Create impervious_surface.py

city_metrix/layers/impervious_surface.py

@@ -0,0 +1,23 @@
+from dask.diagnostics import ProgressBar
+import xarray as xr
+import xee
+import ee
+
+from .layer import Layer, get_utm_zone_epsg, get_image_collection
+
+
+class ImperviousSurface(Layer):
+    def __init__(self, **kwargs):
+        super().__init__(**kwargs)
+
+    def get_data(self, bbox):
+        # load impervious_surface
+        dataset = ee.ImageCollection(ee.Image("Tsinghua/FROM-GLC/GAIA/v10").gt(0))  # change_year_index is zero if permeable as of 2018
+        imperv_surf = ee.ImageCollection(dataset
+                     .filterBounds(ee.Geometry.BBox(*bbox))
+                     .select('change_year_index')
+                     .sum()
+                     )
+
+        data = get_image_collection(imperv_surf, bbox, 100, "imperv surf")
+        return data.change_year_index

tests/test_layers.py

@@ -8,6 +8,7 @@
     EsaWorldCover,
     EsaWorldCoverClass,
     HighLandSurfaceTemperature,
+	ImperviousSurface,
     LandsatCollection2,
     LandSurfaceTemperature,
     NasaDEM,
@@ -77,6 +78,9 @@ def test_high_land_surface_temperature():
     data = HighLandSurfaceTemperature().get_data(BBOX_BRAZIL_LAURO_DE_FREITAS_1)
     assert data.any()
 
+def test_impervious_surface():
+    data = ImperviousSurface().get_data(BBOX_BRAZIL_LAURO_DE_FREITAS_1)
+	assert data.any()
 
 def test_land_surface_temperature():
     mean_lst = LandSurfaceTemperature().get_data(BBOX_BRAZIL_LAURO_DE_FREITAS_1).mean()