def __init__(self, geometry, startDate, stopDate, collection):
"""
Class used to get composites from Earth Engine
Parameters
----------
geometry : GeoJSON
GeoJSON with a polygon.
startDate : string
stopDate : string
collection: string
Name of a collection.
"""
self.geometry = geometry
self.startDate = startDate
self.stopDate = stopDate
self.collection = collection
self.scale = ee_collection_specifics.scales(self.collection)
self.color = '#2BA4A0'
self.style_function = lambda x: {
'fillOpacity': 0.0,
'weight': 4,
'color': self.color
}
# Earth Engine tile URL
self.ee_tiles = 'https://earthengine.googleapis.com/map/{mapid}/{{z}}/{{x}}/{{y}}?token={token}'
self.bucket = 'skydipper_materials'
# Area of Interest
self.region = self.geometry.get('features')[0].get('geometry').get(
'coordinates')
self.polygon = ee.Geometry.Polygon(self.region)
self.centroid = self.polygon.centroid().getInfo().get(
'coordinates')[::-1]
self.locations = list(
map(tuple, list(map(lambda x: x[::-1], self.region[0]))))
self.bbox = self.polygon.bounds().getInfo().get('coordinates')[0]
self.bounds = [self.bbox[0][::-1], self.bbox[2][::-1]]
# Image Collection
self.image_collection = ee_collection_specifics.ee_collections(
self.collection)
# Image Visualization parameters
self.vis = ee_collection_specifics.ee_vis(self.collection)
# Saving parameters
self.visSave = {
'dimensions': 1024,
'format': 'png',
'crs': 'EPSG:3857',
'region': self.region
}
def create_collection(self, scale=None):
years = np.arange(self.start_year, self.stop_year + 1)
dic = ee_collection_specifics.date_range(self.instrument)
years_range = list(map(list, list(dic.values())))
collections = list(dic.keys())
image_list = []
for year in years:
n = 0
in_range = False
for sub_years in years_range:
if year in sub_years:
in_range = True
break
n = +1
if not in_range:
raise ValueError(f'Year out of range.')
collection = collections[n]
if scale:
scale = scale
else:
scale = ee_collection_specifics.scales(collection)
# Image Collection
image_collection = ee_collection_specifics.ee_collections(
collection)
# Image Visualization parameters
vis = ee_collection_specifics.ee_vis(collection)
step_range = ee_collection_specifics.step_range(collection)
startDate = ee.Date(str(year + step_range[0]) + '-12-31')
stopDate = ee.Date(str(year + step_range[1]) + '-12-31')
image = ee_collection_specifics.Composite(collection)(
image_collection, startDate, stopDate, scale, self.polygon)
# convert image to an RGB visualization
image_list.append(self.visFun(image, vis))
return image_list
def __init__(self, point, buffer, startDate, stopDate, scale, collection):
"""
Class used to get the datasets from Earth Engine
Parameters
----------
point : list
A list of two [x,y] coordinates with the center of the area of interest.
buffer : number
Buffer in meters
startDate : string
stopDate : string
scale: number
Pixel size in meters.
collection: string
Name of each collection.
"""
self.point = point
self.buffer = buffer
self.startDate = startDate
self.stopDate = stopDate
self.scale = scale
self.collection = collection
# Area of Interest
self.geom = ee.Geometry.Point(self.point).buffer(self.buffer)
self.region = self.geom.bounds()
# Image Collection
self.image_collection = ee_collection_specifics.ee_collections(self.collection)
# Bands
self.bands = ee_collection_specifics.ee_bands(self.collection)
# normalized Difference bands and their names
self.normDiff_bands = ee_collection_specifics.normDiff_bands(self.collection)
self.normDiff_bands_names = ee_collection_specifics.normDiff_bands_names(self.collection)
def __init__(self, point, buffer, startDate, stopDate, scale, path, collection):
"""
Class used to get the datasets from Earth Engine
Parameters
----------
point : list
A list of two [x,y] coordinates with the center of the area of interest.
buffer : number
Buffer in meters
startDate : string
stopDate : string
scale: number
Pixel size in meters.
collection: string
Name of each collection.
"""
self.point = point
self.buffer = buffer
self.startDate = startDate
self.stopDate = stopDate
self.scale = scale
self.path = path
self.collection = collection
# Area of Interest
self.geom = ee.Geometry.Point(self.point).buffer(self.buffer)
self.region = self.geom.bounds().getInfo()['coordinates']
# Image Collection
self.image_collection = ee_collection_specifics.ee_collections(self.collection)
# Image Visualization parameters
self.vis = ee_collection_specifics.ee_vis(self.collection)
# Saving parameters
self.visSave = {'dimensions': 1024, 'format': 'png', 'crs': 'EPSG:4326'}