Index: trunk/zoo-project/zoo-services/gdal/ndvi/cgi-env/ExtractNDVI.zcfg
===================================================================
--- trunk/zoo-project/zoo-services/gdal/ndvi/cgi-env/ExtractNDVI.zcfg	(revision 334)
+++ trunk/zoo-project/zoo-services/gdal/ndvi/cgi-env/ExtractNDVI.zcfg	(revision 334)
@@ -0,0 +1,57 @@
+[ExtractNDVI]
+ Title = Normalized Difference Vegetation Index. 
+ Abstract = Create raster file containing the Normalized Difference Vegetation Index. 
+ Profile = urn:ogc:wps:1.0.0:buffer
+ processVersion = 2
+ storeSupported = true
+ statusSupported = true
+ serviceProvider = ndvi
+ serviceType = Python
+ <MetaData>
+   title = Demo
+ </MetaData>
+ <DataInputs>
+  [raster]
+   Title = The raster file to be used
+   Abstract = URI to a raster file that contains the mentionned two bands.
+   minOccurs = 1
+   maxOccurs = 1
+   <ComplexData>
+    <Default>
+     mimeType = image/tiff
+    </Default>
+   </ComplexData>
+  [red]
+   Title = The red band number
+   Abstract = The RED band number to use.
+   minOccurs = 0
+   maxOccurs = 1
+   <LiteralData>
+    DataType = int
+    <Default>
+     value = 1
+    </Default>
+   </LiteralData>
+  [nir]
+   Title = The NIR band number
+   Abstract = The NIR band number to use.
+   minOccurs = 0
+   maxOccurs = 1
+   <LiteralData>
+    DataType = int
+    <Default>
+     value = 2
+    </Default>
+   </LiteralData>
+ </DataInputs>
+ <DataOutputs>
+  [raster]
+   Title = The resulting raster
+   Abstract = A single band raster containing the NDVI of the original raster using formula : (NIR - RED) / (NIR + RED) .
+   <ComplexData>
+    <Default>
+     mimeType = image/tiff
+     extension = tif
+    </Default>
+   </ComplexData>
+ </DataOutputs>  
Index: trunk/zoo-project/zoo-services/gdal/ndvi/cgi-env/ndvi.py
===================================================================
--- trunk/zoo-project/zoo-services/gdal/ndvi/cgi-env/ndvi.py	(revision 334)
+++ trunk/zoo-project/zoo-services/gdal/ndvi/cgi-env/ndvi.py	(revision 334)
@@ -0,0 +1,102 @@
+#! /usr/bin/env python
+
+import sys, os, struct
+
+import osgeo.gdal as gdal
+
+# Calculate and output NDVI from raster bands
+def ExtractNDVI(conf, inputs, outputs):
+    
+    # Open the input dataset
+    gdal.FileFromMemBuffer('/vsimem//temp.tif', inputs["raster"]["value"])
+    dataset = gdal.Open( '/vsimem//temp.tif')
+    if dataset is None:
+        conf["lenv"]["message"]="The dataset could not be openned properly"
+        return 4
+
+    # Create the output dataset
+    driver = gdal.GetDriverByName( "GTiff" )
+    # Get the spatial information from the input file
+    geoTransform=None
+    geoProjection=None
+    print >> sys.stderr,dir(dataset) 
+    try:
+        geoTransform = dataset.GetGeoTransform()
+    except:
+        print >> sys.stderr, "Unable to load geotransform"
+    try:
+        geoProjection = dataset.GetProjection()
+    except:
+        print >> sys.stderr, "Unable to load projection"
+
+    # Create an output file of the same size as the inputted 
+    # image but with only 1 output image band.
+    newDataset = driver.Create("/vsimem//output"+conf["lenv"]["sid"], \
+                               dataset.RasterXSize, dataset.RasterYSize,1, \
+                               gdal.GDT_Float32)
+    # Set spatial informations of the new image.
+    if geoTransform:
+        newDataset.SetGeoTransform(geoTransform)
+    if geoProjection:
+        newDataset.SetProjection(geoProjection)
+    if newDataset is None:
+        conf["lenv"]["message"]='Could not create output image'
+        return 4
+    
+    # Get the RED and NIR image bands of the image
+    red_id=int(inputs["red"]["value"])
+    nir_id=int(inputs["nir"]["value"])
+    red_band = dataset.GetRasterBand(red_id) # RED BAND
+    nir_band = dataset.GetRasterBand(nir_id) # NIR BAND
+
+    # Loop through each line in turn.
+    numLines = red_band.YSize
+    for line in range(numLines):
+        # Define variable for output line.
+        outputLine = ''
+        # Read in data for the current line from the 
+        # image band representing the red wavelength
+        red_scanline = red_band.ReadRaster( 0, line, red_band.XSize, 1, \
+                                          red_band.XSize, 1, gdal.GDT_Float32 )
+        # Unpack the line of data to be read as floating point data
+        red_tuple = struct.unpack('f' * red_band.XSize, red_scanline)
+            
+        # Read in data for the current line from the 
+        # image band representing the NIR wavelength
+        nir_scanline = nir_band.ReadRaster( 0, line, nir_band.XSize, 1, \
+                                          nir_band.XSize, 1, gdal.GDT_Float32 )
+        # Unpack the line of data to be read as floating point data
+        nir_tuple = struct.unpack('f' * nir_band.XSize, nir_scanline)
+
+        # Loop through the columns within the image
+        for i in range(len(red_tuple)):
+            # Calculate the NDVI for the current pixel.
+            ndvi_lower = (nir_tuple[i] + red_tuple[i])
+            ndvi_upper = (nir_tuple[i] - red_tuple[i])
+            ndvi = 0
+            # Becareful of zero divide 
+            if ndvi_lower == 0:
+                ndvi = 0
+            else:
+                ndvi = ndvi_upper/ndvi_lower
+            # Add the current pixel to the output line
+            outputLine = outputLine + struct.pack('f', ndvi)
+        # Write the completed line to the output image
+        newDataset.GetRasterBand(1).WriteRaster(0, line, red_band.XSize, 1, \
+                                         outputLine, buf_xsize=red_band.XSize, 
+                                         buf_ysize=1, buf_type=gdal.GDT_Float32)
+    
+        # Delete the output line following write
+        del outputLine
+    print >> sys.stderr,'NDVI Calculated and Outputted to File'
+    print >> sys.stderr,dir(newDataset)
+    newDataset.FlushCache()
+    vsiFile=gdal.VSIFOpenL("/vsimem//output"+conf["lenv"]["sid"],"r")
+    i=0
+    while gdal.VSIFSeekL(vsiFile,0,os.SEEK_END)>0:
+        i+=1
+    fileSize=gdal.VSIFTellL(vsiFile)
+    gdal.VSIFSeekL(vsiFile,0,os.SEEK_SET)
+    outputs["raster"]["value"]=gdal.VSIFReadL(fileSize,1,vsiFile)
+    gdal.Unlink("/vsimem//output"+conf["lenv"]["sid"])
+    return 3