def run(self):
features = self._feature_collection.get_features()
for year in self._years:
for feature in features:
path = feature.get('PATH')
row = feature.get('ROW')
geometry = ee.Geometry.MultiPolygon(feature.get('GEOMETRY'))
neighbors = self.get_neighbors(features, int(path), int(row))
neighbors_paths = map(lambda x: x[0], neighbors)
neighbors_rows = map(lambda x: x[1], neighbors)
neighbors_geometry = ee.Geometry.MultiPolygon(map(lambda x: x[2], neighbors))
image_collection = self._collection \
.filter(ee.Filter.inList('WRS_PATH', ee.List(neighbors_paths))) \
.filter(ee.Filter.inList('WRS_ROW', ee.List(neighbors_rows)))
images = []
for period in self._periods:
period_dates = feature.get(period)
images_by_period = ImageCollection([])
for i in range(self._offset):
local_images_by_period = ImageCollection(image_collection).filter_by_period(year - i, period_dates, 1)
if self._clip_geometry:
local_images_by_period = local_images_by_period.clip_geometry()
if self._apply_mask:
local_images_by_period = local_images_by_period.apply_qamask()
if self._bands:
local_images_by_period = local_images_by_period.apply_bands(self._bands)
images_by_period = images_by_period.merge(local_images_by_period)
reduced_image = ImageCollection(images_by_period).apply_reducers(self._reducers)
reduced_image = reduced_image.rename(reduced_image.bandNames().map(
lambda band: ee.String(period).cat('_').cat(band))
)
images.append(reduced_image)
final_image = Image.cat(images)
final_name = "{0}_{1}_{2}".format(settings.COLLECTION_PREFIX, "{0}{1}".format(path, row), str(year))
final_image = final_image.select(settings.GENERATION_VARIABLES + settings.GENERATION_EXTRA_VARIABLES).set('year', year)
self.add_image_in_batch(final_name,
{"image": final_image, "year": int(year), "path": int(path), "row": int(row), "geometry": geometry,
'neighbors': neighbors_geometry})
def run(self):
for year in self._years:
for feature in self._feature_collection.get_features():
path = feature.get('PATH')
row = feature.get('ROW')
geometry = ee.Geometry.MultiPolygon(feature.get('geometry'))
image_collection = self._collection.map(lambda image: image.clip(geometry))
images = []
for period in self._periods:
period_dates = feature.get(period)
images_by_period = ImageCollection(image_collection).filter_by_period(year, period_dates, self._offset)
images_by_period = images_by_period.apply_smoothing()
if self._clip_geometry:
images_by_period = images_by_period.clip_geometry()
if self._apply_mask:
images_by_period = images_by_period.apply_qamask()
if self._bands:
images_by_period = images_by_period.apply_bands(self._bands)
image_reduced = Image(images_by_period.apply_reducers(self._reducers))
image_reduced = image_reduced.rename(image_reduced.bandNames().map(
lambda band: ee.String(period).cat('_').cat(band))
)
images.append(image_reduced)
final_image = Image.cat(images)
if settings.GENERATION_EXTRA_BANDS:
final_image = final_image.addBands(Image(final_image).get_bands(settings.GENERATION_EXTRA_BANDS))
final_name = "{0}_{1}_{2}".format(settings.COLLECTION_PREFIX, "{0}{1}".format(path, row), str(year))
final_image = final_image.clip(geometry).select(settings.GENERATION_VARIABLES + settings.GENERATION_EXTRA_VARIABLES).set('year',
year).set(
'system:footprint', geometry)
self.add_image_in_batch(final_name,
{"image": final_image, "year": int(year), "path": int(path), "row": int(row), "geometry": geometry})