 12 was found within the region determined by mask value 1 Accordingly we can see that also single pixels with values 46 was found and that the number of pixels with value 47 was five In practical applications the output needs to be converted into more readable format and usable information For example one could be interested in the median Landsat DN value within the mask When using hr option to produce the output the median could be computed using awk and the following equation awk obs_point _ 2_ _ 4 2 _ if NR 1 _ for i 5_ i lt _NF_ i sum sum i if sum_ gt obs_point _ print i 4 exit TRISTI Note that here we exclude background value 0 from the compu tation User Manual 123 EXERCISE For this exercise following tools are used oft his Open your working directory using cd home 1 oft his Lets run a oft his with Input andsat_t1 tif Ouptut histogram txt when asked set the maximum input value to 255 oft his i landsat_tl tif o histog
43. 95 00 89 00 65 00 332 00 732285 00 2444885 00 100 00 3066 00 2 00 2 00 100 00 3066 00 2 00 2 00 100 00 3066 00 46 00 19 00 17 00 40 00 41 00 124 00 46 00 19 00 17 00 40 00 41 00 124 00 100 00 3066 00 55 00 44 00 36 00 80 00 53 00 25 00 55 00 44 00 36 00 80 00 53 00 25 00 333 00 732285 00 2443885 00 100 00 3033 00 2 00 2 00 100 00 3033 00 2 00 2 00 100 00 3033 00 46 00 20 00 18 00 39 00 45 00 124 00 46 00 20 00 18 00 39 00 45 00 124 00 100 00 3033 00 56 00 43 00 35 00 81 00 56 00 26 00 56 00 43 00 35 00 81 00 56 00 26 00 334 00 732285 00 2442885 00 100 00 3000 00 2 00 2 00 100 00 3000 00 2 00 2 00 100 00 3000 00 48 00 20 00 18 00 36 00 42 00 125 00 48 00 20 00 18 00 36 00 42 00 125 00 100 00 3000 00 55 00 43 00 35 00 77 00 54 00 27 00 55 00 43 00 35 00 77 00 54 00 27 00 User Manual 43 ee ae a ee ee ee eG hor roprrprrprrprrorpr i r prrprrprrprrprrpr t ee ee oe ee ee eo ae Saree F SO ee ee ee ee ee eee eo t Oe ee ee ee ee ee eo rhrrprrprrprrprrprrprr r hrrorrprrprrprrprrprrprproror hrrprrprrprrprrprrprrrrrprror hrrorrprrprrprrprrprror t oo o o o hrrprrprrprorprprrrrpr hrrorrprrsroprrprrprror oo o t Se See eee ee eee ee eee oe eo oer eeeee t
44. 95 255746 231077 161926 99078 52656 37538 26630 15925 11265 8864 6682 4744 3055 2146 1396 847 494 320 232 190 105 60 29 16 12 6 6 2 SSOFSUSOZWUONIODMDIAZLIOOMOUDNUM OAM C 000010000 Explanation 1 Image value 10500000 Frequency of image value 1 0 Number of band 0 frequency of value 1 in input image 0 frequency of value 2 in input image 0 frequency of value 3 in input image 1 frequency of value 20 in input image 1 pixel with value 20 4 frequency of value 32 in input image 4 pixels with value 32 2 2 Calculation of median Landsat DN value using AWK For this we are using the output histogramm_hr txt from 2 1 as the input awk obs_point 2_ _ 4 2 _ if NR 1 for i 5 i lt NFU i sum sum i if sum gt obs_point print i 4 exit histogram_hr txt The output is printed in the terminal in our case the median DN values is 48 3 oft his with option compact Lets run a oft his with Input landsat_t1 tif Ouptut histogram_compact txt again the maximum input value to 255 oft his i landsat_tl tif o histogram_compact txt compact head histogram_compact txt User Manual 125 Extraction of histogram_compact txt output is 7 lines for each band one which makes it more readable IL MO OOWOO 1 AX 1 2 al ey ab A SO IL Sy a By GE Ss SH gs SN 36 2 37 5 38 8 39 7 40 5 41 176 42 1576 43 12371 44 114959 45 758774 46 17739
45. 973 129 559346 33 277298 5 pink 54 367835 25 734659 28 453136 53 725893 74 190155 130 886716 36 174309 6 red 50 987633 23 044892 23 452312 52 655091 65 861426 128 754701 29 121125 7 blue 52 926014 24 353222 27 224344 48 176611 77 276850 132 054893 38 276850 8 orange 54 133652 25 214797 28 140811 49 842482 74 985680 131 004773 37 408115 9 green 54 772519 25 961832 29 036641 52 786260 78 035115 130 658015 39 607634 10 orange 51 588723 23 134328 24 255390 45 487562 68 208955 130 310116 33 121061 11 red 53 236948 24 644578 27 423695 48 779116 68 943775 131 594378 33 905622 In comparison to the output of sig_newcol txt we can now see that col2 of sig_colour txt contains the factorial data User Manual 68 7 22 PointsToSquares py NAME Points ToSquares py converts XY locations into 100 x 100 m squares in a kml file OFGT VERSION 1 25 4 SYNOPSIS Points ToSquares py Points ToSquares py lt infile gt lt outfile gt lt UTM zone number gt lt ID gt lt X field gt lt Y field gt DESCRIPTION Points ToSquares py Conversion of user defined plot centre points in a text file into squares of 100 x 100 m in kml format These squares are training data collection locations meant to be used with a specific tool made for Google Earth Input textfile projection needs to be UTM South WGS84 zones Output kml is in latlon WGS84 EXAMPLE For this exercise following tools are used Points ToSquares py gdalinfo e Either use
46. 984 Explanation of values for each column Coll ID in this case one as no mask file has been given Col2 Number of pixels Col3 Minimum value of band1 Col4 col9 Minimum value of band2 band7 Col10 col16 Maximum value of band1 band7 Col17 col23 Average value of band1 band7 Col24 col30 Standard deviation of band1 band7 5 Now we run oft stat with input images landsat_t1 tif output results stats_mask txt optional mask images segments tif oft stat i images landsat t1 tif o results stats_mask txt um images segments tif 6 Print the first 10 lines of the output in terminal head results stats_mask txt 49 60 49 183333 20 366667 18 883333 36 800000 47 866667 126 500000 20 700000 0 929583 0 551321 0 640224 1 054450 1 890804 0 504219 1 046382 89 56 47 714286 20 053571 18 428571 37 125000 49 035714 125 571429 20 660714 1 073893 0 553325 0 598700 1 280092 1 747354 0 499350 0 977507 26 132 49 310606 20 295455 18 651515 35 840909 46 863636 126 833333 20 257576 0 989507 0 490188 0 552370 0 799136 1 763812 0 481199 1 088603 220 54 51 203704 22 629630 23 666667 38 592593 58 777778 131 370370 28 685185 2 870669 2 139444 4 374023 2 375333 9 681078 0 957518 6 804061 User Manual 136 231 132 56 416667 27 325758 34 606061 43 409091 82 636364 134 871212 45 454545 1 644058 1 207459 2 153490 1 689458 4 386434 2 786021 3 416090 236 55 46 200000 19 272727 16 290909 41 9636
47. ERSION 1 25 4 SYNOPSIS oft filter oft filter ot Byte Int16 Ulnt16 Ulnt32 Int32 Float32 Float64 CInt16 CInt32 CFloat32 CFloat64 h x xdim y xdim c const n nodata f filter v lt i inputfile gt lt i inputfile gt OPTIONS x dim Window size in x direction default 3 y dim Window size in y direction default 3 c const Constant used to multiply the resulting value n value Input NoData value ignored in calculation Def from infile v Verbose Ef filter Type of statistics to be computed default 1 mean standard deviation variance skewness rank coefficient of variation 100 std mean OPFWNEH O DESCRIPTION oft filter The program computes local statistics on values of a raster within the zones of a moving window 1 converts the point locations into the projection of the image User Manual 51 2 cuts a set of 20 km x 20 km tiles around the locations 3 converts the tiles to the coordinate system of the points 20 km x 20 km EXAMPLE For this exercise following tools are used oft filter Open your working directory using cd home In the first exercise we want to create the standard deviation for the moving window using the default window size and default statistics without defining f The output image is called std tif oft filter i landsat_tl tif o std tif Now we go through an example calculating the coefficient o
48. EXAMPLE To automatically find changes between a landsat image from year 2000 and 2005 using a threshold of 0 85 oft chdet bash landsat00 tif landsat05 tif change00_05 tif O 0 85 EXERCISE For this exercise following tools are used oft chdet bash Identify changed areas between year 2000 and 2012 using Landsat imagery using landsat_t1 tif and landsat_t2 tif 1 Open your working directory using cd home 2 Unpack the data 3 Now we run oft chdet bash to do the automated change detection using the input Landsat data oft chdet bash landsat_tl tif landsat_t2 tif change 0012 tif 0 0 85 Output includes the following A file beginning with imad name of outfile tif This file contains the raw results of the IMAD process one for each input band and the chi squared layer see Reference The specified output file This file contains 1 s and O s 1 s indicate areas of change and O s indicate areas of no change User Manual 79 7 26 oft clip pl NAME oft clip pl subsets an input image using the extent pixels size and projection of a reference image OFGT VERSION 1 25 4 SYNOPSIS oft clip p oft clip pl lt reference gt lt input gt lt output gt DESCRIPTION oft clip pl The straight forward tool oft clip pl subsets an input image using the extension pixel size and projection of the reference image EXERCISE For this exercise following tools are used oft clip pl 1 Use for this exe
49. NOPSIS oft prepare images for gapfill bash oft prepare images for gapfill bash lt a anchor gt lt f filler gt lt m an chor mask gt lt s second mask filler gt oft prepare images for gapfill bash lt a anchor gt lt f filler gt lt m an chor mask gt lt s second mask filler gt n ndvi threshold a Anchor Better image whose gaps are to be filled f Filler Filler image m Anchor mask 0 1 mask indicating bad areas on anchor image with 0 s Second mask 0 1 mask indicating bad areas on filler image with 0 OPTIONS n ndvi threshold If images differ a lot NDVI can be used to select only vegetated areas for mask Values like 0 4 or 0 5 are useful at some location on the world check your particular situation yourself DESCRIPTION oft prepare images for gapfill bash Takes the anchor and filler images as input Also their 0 1 masks indicating clouds and gaps are needed NDVI can be used to threshold areas with low vegetation off from User Manual 91 the models At this point bands 3 and 4 are used for NDVI computation Otherwise nbr of bands is not fixed but must be equal in the input images All material needs to be in same projection EXAMPLE For this exercise following tools are used oft prepare images for gapfill bash Open your working directory using cd home As landsat_t1 tif and landsat_t2 tif differ in their number of bands we need to exclude band 7 from lan
50. ON oft extr computes zone segment averages and standard deviations It produces two output files an output image and a text file You need to give at least the input image file option the output image o and the maskfile um In the output image each pixel gets assigned the average standard deviation for the zone segment it belonged to The output format in the text file is ID number_pixels avgband1 avgbandN OPTION nomd do not print metadata mm extract min and max values avg extract average values var extract variances ws n size n of extraction window odd o outfile output file name Please note that the default behaviour is to extract window s center pixel values User Manual 117 EXAMPLE For this exercise following tools are used oft extr 1 Open your working directory using cd home 1 Let s run oft extr using the input image landsat_t1 tif with the point text file training txt Output extr txt with no extra option oft extr o extr txt txt training txt images landsat_tl tif You will be asked X coord column in input file 2 Y coord column in input file 3 Now we take a closer look at our result head extr txt 1 00 730785 00 2456134 00 50 00 3441 00 52 00 24 00 24 00 51 00 65 00 128 00 29 00 2 00 730785 00 2455134 00 50 00 3408 00 59 00 27 00 34 00 47 00 82 00 132 00 46 00 3 00 730785 00 2454134 00 50 00
51. Open Foris Geospatial Toolkit USER MANUAL Food and Agriculture Organization of the United Nations Viale delle Terme di Caracalla 00153 Rome Italy Version 1 25 4 October 2013 OPENFORIS SE A Ob OO Contents 1 Introduction 1 1 About this manual 1 2 O A 2S Gye weed oS ae eae ks Sah ak hie 1 3 The great potential of OFGT 1 4 First time users 0000000 0000000084 License Installation of Open Foris Geospatial Toolkit 3 1 Linux debian based distributions Ubuntu Debian etc 3 2 Linux rpm based systems PCLinuxOS RedHat SuSE etc 3 3 Mac OS X Lion a vee a oe oa La ia ke 3 4 Windows Cygwin installation o a a a Get Info Update the tools Uninstallation OFGT Tools documented General Tools 7 1 CsvToPolygon py sha rra 405 2 9 6 Gon a ea 7 2 genericCsv ToPolygon py 200304 a ees 7 3 genericGEkml2csv bash 0 0 0 0 2 7 4 GExml2csv bash Sai a le ee 7 5 oft addattr py Silueta 7 6 oft addpct py a See wg gig Os 6 ee Bek Pe eR oe 7 7 oft admin mask bash 2 0 0 e e 150 cOMEDD aA da al og e e e e els e SRB 7 9 oft classvalues compare bash To be tested 7 10 oft classvalues plot bash To be tested 7 11 oft combine masks baSh 0 0 0 2 7 12 oft compare overlap bash To be tested TI oOMEcroOp Bashi re Ets ss ets Be Bh E e Ad eed 7
52. Output segstats txt oft segstat landsat_tl_min50 tif landsat_tl tif segstats txt The tool will ask you now to define the NoData value which we will set to 0 Please give NODATA value 0 in this step you only need to type the number 0 Lets take a look at the first 10 lines of our result segstats txt head segstats txt 49 60 49 183333 20 366667 18 883333 36 800000 47 866667 126 500000 20 700000 89 56 47 714286 20 053571 18 428571 37 125000 49 035714 125 571429 20 660714 26 132 49 310606 20 295455 18 651515 35 840909 46 863636 126 833333 20 257576 User Manual 130 220 54 51 203704 22 629630 23 666667 38 592593 58 777778 131 370370 28 685185 231 132 56 416667 27 325758 34 606061 43 409091 82 636364 134 871212 45 454545 236 55 46 200000 19 272727 16 290909 41 963636 39 927273 124 654545 15 000000 7 53 48 886792 20 056604 18 339623 37 207547 45 698113 125 698113 19 396226 52 105 49 580952 20 866667 19 666667 38 161905 53 990476 126 361905 22 847619 114 51 46 960784 19 470588 16 235294 41 294118 37 725490 124 764706 15 039216 138 55 45 690909 19 272727 16 054545 40 672727 40 036364 123 563636 14 909091 Explanation of the values of each column Coll Segment ID Col2 Size Col3 Coln Segment average pixel values of band3 bandn 2 oft segstat including std Lets run oft segstat including the option of adding the stan dard deviation Input landsat_t1 tif landsat_t1_min50 tif
53. PSIS oft ndvi bash oft ndvi bash lt input gt lt output gt lt R_band gt lt NIR_band gt lt input gt lt output gt lt R_band gt lt NIR_band gt mask DESCRIPTION oft ndvi bash creates an NDVI image using NIR VIS NIR VIS Input data is an image stack User gives the location of Red and NIR band in regular Landsat TM ETM 3 and 4 Number of bands is not restricted OPTIONS mask include a mask_image into this process by using this option EXAMPLE For this exercise following tools are used oft ndvi bash Open your working directory using cd home Run the command line for calculating the NDVI for your satellite im age where landsat_t1 tif is your input image and NDVI_landsat_t1 tif will be your NDVI output image The numbers lt 3 gt and lt 4 gt refer to the band numbers for the VIS and NIR bands oft ndvi bash landsat_tl tif results NDVI_landsat_t1 tif 3 4 User Manual 88 LoadNDVI_landsat_t1 tif in QGIS Check that all pixels of your NDVI image have the expected values between 1 and 1 Here is an example of how the result looks like Figure 14 Zoomed view of the original Landsat image User Manual 89 Figure 15 Zoomed view of the NDVI result using the freak out colour map in QGIS User Manual 00 7 30 oft prepare images for gapfill bash NAME oft prepare images for gapfill bash prepares images and masks for oft gapfill OFGT VERSION 1 25 4 SY
54. UTHORITY EPSG 32620 AXIS Easting EAST AXIS Northing NORTH User Manual 168 Figure 31 User Manual 169
55. X AND UBUNTU 12 04 WHERE ADMINISTRATIVE RIGHTS WILL BE REQUESTED ONLY FOR THE INSTALLATION The Cygwin project provides a Linux terminal in Windows 1 Download either setup x86 exe or setup x86_64 exe 2 Run it as admin right click on setup exe and Run as admin credentials 3 Click Next 4 Choose Install from Internet 5 You may leave the destination folder as C cygwin for All Users 6 Choose any local package directory it will be used for future storage of installers 7 Select Direct Connection unless your connection requirements are different 8 Choose a download site basing on site country domain or known availability or add your own preferite 9 If it is a first time installation of CygWin acknowledge the warning with OK or click on Skip to activate them if you already have CygWin installed you could skip the installation or check how the installation may affect the existing version 10 During the installation ensure to flag the following options under the Bin column use the Search field for a faster retrieval of the needed components type the package name in the field expand the correct group search for the package and click on Skip to see it changed to the version number a under Devel i gcc g User Manual 9 li make b under Net i wget c under Libs i gsl ii gsl apps iii gsl devel iv gsl doc 11 Click Next 12 Flag Select required packages and click Next to
56. _tl_6bands tif NOTE the mask value to be used is 2 so conversion of mask from value 1 to 2 input landsat_t1_6bands_mask tif output mask1 tif oft calc landsat_tl_6bands_mask tif maskl tif 1 11 02 Create mask for landsat_t2 automatic output landsat_t2_mask tif oft trim mask bash landsat_t2 tif Convert mask value to 2 landsat_t2_mask tif output mask2 tif oft calc landsat_t2_mask tif mask2 tif 1 al O 2 Run oft compare overlap bash oft compare overlap bash landsat_tl_6bands tif landsat_t2 tif maskl tif mask2 tif 1000 Output img12mask12_sed txt printed on screen head imgl2mask12_sed txt 329 00 732285 00 2447885 00 100 00 3166 00 2 00 2 00 100 00 3166 00 2 00 2 00 100 00 3166 00 53 00 25 00 27 00 48 00 71 00 131 00 53 00 25 00 27 00 48 00 71 00 131 00 100 00 3166 00 66 00 60 00 66 00 88 00 98 00 69 00 66 00 60 00 66 00 88 00 98 00 69 00 User Manual 42 330 00 732285 00 2446885 00 100 00 3133 00 2 00 2 00 100 00 3133 00 2 00 2 00 100 00 3133 00 54 00 25 00 27 00 48 00 71 00 128 00 54 00 25 00 27 00 48 00 71 00 128 00 100 00 3133 00 61 00 53 00 51 00 100 00 77 00 49 00 61 00 53 00 51 00 100 00 77 00 49 00 331 00 732285 00 2445885 00 100 00 3100 00 2 00 2 00 100 00 3100 00 2 00 2 00 100 00 3100 00 56 00 25 00 29 00 53 00 73 00 128 00 56 00 25 00 29 00 53 00 73 00 128 00 100 00 3100 00 67 00 61 00 66 00 95 00 89 00 65 00 67 00 61 00 66 00
57. and6 band7 And of course the interesting lines are line 4 11 User Manual 107 7 37 oft avg NAME oft avg computes zone segment averages and standard deviations OFGT VERSION 1 25 4 SYNOPSIS oft avg oft avg i lt input gt o lt output gt um lt maskfile gt oft avg i lt input gt o lt output gt um lt maskfile gt std oft avg i lt input gt o lt output gt ot Byte Int16 Ulnt16 Ulnt32 Int32 Float32 Float64 h help DESCRIPTION oft avg computes zone segment averages and standard deviations It produces two output files an output image and a text file You need to give at least the input image file i option the output image o and the maskfile um In the output image each pixel gets assigned the average standard deviation for the zone segment it belonged to The output format in the text file is ID number_pixels avgband1 avgbandN OPTION Parameters std The program computes and prints out also the std s as extra bands in the output image and extra columns in the text file ot Byte Int16 Ulnt16 Ulnt32 Int32 Float32 Float64 output data type h help User Manual 108 NOTE For the benefit of users that are running scripts using the older version based on order of datafiles instead of options o and um the program can still be used that way EXAMPLE For this exercise following tools are used oft avg 1 Open your working directory using cd home
58. ation equals to less than larger than not equal to if clause maximum of two values minimum of two values Ss Sway All sl F User Manual 72 bit level operator natural logarithm pixel column coordinate pixel row coordinate power e natural logarithm x base e exponential function gt 7za Oo WW OPTION Parameters inv the notation of the equations has changed in version 2 0 In case you want to use the old notations please use the inv option of format Any GDAL output format can be specified If not speci fied output format will be tif ot output data type If not specified output data type will be the same as input data type ot Byte Int16 Ulnt16 Ulnt32 Int32 Float32 Float64 output data type Z M Q C L X M try to speed up the processing by reading n lines at the time Z 2000 M 1000 Q 500 L 50 X 10 um mask If a raster file is provided as a mask only pixels with value different than 0 in the mask will be used for the calculation NOTE The notation of the equations has changed in version 2 0 In case you want to use the old notations please use the inv option EXAMPLE For this exercise following tools are used oft calc 1 EXAMPLES OPERATORS 1 Addition Simple band addition band1 band2 oft calc in_image out_image hit return after defining this line User Manual 73 2 this number defines the number of bands your out_image will have hit return again 1 2 typ
59. ax Col6 ymin Col7 ymax Col8 edge pixels Col9 Segment average pixel values of bandl Coll0 Segment average pixel value of band2 Coln Segment average pixels valued of bandn User Manual 133 7 44 oft stat NAME oft stat computes segment statistics in a text file OFGT VERSION 1 25 4 SYNOPSIS oft stat oft stat i lt infile gt o lt outfile gt oft stat i lt infile gt o lt outfile gt um maskfile mm noavg nostd h help DESCRIPTION oft stat extracts segment level image statistics into a text file Computes image statistics at segment level and outputs a text file The output format in the text file is ID pixels avgband1 avg bandN stdband1 stdbandN You need to give at least the input image file i option and the output file o Normally you give also a maskfile um maskfile which is an image consisting of pixels with integer values Pixels having value 0 are not processed For all other mask values the statistics are reported separately When the um option is not used statistics are a summary of all pixels in the image OPTIONS noavg program does not compute the averages nostd program does not compute the std s mm program computes and prints out also minimum and maxi mum User Manual 134 h prints out help NOTE For benefit of users running scripts using the older version based on order of datafiles instead of options i o and um the
60. band OPTION um maskfile zero values in the maskfile will be excluded in the calculation maskfile extent must match inputfile extent EXAMPLE oft mm input tif EXERCISE For this exercise following tools are used oft mm grep 1 Open your working directory using cd home 2 Now we run oft mm with input images landsat_t1 tif oft mm images landsat t1 tif 3 The output will be printed in the terminal argc 2 Driver GTiff GeoTIFF Size is 3000 3500 Corner Coordinates User Manual 127 Upper Left 729285 000 2352885 000 Lower Left 729285 000 2457885 000 Upper Right 819285 000 2352885 000 Lower Right 819285 000 2457885 000 Center 774285 000 2405385 000 Band min 1 000000 Band max 255 000000 DoneClose Done Band 1 min 20 000000 Band 1 max 255 000000 Band 2 min 1 000000 Band 2 max 255 000000 Band 3 min 1 000000 Band 3 max 208 000000 Band 4 min 8 000000 Band 4 max 255 000000 Band 5 min 5 000000 Band 5 max 255 000000 Band 6 min 112 000000 Band 6 max 195 000000 7 7 4 If you are only interested in the min and max values for a certain band you can use the grep command Example for band 1 oft mm images landsat_tl tif grep Band 1 Band 1 min 20 000000 Band 1 max 255 000000 User Manual 128 7 43 oft segstat NAME oft segstat output segments shape and spectral statistics in a text file
61. ber of bands x defines to look up the x coordinates in column 2 and y defines to look up the y coordinates in column 3 oft crossvalidate i sample_landuse txt k 10 v 1 bands 7 x 2 y 3 Result is printed on screen k 10 normalize 0 RMSE 62255 181 Bias 1367 027 Avg 116318 433 Further and output file sample_landuse txt_out is created head sample_landuse_out User Manual 115 772650 000 773490 000 774750 000 771450 000 774150 000 776220 000 773190 000 775860 000 772680 000 772410 000 2404770 2431680 2439390 2431110 2433990 2431950 2439120 2435400 2437890 2438190 000 000 000 000 000 000 000 000 000 000 10557 94788 201536 88531 123374 97345 199041 144276 180961 185386 00 00 00 00 00 00 103566 128938 110055 127395 102471 123907 105271 130783 127426 126411 30 00 80 30 90 80 30 50 40 20 93009 30 34150 00 91480 20 38864 30 20902 10 26562 80 93769 70 13492 50 53534 60 58974 80 Explanation of the columns x y pixel_id estimate difference col3 col4 User Manua 116 7 40 oft extr NAME oft extr extracts pixel values from an image into a text file OFGT VERSION 1 25 4 SYNOPSIS oft extr oft extr nomd mm avg var ws n o outfile lt pointfile gt lt img file gt um lt maskfile gt DESCRIPTI
62. classifier OFGT VERSION 1 25 4 SYNOPSIS oft nn oft nn lt i input image gt lt o output image or output text file gt oft nn lt i input image gt lt o output image or output text file gt OPTIONS OPTIONS h help ot Byte Int16 UInt16 UInt32 Int32 Float32 Float64 Cint16 CInt32 CFloat32 CFloat64 define output type um lt maskfile gt only areas having mask value larger than O are processed dem lt demfile gt use given dem and vertical distance rules prompted by the program hrules use horizontal distance rules prompted by the program to restrict the search in horizontal direction segme use segments in the mask file If this option is used the processing is done at the segment level speed approximate k nn asks for speed parameter Experimental or lt output_txtfile gt save weights for training data records for later calculations of large area statistics aw ask weights for the input bands dw 1 2 3 weight the nearest neighbor data with l equal 2 inverse distance 3 inverse distance squared default weights norm normalize the image features and the training data features to mean 0 and std 1 default is no normalization lu lt image gt use given land use image for stratification of the reference data NOT IMPLEMENTED YET adm lt image gt use given administrative borders to collect weights for field plots by administrative unit e
63. cript performs conversion from a set of generic kml for mat polygons created in Google Earth GE into one combined textfile This textfile can then be converted into a shapefile using script genericCsv ToPolygon py e How to create polygons in Google Earth and save them as kml files e Then open your working directory using cd home The procedure is 1 Put the kml s into one folder 2 Launch genericGEkml2csv bash in that kml folder This creates a csv file output csv genericGEkml2csv bash 3 Launch genericCsv ToPolygon py in the same folder with param eters as follows genericCsvloPolygon py output csv output shp The shapefile name can be as you wish e g settlements168063 shp The shapefile is in geographic WGS84 but does not carry that infor mation You can transform it e g into UTM 36S WGS84 with the following command Input output shp Output proj_output shp ogr20gr s_srs EPSG 4326 t_srs EPSG 32736 proj_output shp output shp Where EPSG 4326 stands for WGS84 source system and EPSG 32736 for UTM 36S WGS84 target system You can select any target sys tem and find the EPSG code see http spatialreference org ref epsg User Manual 16 7 3 genericGEkml2csv bash NAME genericGEkml2csv bash converts separate kml files from Google Earth into one CSV file OFGT VERSION 1 25 4 SYNOPSIS genericGEkml2csv bash DESCRIPTION genericGEkml2csv bash converts
64. d with a space or tab Prints the average RMSE and bias on screen Saves original value estimate and difference in an output file If id or x and y are given they are printed out as well If the id is indicated in the command line the id s of 10 nearest neighbours are printed into the output file User Manual 113 OPTION Parameters dw weight the nearest neighbour data with 1 equal default 2 inverse distance 3 squared inv distance weights x column for x coordinate y column for y coordinate id column for id norm normalize the image features default is no normalization mindist use a minimum spatial distance e g 1000 Obser vations closer than that based on the x and y coordinates are not allowed as neighbours default is no restriction maxdist use a maximum spatial distance e g 50000 Obser vations outside that radius are not allowed as neighbours default is no restriction dem column and threshold value e g 1000 for restriction of neighbours in vertical direction default is no restriction lu column used for stratification of the data If given separate RMSEs are computed for each class indicated in the column default is no stratification EXAMPLE 1 Input data download for this exercise sample_landuse txt You might have created it already in exercise oft sample within polys bash 2 Open your working directory using cd home
65. dsat_t1 tif by carrying out following procedure gdal_translate landsat_tl tif landsat_tl_6bands tif b 1 b 2 b 3 b 4 b 5 b 6 Let s run oft prepare images for gapfill bash using following input oft prepare images for gapfill bash a landsat_tl_6bands tif f landsat_t2 tif m landsat_tl_mask tif s landsat_t2_mask tif Two output images mask are automatically processed gapmask_landsat_t1_6bands_lanc and goodarea_mask_landsat_t1_6bands_landsat_t2 tif Figure 16 gapmask_landsat_t1_6bands_landsat_t2 tif User Manual 92 Figure 17 goodarea_mask_landsat_t1_6bands_landsat_t2 tif User Manual 93 7 31 oft reclass NAME oft reclass is a reclassification program OFGT VERSION 1 25 4 SYNOPSIS oft reclass oft reclass lt inpufile gt oft reclass OPTIONS lt inpufile gt DESCRIPTION oft reclass changes pixel values to alterenative values given in a text file The maxval parameter is used to allocate memory for the reclassifi cation table If it is not given in the command line it will be asked interactively The reclassification text file should consist of records with input value column 1 and one or more space separated output values Thus the structure could be iL 209 208 299 2 0 00 3 125 100 16 4 0 0 112 The program asks how many output values the user wants to produce for each input band With the given example reclassification file the use
66. e created it already in exercise Google Earth training data into shapefile which can be found in the Wiki Open your working directory using cd home Now run the script in the command line within input raster landsat_t1 tif and input shapefile anduse shp name refers to the shapefile ID If you look at the attribute table of landuse shp you see that you could also use the column id Here we chose name to make it more transparent 100 is the sample size chosen for this exercise Note In the commmand line the extension shp of the shapefile is not included oft sample within polys bash landsat_t1 tif landuse name 100 Output are three text files greyvalues greyvals_landuse txt histogram histogramlanduse txt sample output sample_landuse txt User Manual 61 Here you can see an excerpt of sample_landuse txt Order is pixel_id x y class band1 band2 band3 band4 band5 band6 band 10557 00 772650 00 2404770 00 5 00 53 00 26 00 28 00 54 00 81 00 131 00 39 00 94788 00 773490 00 2431680 00 1 00 51 00 24 00 25 00 45 00 65 00 127 00 33 00 201536 00 774750 00 2439390 00 1 00 54 00 25 00 27 00 50 00 71 00 130 00 35 00 88531 00 771450 00 2431110 00 1 00 47 00 21 00 18 00 37 00 48 00 126 00 21 00 123374 00 774150 00 2433990 00 1 00 54 00 24 00 30 00 35 00 75 00 132 00 42 00 User Manual 62 7 20 oft shptif bash NAME oft shptif bash Rasterizes a shapefile to the
67. e output file to be created include extension inputfiles A set of input files include extension each separated by a space DESCRIPTION oft stack builds image stack from input files in the order of appear ance The output format of the first input file is used The images need to have exactly the same size rows x cols OPTIONS ot Optional The output image type By default the first input image type is used User Manual 99 um Optional A mask file used to restrict the extent of the processing oft stack builds an image stack from input files in the order of appearance By default the output format and type of the first input file is used N B The images need to have exactly the same size rows x cols EXAMPLE To create a 6 band stack of Landsat data from individual input rasters in TIF format oft stack o landsat7band tif landsatbl tif landsatb2 tif landsatb3 tif landsatb4 tif landsatb5 tif landsatb7 tif the above can be written using wildcards oft stack o landsat7band tif landsatx tif EXERCISE For this exercise following tools are used oft stack 1 Open your working directory using cd home 2 Now we run oft stack using two input images landsat_t1 tif and landsat_t2 tif to create the output stack image called stack tif oft stack o stack tif landsat_tl tif landsat_t2 tif 3 Take a closer look at your output in
68. e your clause and hit return Now out_image should be in process 2 Division band1 band2 oft calc in_image out_image 2 1 2 3 Equals to if pixel value of band1 equals O then set it to 0 otherwise to 1 oft calc in_image out_image LI AE bande W e 0 S tien Oso tine wits elm 10 FLO Oley 4 Boolean You can also use boolean larger than operator to determine if 1 gt 2 oft calc in_image out_image 2 1 2 gt 5 The usage of the IF clause if band1 50 output 1 else output 0 This also creates also a simple mask containing 1 for pixels of interest and O for background oft calc in_image out_image 1 1 50 gt 01 HMC Toenilil 2 30 sel 30 gt elem Al otherwise 0 0 1 if band1 band2 2 output 1 else output 0 oft calc in_image out_image 1 pil ed de Des i Pie a 4 anA A eel ete ES 2 2 SS then 1 orense 0 10 1 itr Jamal gt 50 or band2 gt 50 output 1 else output 0 User Manual 74 oft calc in_image out_image 1 ol BO gt 72 50 gt OM it ei 2 fy i leonel gt BO Re 50 gt nem 2 Pi 2 ornarwise i band 2 ss BO 2D US 250 then 1 otherwise 0 0 1 2 EXAMPLES ON APPLICATIONS 1 NDVI Calculate the NDVI for your Landsat image band3 Red band band4 NIR Band oft calc ot Float32 in_image out_image 1 HA 3 4 3 b4 b3 b4 b3 Note that the band4 in the input layerstack i
69. eer oti ay toe Bee ode 1 which becomes 1 1 B if bit one of band 1 equals to 1 0 constant 2 1 B if bit 2 of band 1 equals to 1 4 1 B if bit 4 of band 1 equals to 1 sum up the previous two terms 8 1 B if bit 8 of band 1 equals to 1 Te sum up previous two terms 9 1 B if bit 9 of band 1 equals to 1 sum up previous two terms 12 1 B if bit 12 of band 1 equals to 1 a sum up previous two terms lt if previous term is smaller than User Manual 76 2 output 2 if clause false 1 output 1 if clause true if 1 output 1 if clause true if Now what happens in practice is the following 1 Check bit 1 and record O if its is false and 1 if it is true 2 Check bits 2 4 8 9 and 12 and return their sum 3 if output of 2 is larger than zero second line above return 1 else return 2 4 if output of 1 is 1 return 1 else return output of 3 6 Creating a mask file Create a simple mask containing 1 for pixels of interest and 0 for background The equation in words if your pixel value equals O then set it to 0 otherwise to 1 oft calc in_image out_image 1 note that here we want to define our mask called out_image to consist of 1 band 10 10 7 Including a mask file oft calc um in_mask in_image out_image here the option um defining the mask file is added to the command 2 Fl 2 User Manual 17 7 25 oft chdet bash NAME oft chde
70. es u before dem in case of both NOTES Checking of the result is obligatory EXAMPLE For this exercise following tools are used oft nn training data bash Open your working directory using cd home The script oft nn training data bash extracts image values based on field data locations using input image landsat_t1 tif and for the field data we are using training txt oft nn training data bash i landsat_tl tif f training txt x 2 y 3 Let s take a closer look at our output va ues_for_nn head values _for_nn 1 730785 2456134 1 00 730785 00 2456134 00 52 00 24 00 24 00 51 00 65 00 128 00 29 00 2 730785 2455134 2 00 730785 00 2455134 00 59 00 27 00 34 00 47 00 82 00 132 00 46 00 3 730785 2454134 3 00 730785 00 2454134 00 57 00 28 00 33 00 50 00 82 00 131 00 44 00 4 730785 2453134 4 00 730785 00 2453134 00 55 00 26 00 29 00 52 00 72 00 129 00 34 00 5 730785 2452134 5 00 730785 00 2452134 00 60 00 28 00 35 00 54 00 87 00 129 00 45 00 6 730785 2451134 6 00 730785 00 2451134 00 47 00 19 00 18 00 37 00 47 00 124 00 20 00 7 730785 2450134 7 00 730785 00 2450134 00 46 00 19 00 17 00 38 00 44 00 123 00 18 00 8 730785 2449134 8 00 730785 00 2449134 00 59 00 28 00 33 00 60 00 84 00 129 00 43 00 9 730785 2448134 9 00 730785 00 2448134 00 66 00 34 00 42 00 57 00 98 00 130 00 56 00 User Manual 152 10 730785 2447134 10 00 730785
71. ew image must be in the same projection and gridding pixel locations In all masks O do not use 1 use To take several images into account re run Script produces also an accumulated mask showing common ok areas User Manual 158 EXAMPLE For this exercise following tools are used oft unique mask for nn bash 2 Open your working directory using cd home 2 For this exercise we will use mask tif as mask of the base image and landsat_t2_mask tif as the mask of the new image oft unique mask for nn bash m mask tif s landsat_t2_mask tif 3 Two output images are automatically processed landsat_t2_mask_unique_mask tif and landsat_t2_mask_accumulated_mask tif Figure 28 Mask of base image mask tif Figure 29 Mask of new image landsat_t2_mask tif User Manual 159 Figure 30 Output andsat_t2_mask_unique_mask tif User Manual 160 SEGMENTATION 7 52 oft clump NAME oft clump connected component labeling OFGT VERSION 1 25 4 SYNOPSIS oft clump oft clump lt i input gt lt o output gt oft clump lt i input gt lt o output gt b band um maskile h help DESCRIPTION oft clump Add spatial coherency to existing classes by combining adjacent similar classified areas Oft clump is meant for separating uniform regions in a class imag You may obtain such a class image by using e g oft cluster bash oft kmeans or oft nn The program looks for
72. f variation 100 std mean using the option f 5 Output coe var tif oft filter i landsat_tl tif o coe_var tif f 5 Calculation of the mean using the option f 0 Output mean tif oft filter i landsat_tl tif o mean tif f 0 Load your computed rasters in QGIS and verify your output statistics using Identify Results User Manual 52 User Manual Figure 8 Example of the computed mean tif 53 7 16 oft gengrid bash NAME oft gengrid bash generates a systematic grid over a raster image OFGT VERSION 1 25 4 SYNOPSIS oft gengrid bash oft gengrid bash lt input_img gt lt DX gt lt DY gt lt output gt DESCRIPTION oft gengrid bash generates a grid of points over an image text file with user defined spacing in x and y directions Output is a text file with the coordinates of the points Generates a text file with 3 entries for each point ID Xcoord Ycoord lt input_img gt is a georeferenced input image lt DX gt is the distance between the points in X direction lt DY gt is the distance between the points in Y direction Prints the average RMSE and bias on screen Saves original value estimate and difference in an output file If id or x and y are given they are printed out as well If the id is indicated in the command line the id s of 10 nearest neighbours are printed into the output file EXAMPLE For this exercise following tools are used oft gengrid bash
73. f training data Also figures of class means and standard deviations are provided Training areas need to be in shapefiles The figures of class means and std s for both required bands are created in the launching folder png format It also puts the class means and standard deviations into text files Pixel by pixel values are stored in a separate text file The pixel plots are created in a folder named plots_imagename_band1_band2 They are for all classes png image files And same as text files NOTES Make sure that you have installed GNUPLOT SEE ALSO A further script oft classvalues compare bash can then be used to compare up to 5 classes in one view User Manual 33 EXAMPLE For this exercise following tools are used oft classvalues plot bash Input data download for this exercise the Landsat imagery andsat_t1 tif and the shapefile anduse shp Open your working directory using cd home First of all make sure that you have installed textbfGNUPLOT Further information on Gnuplot and Ubuntu If you don t have Gnuplot type in your terminal sudo apt get install gnuplot press enter Run oft classvalues plot bash with input satellite image shapefile Attribute column for ID in this case name band3 band4 Input image landsat_t1 tif input shapefile landuse shp Note the output is automatically processed oft classvalues plot bash landsat_tl tif landuse na
74. following result Band 1 BB xmin ymin xmax ymax is 1408 1740 1713 1964 You can visualize the result by subsetting the image to these extents using gdal_translate gdal_translate srcwin 1408 1740 305 224 images forestc tif results bb_33 tif User Manual 28 The parameters for the size of the box are calculated as xmax xmin and ymax ymin Visualize the results qgis images forestc tif results bb_33 tif Figure 3 Example of using oft bb output bb_ 33 tif User Manual 29 7 9 oft classvalues compare bash To be tested NAME oft classvalues compare bash creates comparison plots of classes based on result of previous script oft classvalues plot bash OFGT VERSION 1 25 4 SYNOPSIS oft classvalues compare bash oft classvalues compare bash lt class1 gt lt class2 gt oft classvalues compare bash lt class1 gt lt class2 gt class3 class4 class5 DESCRIPTION oft classvalues compare bash This script is meant to be used after script oft classvalues plot bash It plots 2 5 classes in the same figure and the distinction of classwise point clouds can be evaluated It is launched in the folder containing classwise plots and text files produced by the above mentioned script OPTION Additional classes that can be plotted in the same figure Parameters class3 class4 class5 SEE ALSO Look at oft classvalues plot bash which computes input data for this tool EXAMPLE User
75. g county This enables you to compute statistics for each adm unit separately User Manual 146 DESCRIPTION oft nn carries out nearest neighbour estimation or classification of an image oft nn classifies or estimates an output value for every image anal ysis unit using given training data set and k nearest neighbour algorithm Nearest neighbours are determined based on Euclidean distances in the feature space In a classification the output is the class having the largest sum of weights In estimation the output value is computed as straight or weighted average of the k nearest neighbours You need to give at least the input image file i option and the output image o option OR the output text file or option NOTE the program will ask for the datafile number and location of target variables nbr of neighbours k and data type continuous or class Other parameters are asked when needed if you use extra options specified under OPTIONS Last columns of the training data set are used as the feature space In other words if the input image has four bands last four columns of the training data set should correspond to the values for training observations In cases of dem or u you need to have a corresponding column in your field data text file prompted by the program In case of dem is used we use absolute difference if you want to reject observations gt 500 m above or below the target pixel give
76. his exercise following tools are used oft kmeans oft gengrid bash oft extr Open your working directory using cd home The exercise is divided into two step first we prepare the input signature text file which is need for textitoft kmeans then we will run the classification tool itself 1 Creation of input signature text file We want to generate a grid of points over our image andsat_t1 tif using oft gengrid bash with user defined spacing in x and y direc tions in this case 5000 x 5000 m distance between the points in X and Y directions The output file gengrid txt contains information on the created grid ID x y oft gengrid bash landsat_tl tif 5000 5000 gengrid txt head gengrid txt 730785 2456134 730785 2451134 730785 2446134 730785 2441134 730785 2436134 730785 2431134 730785 2426134 730785 2421134 CONDOR WNHE User Manual 143 9 10 730785 730785 2416134 2411134 To extract the values from our input image andsat_t1 tiff for those pixels that lay on our grid we created in the previous step we run oft extr Output my_extr txt oft extr o my_extr txt gengrid txt landsat_tl tif head my_extr txt 1 N w al 00 730785 00 51 00 65 00 00 730785 00 37 00 47 00 00 730785 00 53 00 57 00 00 730785 00 34 00 43 00 00 730785 00 34 00 44 00 00 730785 00 36 00 51 00 00 730785
77. hosen form the top bar and click on the image The window Identify Results should pop up and with the average value for each band for that zone segment Band1 49 Band2 21 Band3 20 Band4 41 Band5 50 Band6 126 Band7 22 5 If you also choose to output standard deviations the format of the output files will be as follows text file e Coll ID value for zone segment e Col2 Number of pixels e Col3 col9 Average value of band1 band2 band7 e Coll0 col16 Standard deviation of band1 band2 band7 raster image file e bandl band7 average for band1 band2 band7 e band8 band14 standard deviation for band1 band2 band7 User Manual 110 7 38 oft countpix pl NAME oft countpix pl counts number of pixel with below or above a specific value OFGT VERSION 1 25 4 SYNOPSIS oft countpix pl oft countpix pl lt input gt lt value gt b v a band lt input gt is a raster image lt value gt is an real number If not precised oft countpix pl gives the total number of pixels If value is below the min or above the max of the image a warning is given OPTION v count all pixels with value value default b count all pixels below value a count all pixels above value band number of the band Default is Band 1 DESCRIPTION oft countpix pl counts the number of pixels within an image with default below or above options a specific value EXAMPLE For this exercise foll
78. ile_basename gt lt shapefile_id_fieldname gt lt shapefile_coverclass_fieldname gt lt output_sigfile gt oft sigshp bash lt image gt lt shapefile_basename gt lt shapefile_id_fieldname gt lt shapefile_coverclass_fieldname gt lt output_sigfile gt lt image_projection EPSG gt lt shp_projection_EPSG gt DESCRIPTION oft sigshp bash creates a signature file of an image e g Landsat based on training area polygons in shapefile format This file can be used in knn classification with stand alone program oft nn NOTE do not put shp into the second parameter basename The training areas and the image must be in the same projection OR you may give the projections in the command line as EPSG codes If the projections are not defined for both or one of the inputs or the program does not recognize it the script will warn This is not dangerous if the files really are similarly aligned The ID s must fit into a 16 bit Unsigned image 65500 The class values may be either numerical or verbal e g bushland Minimum parameters needed 1 2 imagefile shapefile User Manual 65 3 field name storing ids in shape 4 field name storing numeric class values in shape 5 ouput signaturefilename OPTIONS Parameters 6 projection of image file 7 projection of shapefile OTHERS This script can also be used after oft nn EXAMPLE For this exercise following tools are used oft sigshp bash
79. in integer EXAMPLE For this exercise following tools are used oft addattr py You might have created it already in exercise in the OFGT wikipedia How to create and export polygons from Google Earth GE Open your working directory using cd home The first lines of the attribute table of landuse shp look like this 1 red 2 green User Manual 20 3 orange 5 pink 6 red 7 blue 8 orange 9 green 10 orange In this exercise we create a space separated text file as a lookup table You can create it in any text editor such as gedit or kate and save the file as lookup txt in your working directory Note The first column contains the ID linking the lookup table to your shapefile and the second column contains the values you want to add to the new column of your shapefile i ai 2000 3 33 4 44 5 55 6 8 9 1 Now run the script in the command line Each time the value in the first column of lookup txt is found in the JoinAttributeName of the landuse shp field in our case called id The value in the second column is added in the field NewAttrName here called newcol Note The values need to be in integer How to change the data type in QGIS see further down oft addattr py landuse shp id newcol lookup txt Load landuse shp in QGIS and look at your attribute table You should now find the new column called newco with it values Take a look at the ID 7 The newcol value in
80. ion of time than with conventional software e And second automatised data processing makes applications repeat able which is of high advantage for many projects e All tools and methods developed under the Initiative are open source 1 4 First time users First time users the terminal is your friend The Open Foris Geospatial Toolkit tutorial is aiming to provide straight forward guidelines and examples to help first time users to familiarise themselves with the Open Foris Geospatial Toolkit This includes the installation of Ubuntu various geospatial tools and in particular the installation and application of the Open Foris Geospatial Toolkit You do not need to be an expert we just would like you to be curious to try things out Do not be afraid of using the command line We know that the terminal window is for many users a barrier of being afraid ruining everything and having to start from scratch These days the terminal is not exclusively for advanced computer enthusiasts Give it a try and just start playing around following the tutorials and instructions you can find in the wiki 2 License Open Foris Geospatial Toolkit is released under GNU GPLv3 license User Manual 6 3 Installation of Open Foris Geospatial Toolkit The Open Foris Geospatial Toolkit comes with an installer which is frequently updated It is named OpenForisToolkit run To run the installer please use the Terminal 3 1 Linux debian based distributions
81. ked off EXAMPLE For this exercise following tools are used oft prepare image for nn bash 2 Open your working directory using cd home 2 For this exercise we will use landsat_t1 tif as image file and landsat_t2 tif as the base image file landuse shp is the input shape User Manual 156 file of which we define landuse as the attribute to be used oft prepare image for nn bash i landsat_tl tif b landsat_t2 tif s landuse shp a landuse 3 The output image is automatically processed landsat_t1_mask tif 4 Check in QGIS the values of your output mask Figure 27 Output of oft prepare image for nn bash is landsat_t1_mask tif User Manual 157 7 51 oft unique mask for nn bash NAME oft unique mask for nn bash creates a unique mask for oft nn anal ysis OFGT VERSION 1 25 4 SYNOPSIS oft unique mask for nn bash oft unique mask for nn bash lt m mask of base image gt lt s mask of new image gt DESCRIPTION Unique means here that same pixel is not classified from several images It is needed in 2 cases 1 take an adjacent image into account or 2 use the new image to fill a cloud etc on nn classified base image As input you need a mask of the main image and a preliminary mask of the new image A preliminary mask for the new image can be run with oft trim mask bash If you need to add clouds or water do that before or after this unique mask script The n
82. ly for every gap pixel using a local model built using its adjacent pixels or 2 for a given number of Large Area subsets or 3 using both of these methods In the case 2 the option la followed by the number of requested Large Area LA subsets in X direction should be given The total number of LA subsets is the square of the given parameter If the user wants to use only Large Area models the option nolocal should be used Maskfile inputfile and outputfile are all required inputs They may be in any of the formats understood by GDAL The input image is a stack of the Anchor image and the Filler image The output values for Anchor are computed using Filler and the model The input image bands should be organized as follows User Manual 83 e band 1 to nbr_bands 2 Anchor image e bands nbr_bands 2 1 to nbr_bands Filler image The mask file shows the locations of the gaps areas which are suitable for collecting training data and areas which should not be processed The mask values are as follows 1 fill these pixels unusable data in anchor good data in filler 2 collect training data for regression model good data in both images 3 do nothing i e use the original values 2 cases good in anchor bad in filler OR non good in both images 0 do nothing image margins OPTIONS 1 la nbrLargeAreaWindows number of LA windows in X direc tion The total number of LA windows will be the square of
83. mage should be the NIR band and the band 3 the Red band Note also that the output data type should be specified as Float32 in order to have output values from 1 to 1 oft ndvi bash also creates a NDVI image using NIR VIS NIR VIS 2 NBR Normalised Burn Ratio NBR highlights areas that have burned using Landsat TM Calculate the NBR for your Landsat image oft calc in_image out_image 1 HA 7 4 7 b4 b7 b4 b7 3 dNBR In addition the differnence NBR dNBR technique is a form of Change Detection which is used to index the severity of a fire Calculate the differenced or delta dNBR for NBR_prefire NBR_postfire Note as you can t have two separate input files one for User Manual 75 NBR_prefire and a second for NBR_postfire you need to com bine the two output_bands into one file before applying the equation band 1 1 containing information on NBR_prefire and band 2 2 containing info on NBR postfire oft calc in_image out_image 1 H 2 band 1 1 contains info on NBR_prefire and band 2 2 contains NBR_postfire 4 Average of bands Compute an average of bands 1 2 and 3 of an image oft calc in_image out_image 1 1 2 3 3 bandi band 2 1 2 band3 3 divided by 3 3 5 Build a mask from LEDAPS QA layer Bit level operators does the first bit of band 2 equals to 1 1 ais to build a mask from LEDAPS QA layer Be 0 A
84. me 3 4 Output 1 pixelvalueslandsat_t1 tif bands 3 4 txt head pixelvalueslandsat_t1 tif_bands 3 4 txt Column 1 6 Pixel_ID X Y class from attribute name pixelvalue_bandnr3 pixelvalue_bandnr4 1 00 771870 00 2402010 00 6 00 22 00 47 00 2 00 771900 00 2402010 00 6 00 22 00 53 00 3 00 771930 00 2402010 00 6 00 23 00 55 00 4 00 771960 00 2402010 00 6 00 22 00 55 00 5 00 771990 00 2402010 00 6 00 21 00 53 00 2 classvalues_landsat_t1 tif_band_3 txt head classvalues_landsat_tl tif_band_3 txt Column 1 3 classvalue bandnr3 std User Manual 34 7 27 224344 2 480986 13 28 945946 1 679205 8 28 140811 2 322499 9 29 036641 2 258223 12 27 879464 1 288049 11 27 423695 1 199933 3 classvalues_landsat_t1 tif_band_4 txt head classvalues_landsat_tl tif_band_3 txt Column 1 3 classvalue bandnr4 std 7 48 176611 2 622561 13 45 385749 1 525189 8 49 842482 2 397968 9 52 786260 3 513642 12 49 943452 2 232350 11 48 779116 1 172885 4 Folder plots_landsat_t1 tif_bands_3_4 contains the classes to be used for oft classvalues compare bash User Manual 35 7 11 oft combine masks bash NAME oft combine masks bash combines several masks raster and shape files to one mask file OFGT VERSION 1 25 4 SYNOPSIS oft combine masks bash oft combine masks bash lt input1 gt lt input2 gt lt nodata gt oft combine masks bash lt input1 gt lt input2 gt
85. nal Options upon Execution Min segment size Minimum segment size in pixels Min spec dist btw segs Not asked if automin is specified above Max spec dist btw segs Not asked if automax is specified above Use size weighting O indicates no size weighting 1 indicates use size weighting DESCRIPTION oft seg region merging segmentation e oft seg uses a simple iterative region merging algorithm to merge each segment with its spectrally nearest adjacent seg User Manual 163 ment The spectral distance D between the segments is computed using all input bands and Euclidean distance e The algorithm is controlled by three parameters minimum seg ment size in pixels MinSize and minimum required MinDist and maximum allowed MaxDist spectral distances in the feature space The conditional merging is done in two phases First all segments which are 1 smaller than MinSize and 2 have a neighbouring segment to which the spectral distance is lt MaxDist are merged This step is iterated until no such seg ments exist After that all segments which have an adjacent segment with D lt MinDist are merged with their spectrally nearest neighbour e In addition the user can choose to weight the distance compu tation with the size pixels of the neighbouring segment e The tool can also compute the MinDist and MaxDist thresholds automatically To do that use autominand or automax options Otherwi
86. ns and Landsat 7 missing scanlines and trims the edges accepts 6 or 7 band image all values j O are considered nodata Note the output of oft trim maks bash can be furhter used for oft combine images bash EXERCISE For this exercise following tools are used oft trim mask bash 1 Open your working directory using cd home 2 Lets run oft trim mask bash using landsat_t2 tif Automatically processed output landsat_t2_mask tif oft trim mask bash landsat_t2 tif 3 Verify in QGIS your our result if the mask pixel values are 1 or 0 User Manual 103 Figure 21 Original image landsat_t2 tif with visible gaps in QGIS User Manual 104 Figure 22 Output landsat_t2_mask tif using the Pseudo colour colour map in QGIS User Manual 105 STATISTICS 7 36 oft ascstat awk NAME oft ascstat awk computes basic statistics for a space separated text file OFGT VERSION 1 25 4 SYNOPSIS oft ascstat awk oft ascstat awk lt input file textgreater DESCRIPTION oft ascstat awk computes basic statistics for a given input file or stdin Please not that the data must be provided as space separated EXAMPLE 1 For this exercise following tools are used oft ascstat awk 2 Open your working directory using cd home 3 The script oft ascstat awk computes basic statistics for our space separate input file sample _landuse txt head sample_landuse txt 10557 00 772650 00
87. o that enter the command sudo oft uninstall bash User Manual 11 7 OFGT Tools documented GENERAL TOOLS 7 1 CsvToPolygon py NAME CsvToPolygon py converts CSV file from GExml2csv bash into a shapefile OFGT VERSION 1 25 4 SYNOPSIS CsvToPolygon py CsvToPolygon py lt input csv gt lt output shp gt DESCRIPTION CsvToPolygon py is written in Python and creates shapefile polygons from a text file The program is modified form the one by Chris Garrard http www gis usu edu chrisg python 2009 lectures ospy_ hw2a py The input is a text file of the following format Polygon id land cover class land cover subclass tree cover class resolution of the image in GE Google Earth year and month of image in GE After the mark there are corner coordinates in WGS84 system This input data can be output from another script GExml2csv bash and originally derives from a training data collection tool created for GE User Manual 12 EXAMPLE For this exercise following tools are used CsvToPolygon py Open your working directory using cd home An example of the beginning of input data is following 106 OWL OWL_Open 2 Coarse 2002 1 5 47450324983224 32 54081338469396 5 47450324983224 32 5417154317423 5 47540856036825 32 5417154317423 5 47540856036825 32 54081338469396 107 Grassland Grassland_Bushed 1 Coarse 2002 1 5 47456561893842 32 63108751846197 5 47456561893842 32 631989711
88. ocation of the corresponding polygon in landuse shp In the final step we run the command oft combine masks bash Note that output file is automatically processed called combined mask img oft combine masks bash mask1 tif mask2 tif mask3 tif mask4 tif mask5 tif 0 User Manual 38 STEP 2 COMBINE MASKS USING RASTER AND SHAPE FILE Run oft combine masks bash Input mask1 tif mask2 tif mask3 tif mask4 tif mask5 tif and the additional shapefile clouds shp In the shapefile the values of the last column are picked up for processing output is automatically processed combined masks img textbfNOTE copy your combined mask img output from the first exercise as it will be overwritten running oft combine masks bash again combine_masks bash maskl tif mask2 tif mask3 tif mask4 tif mask5 tif clouds shp O the O defines nodata values to be 0 Verify in QGIS if combined masks img contains all mask values and if the additional polygon of clouds shp has the values 99 look into attribute table of clouds shp under the last column User Manual 39 Figure 5 Combined masks including the larger polygon from clouds shp User Manual 40 7 12 oft compare overlap bash To be tested NAME oft compare overlap bash This script compares overlapping areas of 2 images and produces between band correlations OFGT VERSION 1 25 4 SYNOPSIS oft compare overlap bash oft compare overlap bash lt imagel img gt lt
89. oft cuttile pl lt coord_list gt lt CRS file gt lt input_dir gt lt output_basename gt OPTIONS lt coord_ist gt is a text file containing the coordinates of the center of the tiles lt must arranged as id x y lt CRS file gt is a text file containing the projection definitions of the dataset in PROJ4 format lt input_dir gt is the directory containing the image Image must be in geotiff format extension must be TIF with capitals lt output_basename gt is the base name of the tiles that will be generated DESCRIPTION oft cuttile pl Cuts image tiles on the basis of a given list of locations 1 converts the point locations into the projection of the image 2 cuts a set of 20 km x 20 km tiles around the locations 3 converts the tiles to the coordinate system of the points 20 km x 20 km EXAMPLE For this exercise following tools are used oft cuttile pl gdal_translate cs2cs Open your working directory using User Manual 47 cd home 1 First we need to convert the imagery into TIF format You can use the gdal translate function to convert your input imagery from any gdal supported format to TIF using the option of GTiff input your_format output TIF gdal_translate of GTiff images landsat_tl tif results landsat_t1 TIF 2 In the next step we take a closer look at our additional input data coordinates txt and proj txt coordinates txt is a space separated text file coll ID c
90. ol2 X col3 Y coordinates gedit results coordinates txt Then copy paste the following list and save your file 1 767360 2415219 2 755310 2378377 3 781072 2379346 4 789936 2440150 proj txt must contain one line with the projection definition of the tiles coordinates and one line with the projection definition of the imagery Here it is UTM zone 20 for both with the following proj4 format init epsg 32620 proj utm zone 20 datum WGS84 units m no_defs ellps WGS84 Create the file gedit results proj txt Paste the projection definition twice as two separate lines Save proj txt init epsg 32620 proj utm zone 20 datum WGS84 units m no_defs ellps WGS84 init epsg 32620 proj utm zone 20 datum WGS84 units m no_defs ellps WGS84 User Manual 48 NB If you do not have it you can get the PROJ4 format of an image by using the function cs2cs cs2cs v init epsg 32620 If you don t know the EPSG code of your image use gdalinfo for your imagery gdalinfo landsat_t1 TIF 5 Now we run the actual script to create the tiles in the terminal Output Tiles cd results oft cuttile pl coordinates txt proj txt Tiles User Manual 49 Figure 7 The four tiles overlayed on base image displayed with differing band composition to base imagery User Manual 50 7 15 oft filter NAME oft filter moving window filters OFGT V
91. onize shp User Manual 59 7 19 oft sample within polys bash NAME oft sample within polys bash samples pixels within polygons and generates training data for k nn OFGT VERSION 1 25 4 SYNOPSIS oft sample within polys bash oft sample within polys bash lt image gt lt shapefile_basename gt lt shapefile_class_fieldname gt lt size_of_sample gt oft sample within polys bash lt image gt lt shapefile_basename gt lt shapefile_class_fieldname gt lt size_of_sample gt sample_only DESCRIPTION oft sample within polys bash samples pixel values from an image within areas determined by training data polygons shapefile Output is named sample_shapefile_basename txt Specifications Sample size nbr of pixels is given by the user The sample is distributed within classes in relation to class frequen cles Output is a text file to be used e g in k nn A histogram is also printed out sample size per class is shown in last column The image and the shapefile need to be in the same projection OPTIONS User Manual 60 sample_only It is possible to pick a new sample by running the script with option sample_only do not delete greyvals_shapefile_basename txt if you are going to re run At this point the image and the shapefile need to be in the same projection OTHERS Also look at oft knn EXAMPLE For this exercise following tools are used oft oft sample within polys bash You might hav
92. orking directory using cd home In a first step we need to prepare an image with administrative areas using oft shptif bash For exercise purpose we simply use landuse shp as an input for hypothetical admin areas Output anduse_raster tif oft shptif bash landuse shp landsat_tl tif landuse_raster tif landuse User Manual 26 Let s run oft admin mask bash now using anduse_raster tif Note the output is automatically called landsat_t1_adm tif oft admin mask bash landsat_t1 tif landuse_raster tif Verify in QGIS using a contrast enhancement if the pixel values of landsat_t1_adm tif are correctly processed User Manual 27 7 8 oft bb NAME oft bb is a a bounding box calculator t OFGT VERSION 1 25 4 SYNOPSIS oft bb oft bb um maskfile lt inputfile gt lt value gt DESCRIPTION oft bb studies every pixel of the input file and reports minimum and maximum pixels coordinates of pixels having the given value The minimum coordinates are 1 1 lt inputfile gt is an image file lt value gt is the value you want to query um use mask file It will consider only pixels which have mask value gt 0 EXERCISE For this exercise following tools are used oft bb gdal_translate Open your working directory using cd home Find the bounding box of the Forest tree cover file forestc tif with value 33 oft bb images forestc tif 33 It should provide the
93. owing tools are used oft avg Open your working directory using cd home User Manual 111 Usage of oft countpix pl using the input image forestc tif with pixel value of 33 ft countpix pl images forestc tif 33 oft countpix pl images forestc tif 33 a Usage of oft countpix pl using the input image landsat_t1 tif with value 50 counting all pixels below in band 4 oft countpix pl images landsat_tl tif 50 b 4 User Manual 112 7 39 oft crossvalidate NAME oft crossvalidate computes RMSE and bias estimates for k nn via leave one out cross validation OFGT VERSION 1 25 4 SYNOPSIS oft crossvalidate oft crossvalidate lt i datafile gt lt k val gt lt v col gt lt bands val gt oft crossvalidate lt i datafile gt lt k val gt lt v col gt lt bands val gt dw 1 2 3 x col y col id col norm mindist val maxdist val dem col thres lu col DESCRIPTION oft crossvalidate is a Program for carrying out a leave one out cross validation using nearest neighbour estimation You need to give at least the datafile number of neighbours k the column for your variable and nbr of bands Bands must be located after all other variables Program is terminated if the spatial neighbourhood restriction leaves too few less than k potential neighbours A possible order of data is id variable x coordinate y coordinate featurel featureN Values must be separate
94. program can still be used that way EXAMPLE oft stat i images input tif o results stats txt um images segments tif EXERCISE For this exercise following tools are used oft stat Open your working directory using cd home 1 Now we run oft stat with input images J andsat t1 tif output results stats txt oft stat i images landsat_tl tif o results stats txt 2 Print the output in terminal less results stats txt 1 10500000 48 742120 21 032891 19 848100 41 126436 50 192329 126 019212 21 810292 3 532883 2 776924 5 170575 6 554972 13 140675 2 275625 8 220984 Explanation of values for each column Coll ID Col2 Number of pixels Col3 Average value of band1 Col4 col9 Average value of band2 band7 Col10 col16 Standard deviation of bandl1 band7 3 Now we run oft stat with input images andsat _1 tif output results stats_mm txt and the option mm to produce also minimum and maximum values User Manua 135 oft stat i images landsat_tl tif o results stats_mm txt mm 4 Print the output in terminal less results stats txt 1 10500000 20 000000 1 000000 1 000000 8 000000 5 000000 112 000000 1 000000 255 000000 255 000000 208 000000 255 000000 255 000000 195 000000 255 000000 48 742120 21 032891 19 848100 41 126436 50 192329 126 019212 21 810292 3 532883 2 776924 5 170575 6 554972 13 140675 2 275625 8 220
95. r Thermal bash lt anchor gt lt fillerl gt lt filler2 gt lt filler_n gt DESCRIPTION The aim is to have one good image so called anchor with as few problematic areas as possible and then another which is from same season as close a date as possible and has clouds in different locations so called filler EXAMPLE For this exercise following tools are used multifiller Thermal bash Open your working directory using cd home Then run multifillerThermal bash anchor tif filler tif User Manual 71 7 24 oft calc NAME oft calc is a raster image calculator OFGT VERSION 1 25 4 SYNOPSIS oft calc oft calc lt input gt lt output gt oft calc lt input gt lt output gt um maskfile inv of format Z M Q C L X M oft calc lt input gt lt output gt ot Byte Int16 Ulnt16 UInt32 Int32 Float32 Float64 CInt16 CInt32 CFloat32 CFloat64 DESCRIPTION oft calc based on an input raster file oft calc creates an output raster file as result of a simple calculation between the original bands The bands used for the calculation must be all stacked in the input raster file After defining the first line following parameters will be asked 1 Number of output bands 2 Input postfix equations Band 1 The equation for output band 1 has to be specified The input bands are referred to with The implemented operators between input bands include addition subtraction division multiplic
96. r could produce a 3 band RGB image from a single band input file OPTIONS um lt maskfile gt User Manual 94 oi lt output_image gt maxval lt maximum pixel value in infile gt EXAMPLE For this exercise following tools are used oft reclass For this exercise we use a single band image images forestc tif and a segmented image images segments tif which you can also create yourself using oft seg Open your working directory using cd home 1 oft reclass First you need to create a text file called input_reclass txt that should look like this i Ae 25 255 2 0 100 0 3 125 100 16 400 112 5 0 225 0 6 225 0 0 99 200 0 200 Now we run oft reclass with Input image forestc tif and text input_reclass txt Output results reclassforestc img oft reclass oi results reclassforestc img txt input_reclass txt images forestc tif Then tool will ask you then for further information Input reclass file name txt input_reclass txt Nbr of out bands per input channel 3 Col of input value 1 Col of output value Col of output value Col of output value NODATA value 0 O Ne BW Nh Open QGIS and load your the original imagery image forestc tif Colour map Pseudocolour and the result results reclassforestc img Click with the dentify Features Tool over the the different classes and see how they have changed after the reclassification User Manual 95
97. ram txt head histogram txt Extraction of histogram txt output is all in one line 1 10500000 00 0000000000000000001000000 112114235 25 8 7 5 176 1576 12371 114959 758774 1773981 2035039 1918290 1222961 558651 332962 287434 320286 311067 217529 180595 138396 93221 57114 38722 32169 25924 18311 12510 9783 7020 5022 3874 3116 2294 1647 1193 848 632 408 284 185 163 134 72 73 41 16 11 8 1045710462202 L230R 222 TCOL LLITLOLISsSLL awAategewo2 LAO O 2 oft his with option hr for readability one line per band 2 1 Lets run a oft his with Input andsat_t1 tif Ouptut histogram_hr txt again the maximum input value to 255 oft his i landsat_tl tif o histogram hr txt hr head histogram hr txt Extraction of histogram_hr txt output is 7 lines for each band one which makes it more readable 1 10500000 100000000000000000000100000 011211423525 8 7 5 176 1576 12371 114959 758774 1773981 2035039 1918290 1222961 558651 332962 287434 320286 311067 217529 180595 138396 93221 57114 38722 32169 25924 18311 12510 9783 7020 5022 3874 3116 2294 1647 1193 848 632 408 284 185 163 134 72 73 41 16 11 8 104571046220 2 User Manual 124 L230 0 222000 OTE LOLAStUOteLoOecorz 121010000011000010010000100010 0000000200110000101000100000010 000000010000000001010000000000 0100000000000000000000000001000 000002 1 10500000 201103202323 0 3 3 2 26 646 8742 191086 2508329 4562947 718031 338584 429870 487321 3332
98. ranslate oft stack oft calc Open your working directory using cd home As oft gapfill only allows even number of bands first we need to adjust the number of bands of landsat_t1 tif 7 bands landsat_t2 tif 6 bands gdal_translate landsat_tl tif landsat_tl_6bands tif b 1 b 2 b 3 b 4 b 5 b 6 oft gapfill takes as input an image stack of the anchor andsat_t2 tif and the filler andsat_t1 tif oft stack o stack tif landsat_t2 tif landsat_tl_6Obands tif Gapfilling with mask of the scan line using a simple mask created with oft calc in two steps Rules User Manual 85 e if band 1 or band 6 are O put 1 fill e if band 7 or band 12 are 0 put 3 do nothing e else put 2 collect training data for regression models Step 1 oft calc stack tif tmp tif Step 2 10 60 0 gt 21 0 120 0 gt 23 Step 2 oft calc stack tif tmp tif Step 2 1 0 760 0 gt 21 0 120 0 gt 23 Now use oft gapfill to fill the areas indicated as 1 in the mask oft gapfill la 1 nolocal pm sd 2 um simple_mask tif stack tif filled_lal_sd2_simplemask tif Output automatically processed filled_la1_sd2_simplemask tif Figure 12 Original Landsat image User Manual 86 User Manual Figure 13 Landsat imager after gap fill 87 7 29 oft ndvi bash NAME oft ndvi bash computes ndvi images OFGT VERSION 1 25 4 SYNO
99. rcise the MODIS imagery vcf 2010 tif and the Landsat imagery clip landsat_t1 tif 2 Open your working directory using cd home OFGT Data 3 Reproject clip and resample the MODIS image resolution 230 m lat long to the projection extent and pixel size of the Landsat tile resolution 30m UTM 35 oft clip pl images landsat tif images vcf 2010 tif results vcf clip tif 4 Visualize the results in QGIS qgis images landsat_tl tif results vcf clip tif User Manual 80 7 27 oft combine images bash NAME oft combine images bash combines 2 images into one OFGT VERSION 1 25 4 SYNOPSIS oft combine images bash oft combine images bash lt a first image gt lt b second image gt lt m first image mask gt lt s second mask gt a First image Better image whose area is used whenever possible b Second image Image to be used elsewhere m First image mask 0 1 mask indicating bad areas on first image with 0 s Second mask 0 1 mask indicating bad areas on second image with 0 DESCRIPTION Can be used to merge same day Landsat images adjacent or two gapfill results stack Takes as input the images and their masks Masks for same day can be prepared with oft trim mask bash and for gapfill with oft prepare images for gapfill bash All ok areas are taken from image 1 and image 2 is used elsewhere Also produces a mask that indicates ok areas of the resulting combined image
100. rence org ref epsg User Manual 18 7 4 GExml2csv bash NAME GExml2csv bash converts xml files from Google Earth training data collection tool into one CSV file OFGT VERSION 1 25 4 SYNOPSIS GExml2csv bash DESCRIPTION GExml2csv bash converts single files originating from Google Earth GE training data collection tool into a combined CSV file NOTES The script is to be launched in a directory containing the target xml s EXAMPLE For this exercise following tools are used GExml2csv bash Open your working directory where you stored you xml files using cd home hen simply run following command GExml2csv bash User Manual 19 7 5 oft addattr py NAME oft addattr py adds one integer attribute in a shape file OFGT VERSION 1 25 4 SYNOPSIS oft addattr py oft addattr py lt shapefile gt lt JoinAttrName gt lt NewAttrName gt lt textfile gt DESCRIPTION oft addattr py adds one integer attribute in a shape file oft addattr py reads a space separated text file and uses the first and second columns to construct a lookup table which is used to add a new attribute in an existing shapefile Each time the value in the first column is found in the JoinAttributeName field of the shapefile the value in the second column is added in the field NewAttrName In case the corresponding value is not present in the textfile the NewAttrName value for that record becomes 9999 NOTES The values need to be
101. resolution of a refer ence image OFGT VERSION 1 25 4 SYNOPSIS oft shptif bash oft shptif bash lt shapefile gt lt raster_reference gt lt raster_output gt fieldname input files shapefile that is supposed to be rasterized reference raster image the shapefile will be rasterized to the same extent and resolution of this image OPTION fieldname the fieldname of the attribute of the shapefile that is supposed to be rasterized If no fieldname is specified every polygon will be assigned an arbitrary but unique ID EXAMPLE For this exercise following tools are used oft shptif bash Open your working directory using cd home OFGT data 1 We are going to rasterize the shapefile landuse shp with landsat_t1 tif as a reference image We are interested in the landuse specified in the shapefile so we choose landuse as field name 2 Run oft shptif bash oft shptif bash shapefile landuse shp images landsat_t1 tif results raster_landuse tif landuse User Manual 63 3 Open the output results raster_landuse tif in QGIS or use it for further calculations For all areas without landuse information in the shapefile value O will be recorded in the output image User Manual 64 7 21 oft sigshp bash NAME oft sigshp bash creates a signature file of an image based on train ing area polygons OFGT VERSION 1 25 4 SYNOPSIS oft sigshp bash oft sigshp bash lt image gt lt shapef
102. se the tool will ask for user input e If you do not want to use MinDist or MaxDist parameters or size weighting reply 0 when the parameter is asked e lf the given MinSize is 0 an image with unique labels for every pixel is produced e If a mask is given initial segments are read from the mask e To do a hierarchical segmentation the user should run the first iteration without a mask In the subsequent iterations the resulting output of the previous segmentation step should be fed to the process using um option e In case the input image is large and computing resources are low an alternative method can be used The initial segmentation User Manual 164 can be produced using oft cluster bash oft clump and the final removal of undesired small segments with oft seg NOTE A further tool oft segstat can then be used to extract segment level shape size bounding box edge pixels and spectral statistics averages and standard deviations to a text file EXAMPLE For this exercise following tools are used oft seg gdal_polygonize py 1 Open your working directory using cd home 2 Now we run oft seg to do the hierarchical segmentation with Input landsat_t1 tif Output landsat_t1_min50 tif oft seg landsat_tl tif landsat_tl tif_min50 tif The tool will ask you now further details which we will define in this exercise as followed Please give NODATA value 0 Min segment size 50 Min spec di
103. separate kml files from Google Earth GE into one CSV file This script performs conversion from a set of generic kml format polygons created in GE into one combined textfile NOTES All kml files need to be in one folder from where the script needs to be launched SEE ALSO The output textfile of genericGEkml2csv bash can then be converted into a shapefile using script genericCsv ToPolygon py EXAMPLE 1 Put all kml files into one folder 2 Launch genericGEkml2csv bash in that kml folder This creates a csv file output csv genericGEkml2csv bash no need to define input output 3 Look into your working directory and see if output csv was created Take a closer look at its first lines head output csv User Manual 17 3 Conversion of output csv into a shapefile Launch genericCsv ToPolygon py in the same folder with parameters as follows genericCsvToPolygon py output csv output shp The shp name can be as you wish e g settlements168063 shp 4 The shapefile is in geographic WGS84 but does not carry that in formation You can transform it e g into UTM 36S WGS84 with the following command Input output shp Output proj_output shp ogr2ogr s_srs EPSG 4326 t_srs EPSG 32736 proj_output shp output shp Where EPSG 4326 stands for WGS84 source system and EPSG 32736 for UTM 36S WGS84 target system You can select any target system and find the EPSG code see http spatialrefe
104. sing the grey value distribution obtained from the training data file EXAMPLE For this exercise following tools are used oft normalize bash Open your working directory using cd home Let s run a simple exercise using landsat_t1 tif as the only input oft normalize bash i landsat_tl tif Output landsat_t1_norm tif and stat_landsat_t1 txt Now we run it including the training data option va ues_for_nn oft normalize bash i landsat_tl tif f values_for_nn User Manual 155 7 50 oft prepare image for nn bash NAME oft prepare image for nn bash for preparing a Landsat image for nn analysis with oft nn OFGT VERSION 1 25 4 SYNOPSIS oft prepare image for nn bash oft prepare image for nn bash lt i image gt oft prepare image for nn bash lt i image gt b baseimage p projec tion s shapefile a attribute DESCRIPTION Re projects and shifts an image if needed Prepares a 0 1 mask of nodata in image all values j 0 are consid ered nodata Image Landsat image with 6 or 7 bands to be prepared for oft nn Baseimage Image already in correct grid meaning pixel size and pixel locations Target projection in EPSG e g EPSG 32736 Shapefile additional mask areas to be added to the base mask e g clouds If target projection is given also shapefile is re projected Attribute name of attribute field to be used in shapefile Field must contain 0 in regions to be mas
105. st btw segs 0 Max spec dist btw segs 0 Use size weighting 0 3 In the next step we create a shapefile where pixels of the same value with other words of the same segment combined into one polygon Input landsat_t1_min50 tif Output landsat_t1_min50 shp gdal_polygonize py landsat_tl_min50 tif f ESRl Shapefile landsat_t1_min50 shp 4 Open your file landsat_t1_min50 tif in QGIS and overlay it with landsat_t1_min50 shp Right click of the shapefile gt Properties gt Label gt tick display User Manual 165 label and under Field containing label chose DN Right click of the shapefile gt Properties gt Style gt Transparency eg 50 Now zoom in and will see something similar to the image displayed depending on the area you are zooming in where each polygon refers to one segment and the displayed number is the corresponding ID Note some segments have the same ID but they still belong to the same segment as they are connect through neighbouring corner pixels 5 The segmentation image andsat_t1_min50 tif can be used in a further step for oft segstat Figure 32 The segmentation image andsat_t1_min50 tif User Manual 166 PROJECTION 7 54 oft getproj bash NAME oft getproj bash fetches projection definition files for UTM zones OFGT VERSION 1 25 4 SYNOPSIS oft getproj bash DESCRIPTION oft getproj bash fetches projection definition files for UTM zones Downloads
106. t t t Phrrprrprrprrprrprrprrprr r eee or prrprrprrprrprrprrprror horsrrpr toos Pe ne Se ne ee ne ne eee eee ee Se ee nes hrrprr hrrprrprrprrprprrprrprror t eee hor rporprrprrprrprrprrprrrr po if trrprr r prrprrprrprrprrprrprrprrpr eee eee ee eee eee eee eee eee eee eee ees t t hrrprr hrrprrprr r rhrrprrprrprrprrpr prrprrpr rhrrprrprrprrprrprrprr lt proror o o hrrprrprrprrprprrprrrrrprrs prrprrprrproprrprrprrro prrs hrrprrprrprrprorprrprprrprr oo o QGIS in Output of oft compare overlap bash visualized Figure 6 44 User Manual 7 13 oft crop bash NAME oft crop bash crops a raster image to the extent of a certain pixel value OFGT VERSION 1 25 4 SYNOPSIS oft crop bash oft crop bash lt input img gt lt output img gt value all nodata value OPTION value all value is the value of the inputfile it should be cropped to all if image should be cropped to every unique pixel value output will be named accordingly nodata value for this value no cropping will be done if not provided it is assumed to be 0 only applicable for option all DESCRIPTION Oft crop bash crops a raster image
107. t bash automated change detection OFGT VERSION 1 25 4 SYNOPSIS oft chdet bash oft chdet bash lt input1 gt lt input2 gt lt output gt lt nodata_value gt threshold lt inputl gt Input raster 1 with extension lt input2 gt Input raster 2 with extension lt output gt A raster consisting of binary values 0 or 1 indicating pixels of likely change between the two dates Values of 1 indicate change Values of 0 indicate no change lt nodata_value gt Value indicating no data within the image threshold Default 0 99 Specifies the threshold value of the cumu lative frequency distribution of the resulting Chi square layer see Reference below above which pixels are identified as changed Higher threshold values indicate more stringent limits for detecting changes and thus produce less changed area than lower thresholds Threshold values must be specified as a proportion using 0 XX no tation DESCRIPTION This tool performs automated change detection between 2 input images The script uses the Iteratively Re weighted Multivariate Alteration Detection MAD algorithm Canty and Nielsen 2008 Input imagery must have the same format extent resolution num ber of bands and type of data User Manual 78 REFERENCE M J Canty and A A Nielsen 2008 Automatic radiometric nor malization of multitemporal satellite imagery with the iteratively re weighted MAD transformation RSE 112 3 1025 1036
108. the output ulx upper left x coordinate uly upper left y coordinate Irx lower right x coordinate Iry lower right y coordinate EXAMPLE For this exercise following tools are used oft getcorners bash Open your working directory using cd home OFGT data 1 Run the oft getcorners bash oft getcorners bash images landsat_tl tif User Manual 56 2 You should get the following output Not an OGR vector layer Using GDAL raster layer Output in order ulx uly 729285 000 2352885 000 Irx Iry 819285 000 2457885 000 User Manual 57 7 18 oft polygonize bash NAME oft polygonize bash a wrapper for gdal_polygonize OFGT VERSION 1 25 4 SYNOPSIS oft polygonize bash oft polygonize bash lt input img gt lt output shp gt EXAMPLE For this exercise following tools are used oft polygonize bash Open your working directory using cd home OFGT data 1 Let s run oft polygonize bash using the input image landsat_t1 tif to create the output oft polygonize shp oft polygonize bash landsat_t1 tif oft polygonize shp 2 Take a look at your shapefile in QGIS on go on propertiesof the shp gt Labels gt tick Display Labels set Field Containing Label to DN gt Press OK The DN of each polygon in oft polygonize shp should be the same as the pixel value of landsat_t1 tif for the same location User Manual 58 Figure 10 Zoomed view of oft polyg
109. this parameter 2 da do4allpixels use to built model to predict output value for every pixel of the anchor using the built models and the values of the Filler 3 sd sampling density sampling density used to build the LargeArea model Value two for example would force the algorithm to collect every other valid pixel within the scene to be used in building the model 4 ws WindowSize size of the neighbourhood from which the data for local model construction is collected NOTE The input image can be produced from 2 image stacks for in stance 2 Erdas imagine composites consisting of 7 bands The script stack2images bash produces the composite It can also be produced from HDF images that are stored in folders The script stack2images_hdf bash is for that purpose User Manual 84 The model may be very sensitive to outliers Therefore it is impor tant that the mask value 2 is present only in location where both Anchor and Filler have valid data IMPORTANT The stack and the mask must have been reprojected to the same geographical window and they do must have the same number of rows and cols EXAMPLE oft gapfill la 2 nolocal sd 5 ws 13 um mymask img myl4bandimage img filled img The program performs 2 passes over the image Pass1 collect the data to build the model Pass2 fill the gaps with Large Area models EXERCISE For this exercise following tools are used oft gapfill gdal_t
110. tion libgdal devel gdal gdal python prom gsl devel gsl progs e Click Apply to install them Download the OpenForisToolkit run installer wget http foris fao org static geospatialtoolkit releases OpenForisToolkit run Make the installer executable open a Terminal and enter the command chmod u x OpenForisToolkit run Install OpenForisToolkit enter the command su c OpenForisToolkit run Mac OS X Lion Download wget make it executable and copy it into the system open a Terminal and enter the command chmod a x wget sudo cp wget usr bin Download and install the latest version of the gsl framework and gdal complete from kyngchaos Download the OpenForisToolkit run installer wget http foris fao org static geospatialtoolkit releases OpenForisToolkit run Making the installer executable open a Terminal and enter the command chmod u x OpenForisToolkit run Amend the PATH environment for the installation enter the command Export PATH Library Frameworks GSL framework Programs PATH Install OpenForis Toolkit enter the command sudo OpenForisToolkit run User Manual 8 3 4 Windows Cygwin installation WARNING ADMINISTRATIVE PRIVILEGES ARE REQUIRED IN ORDER TO PER FORM THE INSTALLATIONS AND EVENTUALLY ALSO TO USE THE APPLICATION USERS WITH STANDARD PRIVILEGES MAY WANT TO CREATE A VIRTUAL MACHINE WITH VIRTUAL BO
111. to the extent of a certain pixel value This can be useful when for example one wants to produce a separate raster image for every district of a country Input image is a raster image with unique pixel values for each region of interest In the output image the value for the region of interest is kept All other pixels are set to 0 The user can choose to either e do the cropping for one single pixel value e do the cropping for all occurring pixel values besides the nodata value The nodata value can be specified with the nodatal option If not specified it is assumed to be 0 In this case User Manual 45 output files will carry the value they have been cropped to in their name EXAMPLE For this exercise following tools are used oft crop bash gdal_rasterize Open your working directory using cd home You will need for this exercise the file anduse shp digitized manu ally with QGIS Create a raster file that has the landuse class attribute of the landuse shp file gdal_rasterize a newcol landuse tr 30 30 shapefiles landuse shp results landuse tif Extract one particular class in that case the zone that has the label 2000 oft crop bash results landuse tif results lu_class tif 2000 46 User Manua 7 14 oft cuttile pl NAME oft cuttile pl Cuts image tiles on the basis of a given list of locations OFGT VERSION 1 25 4 SYNOPSIS oft cuttile pl
112. with 1 All material needs to be in same projection Works with 6 or 7 band images EXERCISE For this exercise following tools are used oft combine images bash gdal_translate trim User Manual 81 Open your working directory using cd home OFGT Data In a first step we need to adjust the nr of bands of landsat_t1 tif 7 bands to the nr of bands of our second image 6 bands gdal_translate landsat_tl tif landsat_tl_6bands tif b 1 b 2 b 3 b 4 b 5 b 6 Then we need to prepare our mask files for each landsat image using oft trim oft trim mask bash landsat_t2 tif oft trim mask bash landsat_tl tif Now we can run oft combine images bash The output is automati cally processed in this case it is called stack_landsat_t1_6bands_landsat_t2 tif oft combine images bash a landsat_tl_6bands tif b landsat_t2 tif n landsat_tl_mask tif s landsat_t2_mask tif User Manual 82 7 28 oft gapfill NAME oft gapfill regression based gap and cloud filler OFGT VERSION 1 25 4 SYNOPSIS oft gapfill oft gapfill lt um maskfile gt lt input gt lt output gt oft gapfill lt um maskfile gt lt input gt lt output gt la nbrLargeAreaWin dows nolocal smooth pm da sd sampling density ws WindowSize DESCRIPTION oft gapfill fills the gaps in an input image using locally built regres sion models The models can be built 1 separate
113. your own txt file consisting of three columns lt ID gt lt xX field gt lt Y field gt or e Generate it by using oft gengrid bash Open your working directory using cd home 3 In this exercise we use the txt file derived from oft gengrid bash called training txt This is how the first 10 rows look like User Manual 69 head training txt 4 NOTE that the projection is UTM South WGS84 zones In our case it is UTM Zone 20S 5 How to find out Before running oft gengrid bash check the projection of the input image landsat_t1 tif which is the base to calculate training txt using gdalinfo landsat_tl tif part of output PROJCS WGS 84 UTM zone 20S 5 After generating training txt run the command line for calculating your points to 100 x 100x meter squares creating an kml outputfile called Points2Squares_training kml PointsToSquares py training txt Points2Squares_training kml 20 1 2 3 20 refers to our UTM Zone nr 1 3 refer to the columns Mo Or impar Wola ral a sv 6 Load your result Points2Squares training kml e g in GoogleEarth 7 Check if the individual square is 100 x 100 meter User Manual 70 IMAGE MANIPULATION 7 23 multifillerThermal bash NAME multifillerT hermal bash is a script which utilizes several Landsat scenes to build a multi temporal image composite using the warmest pixel method OFGT VERSION 1 25 4 SYNOPSIS multifiller Thermal bash multifille

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