Merge pull request #23 from Open-ET/water-ndvi-nodata

Setting negative and low reflectance NDVI values to 0

openet/sims/collection.py

@@ -664,7 +664,6 @@ def aggregate_image(agg_start_date, agg_end_date, date_format):
                 ndvi_img = (
                     daily_coll.filterDate(agg_start_date, agg_end_date)
                     .select(['ndvi']).mean().float()
-
                 )
                 image_list.append(ndvi_img)
             if ('scene_count' in variables) or ('count' in variables):

openet/sims/image.py

@@ -491,4 +491,27 @@ def _ndvi(landsat_image):
         ee.Image
 
         """
-        return landsat_image.normalizedDifference(['nir', 'red']).rename(['ndvi'])
+
+        # Force the input values to be at greater than or equal to zero
+        #   since C02 surface reflectance values can be negative
+        #   but the normalizedDifference function will return nodata
+        ndvi = (
+            landsat_image.select(['nir', 'red'])
+            .max(0)
+            .normalizedDifference(['nir', 'red'])
+            .rename(['ndvi'])
+        )
+
+        # Assume that low reflectance values are unreliable for computing NDVI
+        # If both reflectance values are below the minimum, set the output to 0
+        # If either of the reflectance values was negative, set the output to 0
+        # The 0.01 threshold was chosen arbitrarily and may need to be adjusted
+        nir = landsat_image.select(['nir'])
+        red = landsat_image.select(['red'])
+        ndvi = ndvi.where(nir.lt(0.01).And(red.lt(0.01)), 0)
+        #ndvi = ndvi.where(nir.lt(0).Or(red.lt(0)), 0)
+        #ndvi = ndvi.where(nir.lte(0).And(red.lte(0.01)), 0)
+        #ndvi = ndvi.where(nir.lte(0.01).And(red.lte(0)), 0)
+        return ndvi
+
+        # return landsat_image.normalizedDifference(['nir', 'red']).rename(['ndvi'])

openet/sims/tests/test_c_image.py

@@ -141,6 +141,17 @@ def test_Image_init_date_properties():
         [0.2, 0.8, 0.6],
         [0.1, 17.0 / 30, 0.7],
         [0.1, 0.9, 0.8],
+        # First check that negative values are not masked
+        [-0.01, 0.1, 1.0],
+        [0.1, -0.01, -1.0],
+        # Check that low reflectance values are set to 0
+        [-0.1, -0.1, 0.0],
+        [0.0, 0.0, 0.0],
+        [0.009, 0.009, 0.0],
+        [0.009, -0.01, 0.0],
+        [-0.01, 0.009, 0.0],
+        # Don't adjust NDVI if only one reflectance value is low
+        [0.005, 0.1, 0.9047619104385376],
     ]
 )
 def test_Image_static_ndvi_calculation(red, nir, expected, tol=0.000001):

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "openet-sims"
-version = "0.2.5"
+version = "0.2.6"
 authors = [
     { name = "Alberto Guzman", email = "[email protected]" },
 ]