Snippets

Daniel Clewley Calculate NDVI from RAT

Updated by Daniel Clewley
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File calc_ndvi_ratapplier.py Modified

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     ndvi = (nir - red) / (nir + red)
 
     # Save to 'NDVI' column (will create if doesn't exist)
-    outputs.outrat.NDVI = ndvi
+    setattr(outputs.outrat,"NDVI", ndvi)
 
 if __name__ == "__main__":
Created by Daniel Clewley
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File calc_ndvi_rat.py Added

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+#!/usr/bin/env python
+"""
+Calculate NDVI from RAT using RIOS rat
+module.
+
+Dan Clewley
+
+https://spectraldifferences.wordpress.com/
+
+"""
+
+from osgeo import gdal
+from rios import rat
+
+# Open RAT dataset
+rat_dataset = gdal.Open("clumps.kea", gdal.GA_Update)
+
+# Get columns with average red and NIR for each object
+red = rat.readColumn(rat_dataset, "RedAvg")
+nir = rat.readColumn(rat_dataset, "NIR1Avg")
+
+ndvi = (nir - red) / (nir + red)
+
+# Write out column
+rat.writeColumn(rat_dataset, "NDVI", ndvi)
+
+# Close RAT dataset
+rat_dataset = None

File calc_ndvi_ratapplier.py Added

  • Ignore whitespace
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+#!/usr/bin/env python
+"""
+Calculate NDVI from RAT using RIOS ratapplier
+module.
+
+Dan Clewley
+
+https://spectraldifferences.wordpress.com/
+
+"""
+from rios import ratapplier
+
+def _ratapplier_calc_ndvi(info, inputs, outputs):
+    """
+    Calculate NDVI from RAT.
+
+    Called by ratapplier
+    """
+
+    # Get columns with average red and NIR for each object
+    # within block
+    red = getattr(inputs.inrat, "RedAvg")
+    nir = getattr(inputs.inrat, "NIR1Avg")
+
+    # Calculate NDVI
+    ndvi = (nir - red) / (nir + red)
+
+    # Save to 'NDVI' column (will create if doesn't exist)
+    outputs.outrat.NDVI = ndvi
+
+if __name__ == "__main__":
+
+    # Set up rat applier for input / output
+    in_rats = ratapplier.RatAssociations()
+    out_rats = ratapplier.RatAssociations()
+
+    # Pass in clumps file
+    # Same file is used for input and output to write
+    # to existing RAT
+    in_rats.inrat = ratapplier.RatHandle("clumps.kea")
+    out_rats.outrat = ratapplier.RatHandle("clumps.kea")
+
+    # Apply function to all rows in chunks
+    ratapplier.apply(_ratapplier_calc_ndvi, in_rats, out_rats)
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