Merge branch 'main' into CIF-293-Set-tile-size-in-meters-for-fishnet-…

…functions

city_metrix/layers/__init__.py

@@ -21,3 +21,7 @@
 from .nasa_dem import NasaDEM
 from .era_5_hottest_day import Era5HottestDay
 from .impervious_surface import ImperviousSurface
+from.glad_lulc import LandCoverGlad
+from.glad_lulc import LandCoverSimplifiedGlad
+from.glad_lulc import LandCoverHabitatGlad
+from.glad_lulc import LandCoverHabitatChangeGlad

city_metrix/layers/era_5_hottest_day.py

@@ -96,12 +96,11 @@ def hourly_mean_temperature(image):
                 },
                 f'download_{i}.nc')
 
-            dataarray = xr.open_dataset(f'download_{i}.nc')
-
-            # Subset times for the day
-            times = [valid_time.astype('datetime64[s]').astype(datetime).replace(tzinfo=pytz.UTC) for valid_time in dataarray['valid_time'].values]
-            indices = [i for i, value in enumerate(times) if value in utc_times]
-            subset_dataarray = dataarray.isel(valid_time=indices)
+            with xr.open_dataset(f'download_{i}.nc') as dataarray:
+                # Subset times for the day
+                times = [valid_time.astype('datetime64[s]').astype(datetime).replace(tzinfo=pytz.UTC) for valid_time in dataarray['valid_time'].values]
+                indices = [i for i, value in enumerate(times) if value in utc_times]
+                subset_dataarray = dataarray.isel(valid_time=indices).load()
 
             dataarray_list.append(subset_dataarray)
 

city_metrix/layers/glad_lulc.py

@@ -0,0 +1,126 @@
+import xarray as xr
+import ee
+
+from .layer import Layer, get_utm_zone_epsg, get_image_collection
+
+
+class LandCoverGlad(Layer):
+    """
+    Attributes:
+        year: year used for data retrieval
+        spatial_resolution: raster resolution in meters (see https://github.com/stac-extensions/raster)
+    """
+
+    def __init__(self, year=2020, spatial_resolution=30, **kwargs):
+        super().__init__(**kwargs)
+        self.year = year
+        self.spatial_resolution = spatial_resolution
+
+    def get_data(self, bbox):
+        data = get_image_collection(
+            ee.ImageCollection(ee.Image(f'projects/glad/GLCLU2020/LCLUC_{self.year}')),
+            bbox,
+            self.spatial_resolution,
+            "GLAD Land Cover"
+        ).b1
+
+        return data
+
+
+class LandCoverSimplifiedGlad(Layer):
+    """
+    Attributes:
+        year: year used for data retrieval
+        spatial_resolution: raster resolution in meters (see https://github.com/stac-extensions/raster)
+    """
+
+    def __init__(self, year=2020, spatial_resolution=30, **kwargs):
+        super().__init__(**kwargs)
+        self.year = year
+        self.spatial_resolution = spatial_resolution
+
+    def get_data(self, bbox):
+        glad = LandCoverGlad(year=self.year, spatial_resolution=self.spatial_resolution).get_data(bbox)
+        # Copy the original data
+        data = glad.copy(deep=True)
+
+        # Assign values based on ranges and conditions
+        data = data.where(glad != 0, 0)  # If glad == 0, assign 0
+        # If glad between 1 and 24, assign 1
+        data = data.where((glad < 1) | (glad > 24), 1)
+        # If glad between 25 and 41, assign 2
+        data = data.where((glad < 25) | (glad > 41), 2)
+        # If glad between 42 and 48, assign 3
+        data = data.where((glad < 42) | (glad > 48), 3)
+        # If glad between 100 and 124, assign 4
+        data = data.where((glad < 100) | (glad > 124), 4)
+        # If glad between 125 and 148, assign 5
+        data = data.where((glad < 125) | (glad > 148), 5)
+        # If glad between 200 and 207, assign 6
+        data = data.where((glad < 200) | (glad > 207), 6)
+        # data = data.where(glad != 254, 6)  # Assign 6 if glad == 254
+        data = data.where(glad != 241, 7)  # If glad == 241, assign 7
+        data = data.where(glad != 244, 8)  # If glad == 244, assign 8
+        data = data.where(glad != 250, 9)  # If glad == 250, assign 9
+        data = data.where(glad != 255, 10)  # If glad == 255, assign 10
+
+        return data
+
+
+class LandCoverHabitatGlad(Layer):
+    """
+    Attributes:
+        year: year used for data retrieval
+        spatial_resolution: raster resolution in meters (see https://github.com/stac-extensions/raster)
+    """
+
+    def __init__(self, year=2020, spatial_resolution=30, **kwargs):
+        super().__init__(**kwargs)
+        self.year = year
+        self.spatial_resolution = spatial_resolution
+
+    def get_data(self, bbox):
+        simplified_glad = LandCoverSimplifiedGlad(year=self.year, spatial_resolution=self.spatial_resolution).get_data(bbox)
+        # Copy the original data
+        data = simplified_glad.copy(deep=True)
+
+        # Apply the conditions individually to avoid overwriting
+        data = data.where(simplified_glad != 0, 0)  # Where glad == 0, set to 0
+        # Where glad is between 1 and 6, set to 1
+        data = data.where((simplified_glad < 1) | (simplified_glad > 6), 1)
+        data = data.where(simplified_glad < 7, 0)  # Where glad >= 7, set to 0
+
+        return data
+
+
+class LandCoverHabitatChangeGlad(Layer):
+    """
+    Attributes:
+        start_year: baseline year for habitat change
+        end_year: target year for habitat change
+        spatial_resolution: raster resolution in meters (see https://github.com/stac-extensions/raster)
+    """
+
+    def __init__(self, start_year=2000, end_year=2020, spatial_resolution=30, **kwargs):
+        super().__init__(**kwargs)
+        self.start_year = start_year
+        self.end_year = end_year
+        self.spatial_resolution = spatial_resolution
+
+    def get_data(self, bbox):
+        habitat_glad_start = LandCoverHabitatGlad(year=self.start_year, spatial_resolution=self.spatial_resolution).get_data(bbox)
+        habitat_glad_end = LandCoverHabitatGlad(year=self.end_year, spatial_resolution=self.spatial_resolution).get_data(bbox)
+
+        # Class 01: Became habitat between start year and end year
+        class_01 = ((habitat_glad_start == 0) & (habitat_glad_end == 1))
+        # Class 10: Became non-habitat between start year and end year
+        class_10 = ((habitat_glad_start == 1) & (habitat_glad_end == 0))
+
+        # Initialize the habitat change DataArray with zeros
+        habitatchange = xr.full_like(habitat_glad_start, 0)
+        # Set values 1 for class_01 (became habitat between start year and end year)
+        habitatchange = habitatchange.where(~class_01, other=1)
+        # Set values 10 for class_10 (became non-habitat between start year and end year)
+        habitatchange = habitatchange.where(~class_10, other=10)
+
+        return habitatchange

tests/test_layers.py

@@ -10,6 +10,10 @@
     EsaWorldCoverClass,
     HighLandSurfaceTemperature,
     ImperviousSurface,
+    LandCoverGlad,
+    LandCoverHabitatGlad,
+    LandCoverHabitatChangeGlad,
+    LandCoverSimplifiedGlad,
     LandsatCollection2,
     LandSurfaceTemperature,
     NasaDEM,
@@ -66,6 +70,22 @@ def test_impervious_surface():
     data = ImperviousSurface().get_data(BBOX)
     assert np.size(data) > 0
 
+def test_land_cover_glad():
+    data = LandCoverGlad().get_data(BBOX)
+    assert np.size(data) > 0
+
+def test_land_cover_habitat_glad():
+    data = LandCoverHabitatGlad().get_data(BBOX)
+    assert np.size(data) > 0
+
+def test_land_cover_habitat_change():
+    data = LandCoverHabitatChangeGlad().get_data(BBOX)
+    assert np.size(data) > 0
+
+def test_land_cover_simplified_glad():
+    data = LandCoverSimplifiedGlad().get_data(BBOX)
+    assert np.size(data) > 0
+
 def test_land_surface_temperature():
     data = LandSurfaceTemperature().get_data(BBOX)
     assert np.size(data) > 0