def pix():
mask = image.select('pixel_qa')
cloud_mask = tools.compute_bits(mask, 5, 5, 'cloud')
shadow_mask = tools.compute_bits(mask, 3, 3, 'shadow')
snow_mask = tools.compute_bits(mask, 4, 4, 'snow')
good_pix = cloud_mask.eq(0).And(shadow_mask.eq(0)).And(snow_mask.eq(0))
return good_pix
def sr():
mask = image.select('sr_cloud_qa')
cloud_mask = tools.compute_bits(mask, 1, 1, 'cloud')
shadow_mask = tools.compute_bits(mask, 2, 2, 'shadow')
adjacent_mask = tools.compute_bits(mask, 3, 3, 'adjacent')
snow_mask = tools.compute_bits(mask, 4, 4, 'snow')
good_pix = cloud_mask.eq(0).And(shadow_mask.eq(0)).And(
snow_mask.eq(0)).And(adjacent_mask.eq(0))
return good_pix
def sentinel2(image):
""" Function to use in SENTINEL2 Collection
Use:
`masked = collection.map(cloud_mask.sentinel2)`
"""
nubes = image.select("QA60")
opaque = tools.compute_bits(nubes, 10, 10, "opaque")
cirrus = tools.compute_bits(nubes, 11, 11, "cirrus")
mask = opaque.Or(cirrus)
result = image.updateMask(mask.Not())
return result
def modis(img):
""" Function to use in MODIS Collection
Use:
`masked = collection.map(cloud_mask.modis)`
"""
cmask = img.select("state_1km")
cloud = tools.compute_bits(cmask, 1, 1, "cloud")
mix = tools.compute_bits(cmask, 0, 0, "mix")
shadow = tools.compute_bits(cmask, 2, 2, "shadow")
cloud2 = tools.compute_bits(cmask, 10, 10, "cloud2")
snow = tools.compute_bits(cmask, 11, 11, "snow")
mask = cloud.Or(mix).Or(shadow).Or(cloud2).Or(snow)
return img.updateMask(mask.Not())
def ledaps(image):
""" Function to use in Surface Reflectance Collections computed by
LEDAPS
Use:
`masked = collection.map(cloud_mask.ledaps)`
"""
cmask = image.select('QA')
valid_data_mask = tools.compute_bits(cmask, 1, 1, 'valid_data')
cloud_mask = tools.compute_bits(cmask, 2, 2, 'cloud')
snow_mask = tools.compute_bits(cmask, 4, 4, 'snow')
good_pix = cloud_mask.eq(0).And(valid_data_mask.eq(0)).And(snow_mask.eq(0))
result = image.updateMask(good_pix)
return result
def wrap(img):
# mask = img.select('pixel_qa')
mask = img.select('BQA')
cloud_mask = tools.compute_bits(mask, 4, 4, 'cloud')
shadow_mask = tools.compute_bits(mask, 8, 8, 'shadow')
snow_mask = tools.compute_bits(mask, 10, 10, 'snow')
relation = ee.Dictionary({
'cloud': cloud_mask,
'shadow': shadow_mask,
'snow': snow_mask
})
masks_list = tools.get_from_dict(options,
relation) # make a list of masks
good_pix = apply_masks(masks_list)
return img.updateMask(good_pix)
def for_iterate(option, ini):
i = ee.Image(ini) # cast ini
# bits relation dict contains the option?
cond = bits_dict.contains(option)
# get the mask for the option
mask = tools.compute_bits(bits_dict.get(option), bits_dict.get(option),
option)(image)
return ee.Image(ee.Algorithms.If(cond, i.Or(mask), i))
def modis(img):
""" Function to use in MODIS Collection
Use:
`masked = collection.map(cloud_mask.modis)`
"""
cmask = img.select("state_1km")
cloud = tools.compute_bits(cmask, 0, 0, "cloud")
mix = tools.compute_bits(cmask, 1, 1, "mix")
shadow = tools.compute_bits(cmask, 2, 2, "shadow")
cloud2 = tools.compute_bits(cmask, 10, 10, "cloud2")
snow = tools.compute_bits(cmask, 12, 12, "snow")
mask = (
cloud.Or(mix)
# .Or(shadow) # Cloud shadow seems to be miscomputed (MODIS/MYD09GA/MYD09GA_005_2015_09_18)
.Or(cloud2).Or(snow))
return img.updateMask(mask.Not())
