gee_ndvi

gee_ndvi.py

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')