Added Sentinel-1 filtering options and improved UI

PyGEE_SWToolbox.ipynb

@@ -36,13 +36,14 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "documentary-patch",
-   "metadata": {},
+   "metadata": {
+    "scrolled": false
+   },
    "outputs": [],
    "source": [
-    "import PyGEE_SWToolbox\n",
+    "from PyGEE_SWToolbox import Toolbox\n",
     "\n",
-    "toolbox = PyGEE_SWToolbox.Toolbox()\n",
-    "toolbox"
+    "Toolbox()"
    ]
   }
  ],

PyGEE_SWToolbox.py

@@ -78,8 +78,20 @@ def __init__(self):
 
         self.Platform_dropdown = ipw.Dropdown(options = Platform_options, value = None,
                                            layout=Layout(width='150px', margin='5px 0 0 5px'))
-
+
+        filtering_Label = ipw.Label('Speckle filter:', layout=Layout(margin='5px 0 0 5px'))
+
+        filtering_options = ['Refined-Lee', 'Perona-Malik', 'P-median', 'Lee Sigma', 'Gamma MAP','Boxcar Convolution']
+
+
+        self.filter_dropdown = ipw.Dropdown(options = filtering_options, value = 'Gamma MAP',
+                                           layout=Layout(width='150px', margin='5px 0 0 15px'))
+
+        self.filter_dropdown.disabled = True
+
         PlatformType = HBox([dataset_Label, self.Platform_dropdown])
+        FilterType = HBox([filtering_Label, self.filter_dropdown])
+
 
         # Study period definition
         #************************************************************************************************
@@ -108,7 +120,7 @@ def __init__(self):
         self.cloud_threshold = ipw.IntSlider(description = 'Cloud Threshold:', orientation = 'horizontal',
                                          value = 50, step = 5, style = style)
 
-        imageParameters = VBox([dataset_description, PlatformType, datePickers, self.cloud_threshold], 
+        imageParameters = VBox([dataset_description, PlatformType, FilterType, datePickers, self.cloud_threshold], 
                            layout=Layout(width='305px', border='solid 2px black'))
 
 
@@ -361,15 +373,15 @@ def platform_index_change(change):
                     self.threshold_value.disabled = False
                     self.water_indices.options = ['NDWI','MNDWI','DSWE','AWEInsh', 'AWEIsh']
                     self.threshold_dropdown.options = ['Simple','Otsu']
-
+                    self.filter_dropdown.disabled = True
                 elif self.Platform_dropdown.value == 'Sentinel-1':
                     visParams = {'min': -25,'max': 0}
                     self.cloud_threshold.disabled = True
                     self.water_indices.disabled = True
                     self.index_color.disabled = False
                     self.threshold_value.disabled = True
                     self.threshold_dropdown.options = ['Otsu']
-
+                    self.filter_dropdown.disabled = False
                 elif self.Platform_dropdown.value == 'Sentinel-2':
                     visParams = {'bands': ['red', 'green', 'blue'],
                       'min': 0.0,
@@ -380,7 +392,7 @@ def platform_index_change(change):
                     self.threshold_value.disabled = False
                     self.water_indices.options = ['NDWI','MNDWI','AWEInsh', 'AWEIsh']
                     self.threshold_dropdown.options = ['Simple','Otsu']
-
+                    self.filter_dropdown.disabled = True
                 elif self.Platform_dropdown.value == 'USDA NAIP':
                     visParams = {'bands': ['R', 'G','B'],
                                 'min': 0.0,
@@ -390,6 +402,7 @@ def platform_index_change(change):
                     self.index_color.disabled = False
                     self.water_indices.options = ['NDWI']
                     self.threshold_dropdown.options = ['Simple','Otsu']
+                    self.filter_dropdown.disabled = True
             except Exception as e:
                      print(e)
 
@@ -602,6 +615,7 @@ def process_images(self, b):
 
                 # get widget values
                 imageType = self.Platform_dropdown.value
+                filterType = self.filter_dropdown.value
                 StartDate = ee.Date.fromYMD(self.start_date.value.year,self.start_date.value.month,self.start_date.value.day)
                 EndDate = ee.Date.fromYMD(self.end_date.value.year,self.end_date.value.month,self.end_date.value.day)
 
@@ -620,8 +634,24 @@ def filtr(img):
                 elif imageType == 'Sentinel-1':
                     Collection_before = load_Sentinel1(site, StartDate, EndDate)
                     # apply speckle filter algorithm or smoothing
-                    filtered_Collection = Collection_before.map(hf.perona_malik)
-    #                 filtered_Collection = Collection_before.map(filtr)
+                    if filterType == 'Gamma MAP':
+                        corrected_Collection = Collection_before.map(slope_correction)
+                        filtered_Collection = corrected_Collection.map(hf.gamma_map)
+                    elif filterType == 'Refined-Lee':
+                        corrected_Collection = Collection_before.map(slope_correction)
+                        filtered_Collection = corrected_Collection.map(hf.refined_lee)
+                    elif filterType == 'Perona-Malik':
+                        corrected_Collection = Collection_before.map(slope_correction)
+                        filtered_Collection = corrected_Collection.map(hf.perona_malik)
+                    elif filterType == 'P-median':
+                        corrected_Collection = Collection_before.map(slope_correction)
+                        filtered_Collection = corrected_Collection.map(hf.p_median)
+                    elif filterType == 'Boxcar Convolution':
+                        corrected_Collection = Collection_before.map(slope_correction)
+                        filtered_Collection = corrected_Collection.map(filtr)
+                    elif filterType == 'Lee Sigma':
+#                         corrected_Collection = Collection_before.map(ut.slope_correction) # slope correction before lee_sigma fails
+                        filtered_Collection = Collection_before.map(hf.lee_sigma)
                 elif imageType == 'USDA NAIP':
                     filtered_Collection = load_NAIP(site, StartDate, EndDate)
 

Utilities.py

@@ -4,7 +4,7 @@
 from geetools import tools, cloud_mask
 import geemap
 import hydrafloods as hf
-from hydrafloods import geeutils
+from hydrafloods import geeutils, corrections
 
 def DSWE(imgCollection, DEM, aoi=None):
 
@@ -265,17 +265,23 @@ def load_Sentinel1(site, StartDate, EndDate):
     returns:
         Image collection of Sentinel-1 images
     """
-	
+
     filtered_col = ee.ImageCollection('COPERNICUS/S1_GRD')\
         .filterDate(StartDate,EndDate)\
         .filter(ee.Filter.eq('instrumentMode', 'IW'))\
         .filterMetadata('transmitterReceiverPolarisation', 'equals',['VV','VH'])\
+        .filter(ee.Filter.eq('orbitProperties_pass', 'ASCENDING'))\
         .filterMetadata('resolution_meters', 'equals', 10)\
         .filterBounds(site)\
         .sort('system:time_start')
-
     return filtered_col
 
+def slope_correction(img):
+#     orig = img
+    elev = ee.Image("MERIT/DEM/v1_0_3").select("dem")
+    corrected_image = corrections.slope_correction(img,elevation=elev)
+    return corrected_image.copyProperties(img, img.propertyNames())
+
 def load_Sentinel2(aoi, StartDate, EndDate, cloud_thresh):
     """
     Function to retrieve and filter Sentinel-2 images