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@jcaceres85
Created October 25, 2023 19:46
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gee_ndvi
import ee, geemap
Map = geemap.Map()
out_dir = 'C:/info_sig/IVCC_Backup/IVCC_SIG/Datos/Rasters/USLE'
filename = os.path.join(out_dir, 'NDVI_NoClouds.tif')
fc = ee.FeatureCollection("users/josecaceres/Limite_Depto_HN")
hn = fc.geometry()
def maskL8sr(image):
"""
Función para enmascarar nubes según la banda pixel_qa de los datos de Landsat 8 SR.
Parameters
----------
image : ee.Image
entrada de imagen Imagen Landsat 8 SR.
Returns
-------
image : ee.Image
imagen de Landsat 8 enmascarada
"""
#Bits 3 and 5 are cloud shadow and cloud, respectively
cloudShadowBitMask = (1 << 3)
cloudsBitMask = (1 << 5)
#Get the pixel QA band. Both flags should be set to zero, indicating clear conditions
qaMask = image.select('pixel_qa').bitwiseAnd(cloudShadowBitMask).eq(0) and image.select('pixel_qa').bitwiseAnd(cloudShadowBitMask).eq(0)
return image.updateMask(qaMask)
dataset = (ee.ImageCollection('LANDSAT/LC08/C01/T1_SR')
.filterDate('2021-01-01', '2021-12-31')
.filterBounds(hn)
.map(maskL8sr)
)
median = dataset.median()
ndvi = median.normalizedDifference(['B5', 'B4']).rename('NDVI')
image = ndvi.clip(hn)
geemap.download_ee_image(image, filename=filename, region=hn, scale=30, crs='EPSG:4326')
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