Added further testing

city_metrix/layers/albedo.py

@@ -1,6 +1,6 @@
 import ee
 
-from .layer import Layer, get_image_collection
+from .layer import Layer, get_image_collection, set_bilinear_resampling
 
 class Albedo(Layer):
     """
@@ -115,7 +115,10 @@ def calc_s2_albedo(image):
         ## S2 MOSAIC AND ALBEDO
         dataset = get_masked_s2_collection(ee.Geometry.BBox(*bbox), self.start_date, self.end_date)
         s2_albedo = dataset.map(calc_s2_albedo)
-        albedo_mean = s2_albedo.reduce(ee.Reducer.mean())
+        albedo_mean = (s2_albedo
+                       .map(set_bilinear_resampling)
+                       .reduce(ee.Reducer.mean())
+                       )
 
         albedo_mean_ic = ee.ImageCollection(albedo_mean)
         data = get_image_collection(

city_metrix/layers/alos_dsm.py

@@ -1,6 +1,6 @@
 import ee
 
-from .layer import Layer, get_image_collection
+from .layer import Layer, get_image_collection, set_bilinear_resampling
 
 
 class AlosDSM(Layer):
@@ -18,6 +18,7 @@ def get_data(self, bbox):
 
         alos_dsm_ic = ee.ImageCollection(alos_dsm
                                          .filterBounds(ee.Geometry.BBox(*bbox))
+                                         .map(set_bilinear_resampling)
                                          .select('DSM')
                                          .mean()
                                          )

city_metrix/layers/land_surface_temperature.py

@@ -1,6 +1,6 @@
 import ee
 
-from .layer import Layer, get_image_collection
+from .layer import Layer, get_image_collection, set_bilinear_resampling
 
 class LandSurfaceTemperature(Layer):
     """
@@ -35,6 +35,7 @@ def apply_scale_factors(image):
                  .filterBounds(ee.Geometry.BBox(*bbox))
                  .map(cloud_mask)
                  .map(apply_scale_factors)
+                 .map(set_bilinear_resampling)
                  .reduce(ee.Reducer.mean())
                  )
 

city_metrix/layers/layer.py

@@ -323,6 +323,20 @@ def get_stats_funcs(stats_func):
         return [stats_func]
 
 
+def set_bilinear_resampling(data):
+    if isinstance(data, ee.ImageCollection):
+        resampled = data.map(_assign_bilinear_interpolation)
+    else:
+        resampled = data.resample('bilinear')
+
+    return resampled
+
+
+def _assign_bilinear_interpolation(dataset):
+    data = dataset.resample('bilinear')
+    return data
+
+
 def get_image_collection(
         image_collection: ImageCollection,
         bbox: Tuple[float],

city_metrix/layers/nasa_dem.py

@@ -1,6 +1,6 @@
 import ee
 
-from .layer import Layer, get_image_collection
+from .layer import Layer, get_image_collection, set_bilinear_resampling
 
 
 class NasaDEM(Layer):
@@ -18,6 +18,7 @@ def get_data(self, bbox):
 
         nasa_dem_elev = (ee.ImageCollection(nasa_dem)
                          .filterBounds(ee.Geometry.BBox(*bbox))
+                         .map(set_bilinear_resampling)
                          .select('elevation')
                          .mean()
                          )

city_metrix/layers/ndvi_sentinel2_gee.py

@@ -1,6 +1,6 @@
 import ee
 
-from .layer import Layer, get_image_collection
+from .layer import Layer, get_image_collection, set_bilinear_resampling
 
 class NdviSentinel2(Layer):
     """"
@@ -33,8 +33,9 @@ def calculate_ndvi(image):
             return image.addBands(ndvi)
 
         s2 = ee.ImageCollection("COPERNICUS/S2_HARMONIZED")
+        s2_resampled = set_bilinear_resampling(s2)
 
-        ndvi = (s2
+        ndvi = (s2_resampled
                 .filterBounds(ee.Geometry.BBox(*bbox))
                 .filterDate(start_date, end_date)
                 .map(calculate_ndvi)

city_metrix/layers/tree_canopy_height.py

@@ -1,6 +1,6 @@
 import ee
 
-from .layer import Layer, get_image_collection
+from .layer import Layer, get_image_collection, set_bilinear_resampling
 
 class TreeCanopyHeight(Layer):
     """
@@ -20,6 +20,7 @@ def get_data(self, bbox):
 
         # aggregate time series into a single image
         canopy_ht_img = (canopy_ht
+                         .map(set_bilinear_resampling)
                          .reduce(ee.Reducer.mean())
                          .rename("cover_code")
                          )

city_metrix/layers/tree_cover.py

@@ -1,6 +1,6 @@
 import ee
 
-from .layer import Layer, get_image_collection
+from .layer import Layer, get_image_collection, set_bilinear_resampling
 
 class TreeCover(Layer):
     """
@@ -25,6 +25,7 @@ def get_data(self, bbox):
 
         merged_ttc = tropics.merge(non_tropics)
         ttc_image = (merged_ttc
+                     .map(set_bilinear_resampling)
                      .reduce(ee.Reducer.mean())
                      .rename('ttc')
                      )

city_metrix/layers/world_pop.py

@@ -1,6 +1,6 @@
 import ee
 
-from .layer import Layer, get_image_collection
+from .layer import Layer, get_image_collection, set_bilinear_resampling
 
 
 class WorldPop(Layer):
@@ -29,6 +29,7 @@ def get_data(self, bbox):
                 dataset
                 .filterBounds(ee.Geometry.BBox(*bbox))
                 .filter(ee.Filter.inList('year', [self.year]))
+                .map(set_bilinear_resampling)
                 .select('population')
                 .mean()
             )
@@ -53,6 +54,7 @@ def get_data(self, bbox):
 
             world_pop_group_ic = ee.ImageCollection(
                 world_pop_age_sex_year
+                .map(set_bilinear_resampling)
                 .reduce(ee.Reducer.sum())
                 .rename('sum_age_sex_group')
             )