Add spatial join examples

Join/inner_joins.py

@@ -0,0 +1,35 @@
+import ee 
+from ee_plugin import Map 
+
+# Make a date filter to get images in this date range.
+dateFilter = ee.Filter.date('2014-01-01', '2014-02-01')
+
+# Load a MODIS collection with EVI data.
+mcd43a4 = ee.ImageCollection('MODIS/MCD43A4_006_EVI') \
+    .filter(dateFilter)
+
+# Load a MODIS collection with quality data.
+mcd43a2 = ee.ImageCollection('MODIS/006/MCD43A2') \
+    .filter(dateFilter)
+
+# Define an inner join.
+innerJoin = ee.Join.inner()
+
+# Specify an equals filter for image timestamps.
+filterTimeEq = ee.Filter.equals(**{
+  'leftField': 'system:time_start',
+  'rightField': 'system:time_start'
+})
+
+# Apply the join.
+innerJoinedMODIS = innerJoin.apply(mcd43a4, mcd43a2, filterTimeEq)
+
+# Display the join result: a FeatureCollection.
+print('Inner join output:', innerJoinedMODIS)
+
+# Map a function to merge the results in the output FeatureCollection.
+joinedMODIS = innerJoinedMODIS.map(lambda feature: ee.Image.cat(feature.get('primary'), feature.get('secondary')))
+
+# Print the result of merging.
+print('Inner join, merged bands:', joinedMODIS.getInfo())
+

Join/intersect.py

@@ -0,0 +1,51 @@
+import ee 
+from ee_plugin import Map 
+
+def intersect(state):
+  nPowerPlants = ee.List(state.get('power_plants')).size()
+  # Return the state feature with a new property: power plant count.
+  return state.set('n_power_plants', nPowerPlants)
+
+# Load the primary 'collection': US state boundaries.
+states = ee.FeatureCollection('TIGER/2018/States')
+
+# Load the secondary 'collection': power plants.
+powerPlants = ee.FeatureCollection('WRI/GPPD/power_plants')
+
+# Define a spatial filter as geometries that intersect.
+spatialFilter = ee.Filter.intersects(**{
+  'leftField': '.geo',
+  'rightField': '.geo',
+  'maxError': 10
+})
+
+# Define a save all join.
+saveAllJoin = ee.Join.saveAll(**{
+  'matchesKey': 'power_plants',
+})
+
+# Apply the join.
+intersectJoined = saveAllJoin.apply(states, powerPlants, spatialFilter)
+
+# Add power plant count per state as a property.
+intersectJoined = intersectJoined.map(intersect)
+# intersectJoined = intersectJoined.map(function(state) {
+#   # Get "power_plant" intersection list, count how many intersected this state.
+#   nPowerPlants = ee.List(state.get('power_plants')).size()
+#   # Return the state feature with a new property: power plant count.
+#   return state.set('n_power_plants', nPowerPlants)
+# })
+
+print(intersectJoined.getInfo())
+
+# # Make a bar chart for the number of power plants per state.
+# chart = ui.Chart.feature.byFeature(intersectJoined, 'NAME', 'n_power_plants') \
+#   .setChartType('ColumnChart') \
+#   .setSeriesNames({n_power_plants: 'Power plants'}) \
+#   .setOptions({
+#     title: 'Power plants per state',
+#     hAxis: {title: 'State'},
+#     vAxis: {title: 'Frequency'}})
+
+# # Print the chart to the console.
+# print(chart)

Join/inverted_joins.py

@@ -0,0 +1,34 @@
+import ee 
+from ee_plugin import Map 
+
+# Load a Landsat 8 image collection at a point of interest.
+collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_TOA') \
+    .filterBounds(ee.Geometry.Point(-122.09, 37.42))
+
+# Define start and end dates with which to filter the collections.
+april = '2014-04-01'
+may = '2014-05-01'
+june = '2014-06-01'
+july = '2014-07-01'
+
+# The primary collection is Landsat images from April to June.
+primary = collection.filterDate(april, june)
+
+# The secondary collection is Landsat images from May to July.
+secondary = collection.filterDate(may, july)
+
+# Use an equals filter to define how the collections match.
+filter = ee.Filter.equals(**{
+  'leftField': 'system:index',
+  'rightField': 'system:index'
+})
+
+# Define the join.
+invertedJoin = ee.Join.inverted()
+
+# Apply the join.
+invertedJoined = invertedJoin.apply(primary, secondary, filter)
+
+# Display the result.
+print('Inverted join: ', invertedJoined.getInfo())
+

Join/save_all_joins.py

@@ -0,0 +1,42 @@
+import ee 
+from ee_plugin import Map 
+
+# Load a primary 'collection': Landsat imagery.
+primary = ee.ImageCollection('LANDSAT/LC08/C01/T1_TOA') \
+    .filterDate('2014-04-01', '2014-06-01') \
+    .filterBounds(ee.Geometry.Point(-122.092, 37.42))
+
+# Load a secondary 'collection': MODIS imagery.
+modSecondary = ee.ImageCollection('MODIS/006/MOD09GA') \
+    .filterDate('2014-03-01', '2014-07-01')
+
+# Define an allowable time difference: two days in milliseconds.
+twoDaysMillis = 2 * 24 * 60 * 60 * 1000
+
+# Create a time filter to define a match as overlapping timestamps.
+timeFilter = ee.Filter.Or(
+  ee.Filter.maxDifference(**{
+    'difference': twoDaysMillis,
+    'leftField': 'system:time_start',
+    'rightField': 'system:time_end'
+  }),
+  ee.Filter.maxDifference(**{
+    'difference': twoDaysMillis,
+    'leftField': 'system:time_end',
+    'rightField': 'system:time_start'
+  })
+)
+
+# Define the join.
+saveAllJoin = ee.Join.saveAll(**{
+  'matchesKey': 'terra',
+  'ordering': 'system:time_start',
+  'ascending': True
+})
+
+# Apply the join.
+landsatModis = saveAllJoin.apply(primary, modSecondary, timeFilter)
+
+# Display the result.
+print('Join.saveAll:', landsatModis.getInfo())
+

Join/save_best_joins.py

@@ -0,0 +1,30 @@
+import ee 
+from ee_plugin import Map 
+
+# Load a primary 'collection': Landsat imagery.
+primary = ee.ImageCollection('LANDSAT/LC08/C01/T1_TOA') \
+    .filterDate('2014-04-01', '2014-06-01') \
+    .filterBounds(ee.Geometry.Point(-122.092, 37.42))
+
+# Load a secondary 'collection': GRIDMET meteorological data
+gridmet = ee.ImageCollection('IDAHO_EPSCOR/GRIDMET')
+
+# Define a max difference filter to compare timestamps.
+maxDiffFilter = ee.Filter.maxDifference(**{
+  'difference': 2 * 24 * 60 * 60 * 1000,
+  'leftField': 'system:time_start',
+  'rightField': 'system:time_start'
+})
+
+# Define the join.
+saveBestJoin = ee.Join.saveBest(**{
+  'matchKey': 'bestImage',
+  'measureKey': 'timeDiff'
+})
+
+# Apply the join.
+landsatMet = saveBestJoin.apply(primary, gridmet, maxDiffFilter)
+
+# Print the result.
+print(landsatMet.getInfo())
+

Join/simple_joins.py

@@ -0,0 +1,34 @@
+import ee 
+from ee_plugin import Map 
+
+# Load a Landsat 8 image collection at a point of interest.
+collection = ee.ImageCollection('LANDSAT/LC08/C01/T1_TOA') \
+    .filterBounds(ee.Geometry.Point(-122.09, 37.42))
+
+# Define start and end dates with which to filter the collections.
+april = '2014-04-01'
+may = '2014-05-01'
+june = '2014-06-01'
+july = '2014-07-01'
+
+# The primary collection is Landsat images from April to June.
+primary = collection.filterDate(april, june)
+
+# The secondary collection is Landsat images from May to July.
+secondary = collection.filterDate(may, july)
+
+# Use an equals filter to define how the collections match.
+filter = ee.Filter.equals(**{
+  'leftField': 'system:index',
+  'rightField': 'system:index'
+})
+
+# Create the join.
+simpleJoin = ee.Join.simple()
+
+# Apply the join.
+simpleJoined = simpleJoin.apply(primary, secondary, filter)
+
+# Display the result.
+print('Simple join: ', simpleJoined.getInfo())
+

Join/spatial_joins.py

@@ -0,0 +1,31 @@
+import ee 
+from ee_plugin import Map 
+
+# Load a primary 'collection': protected areas (Yosemite National Park).
+primary = ee.FeatureCollection("WCMC/WDPA/current/polygons") \
+  .filter(ee.Filter.eq('NAME', 'Yosemite National Park'))
+
+# Load a secondary 'collection': power plants.
+powerPlants = ee.FeatureCollection('WRI/GPPD/power_plants')
+
+# Define a spatial filter, with distance 100 km.
+distFilter = ee.Filter.withinDistance(**{
+  'distance': 100000,
+  'leftField': '.geo',
+  'rightField': '.geo',
+  'maxError': 10
+})
+
+# Define a saveAll join.
+distSaveAll = ee.Join.saveAll(**{
+  'matchesKey': 'points',
+  'measureKey': 'distance'
+})
+
+# Apply the join.
+spatialJoined = distSaveAll.apply(primary, powerPlants, distFilter)
+
+# Print the result.
+# print(spatialJoined.getInfo())
+Map.centerObject(spatialJoined, 10)
+Map.addLayer(ee.Image().paint(spatialJoined, 1, 3), {}, 'Spatial Joined')

convert_js_to_python.py

@@ -14,7 +14,7 @@ def dict_key_str(line):
     'sigma', 'magnitude', 'size', 'connectedness', 'maxSize', 'eightConnected',
     'reducer', 'labelBand', 'color', 'source', 'maxDistance', 'referenceImage',
     'maxOffset', 'patchWidth', 'strokeWidth', 'width', 'geometry', 'scale', 'maxPixels',
-    'collection', 'selectors']
+    'collection', 'selectors', 'leftField', 'rightField']
     for key in keys:
         if ":" in line and key in line:
             line = line.replace(key + ":", "'" + key + "':")