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.filter(ee.Filter.eq('WRS_PATH', int(path))).filter(ee.Filter.eq('WRS_ROW', int(row)))
for period in self._periods:
images_by_period = ImageCollection(image_collection).filter_by_period(year, feature.get(period), self._offset)
if self._apply_brdf:
images_by_period = images_by_period.apply_brdf()
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)
if self._reducers:
image_reduced = Image(ImageCollection(images_by_period).apply_reducers(self._reducers))
image_reduced = image_reduced.rename(image_reduced.bandNames().map(
lambda band: ee.String(period).cat('_').cat(band))
)
final_name = "{0}_{1}_{2}".format(settings.COLLECTION_PREFIX, "{0}{1}".format(path, row), str(year))
final_image = image_reduced.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})
else:
images_by_period = images_by_period.map(
lambda image: Image(image).rename(Image(image).bandNames().map(
lambda band: ee.String(period).cat('_').cat(band))
)
)
images_by_period = images_by_period.toList(settings.MAX_IMAGES)
for i in xrange(images_by_period.size().getInfo()):
image = Image(images_by_period.get(i))
date = image.date().format('yyyyMMdd').getInfo()
final_name = "{0}_{1}_{2}".format(settings.COLLECTION_PREFIX, "{0}{1}".format(path, row), str(date))
final_image = Image(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})
def apply_temporal_filter(self, collection, offset, initial_threshold):
collection = collection.toList(settings.MAX_IMAGES)
new_collection = ImageCollection([])
for index in xrange(len(self.__years)):
left, center, right, threshold = self.__break_list(
collection, index, offset, 0,
len(self.__years) - 1, initial_threshold)
year = self.__years[index]
roi = center.geometry()
filename = "{0}_{1}".format(self.__collection_prefix, str(year))
center = center.unmask(None).eq(self.__class_of_reference)
left = ImageCollection(left)
right = ImageCollection(right)
sides = ImageCollection(left.merge(right)).map(lambda image: Image(
image).eq(self.__class_of_reference)).sum()
mask = center.add(sides.eq(0)).neq(2)
image = center.add(sides).gte(threshold + 1)
filtered_image = Image(center.add(image)).updateMask(mask).gte(1)
filtered_image = filtered_image.clip(roi).set(
'system:index',
filename).set('year', year).set('system:footprint', roi)
new_collection = new_collection.merge(
ImageCollection(filtered_image))
final_name = filename
final_image = filtered_image
self.add_image_in_batch(final_name, {
"image": final_image,
"year": int(year),
"geometry": roi
})
return new_collection