| [426] | 1 | # |
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| [468] | 2 | # Python Scripting for ArcGIS |
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| 3 | # by Dr Peter Bunting is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License - |
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| 4 | # See more at: |
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| 5 | # http://www.landmap.ac.uk/index.php/Learning-Materials/Python-Scripting/9.4-Calculate-NDVI-using-GDAL |
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| [426] | 6 | # |
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| [334] | 7 | |
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| 8 | import sys, os, struct |
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| 9 | |
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| 10 | import osgeo.gdal as gdal |
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| 11 | |
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| 12 | # Calculate and output NDVI from raster bands |
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| 13 | def ExtractNDVI(conf, inputs, outputs): |
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| 14 | |
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| 15 | # Open the input dataset |
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| 16 | gdal.FileFromMemBuffer('/vsimem//temp.tif', inputs["raster"]["value"]) |
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| 17 | dataset = gdal.Open( '/vsimem//temp.tif') |
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| 18 | if dataset is None: |
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| 19 | conf["lenv"]["message"]="The dataset could not be openned properly" |
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| 20 | return 4 |
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| 21 | |
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| 22 | # Create the output dataset |
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| 23 | driver = gdal.GetDriverByName( "GTiff" ) |
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| 24 | # Get the spatial information from the input file |
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| 25 | geoTransform=None |
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| 26 | geoProjection=None |
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| 27 | print >> sys.stderr,dir(dataset) |
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| 28 | try: |
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| 29 | geoTransform = dataset.GetGeoTransform() |
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| 30 | except: |
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| 31 | print >> sys.stderr, "Unable to load geotransform" |
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| 32 | try: |
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| 33 | geoProjection = dataset.GetProjection() |
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| 34 | except: |
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| 35 | print >> sys.stderr, "Unable to load projection" |
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| 36 | |
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| 37 | # Create an output file of the same size as the inputted |
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| 38 | # image but with only 1 output image band. |
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| 39 | newDataset = driver.Create("/vsimem//output"+conf["lenv"]["sid"], \ |
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| 40 | dataset.RasterXSize, dataset.RasterYSize,1, \ |
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| 41 | gdal.GDT_Float32) |
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| 42 | # Set spatial informations of the new image. |
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| 43 | if geoTransform: |
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| 44 | newDataset.SetGeoTransform(geoTransform) |
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| 45 | if geoProjection: |
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| 46 | newDataset.SetProjection(geoProjection) |
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| 47 | if newDataset is None: |
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| 48 | conf["lenv"]["message"]='Could not create output image' |
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| 49 | return 4 |
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| 50 | |
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| 51 | # Get the RED and NIR image bands of the image |
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| 52 | red_id=int(inputs["red"]["value"]) |
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| 53 | nir_id=int(inputs["nir"]["value"]) |
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| 54 | red_band = dataset.GetRasterBand(red_id) # RED BAND |
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| 55 | nir_band = dataset.GetRasterBand(nir_id) # NIR BAND |
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| 56 | |
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| 57 | # Loop through each line in turn. |
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| 58 | numLines = red_band.YSize |
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| 59 | for line in range(numLines): |
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| 60 | # Define variable for output line. |
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| 61 | outputLine = '' |
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| 62 | # Read in data for the current line from the |
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| 63 | # image band representing the red wavelength |
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| 64 | red_scanline = red_band.ReadRaster( 0, line, red_band.XSize, 1, \ |
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| 65 | red_band.XSize, 1, gdal.GDT_Float32 ) |
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| 66 | # Unpack the line of data to be read as floating point data |
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| 67 | red_tuple = struct.unpack('f' * red_band.XSize, red_scanline) |
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| 68 | |
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| 69 | # Read in data for the current line from the |
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| 70 | # image band representing the NIR wavelength |
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| 71 | nir_scanline = nir_band.ReadRaster( 0, line, nir_band.XSize, 1, \ |
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| 72 | nir_band.XSize, 1, gdal.GDT_Float32 ) |
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| 73 | # Unpack the line of data to be read as floating point data |
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| 74 | nir_tuple = struct.unpack('f' * nir_band.XSize, nir_scanline) |
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| 75 | |
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| 76 | # Loop through the columns within the image |
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| 77 | for i in range(len(red_tuple)): |
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| 78 | # Calculate the NDVI for the current pixel. |
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| 79 | ndvi_lower = (nir_tuple[i] + red_tuple[i]) |
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| 80 | ndvi_upper = (nir_tuple[i] - red_tuple[i]) |
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| 81 | ndvi = 0 |
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| 82 | # Becareful of zero divide |
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| 83 | if ndvi_lower == 0: |
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| 84 | ndvi = 0 |
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| 85 | else: |
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| 86 | ndvi = ndvi_upper/ndvi_lower |
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| 87 | # Add the current pixel to the output line |
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| 88 | outputLine = outputLine + struct.pack('f', ndvi) |
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| 89 | # Write the completed line to the output image |
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| 90 | newDataset.GetRasterBand(1).WriteRaster(0, line, red_band.XSize, 1, \ |
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| 91 | outputLine, buf_xsize=red_band.XSize, |
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| 92 | buf_ysize=1, buf_type=gdal.GDT_Float32) |
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| 93 | |
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| 94 | # Delete the output line following write |
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| 95 | del outputLine |
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| 96 | print >> sys.stderr,'NDVI Calculated and Outputted to File' |
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| 97 | print >> sys.stderr,dir(newDataset) |
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| 98 | newDataset.FlushCache() |
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| 99 | vsiFile=gdal.VSIFOpenL("/vsimem//output"+conf["lenv"]["sid"],"r") |
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| 100 | i=0 |
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| 101 | while gdal.VSIFSeekL(vsiFile,0,os.SEEK_END)>0: |
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| 102 | i+=1 |
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| 103 | fileSize=gdal.VSIFTellL(vsiFile) |
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| 104 | gdal.VSIFSeekL(vsiFile,0,os.SEEK_SET) |
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| 105 | outputs["raster"]["value"]=gdal.VSIFReadL(fileSize,1,vsiFile) |
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| 106 | gdal.Unlink("/vsimem//output"+conf["lenv"]["sid"]) |
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| 107 | return 3 |
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