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Merge pull request #183 from njwilson23/bqa-mask

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Proposed cloud/ice detection fixes
This commit is contained in:
Scisco
2016-05-13 14:13:07 -04:00
parent 87873fc13b 85e1b26785
commit 362d5b046f
2 changed files with 12 additions and 14 deletions
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2
landsat/downloader.py
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@@ -126,7 +126,7 @@ class Downloader(VerbosityMixin):
self.remote_file_exists(url)
self.output('Source: Google Storge', normal=True, arrow=True)
self.output('Source: Google Storage', normal=True, arrow=True)
return self.fetch(url, path)
def amazon_s3(self, scene, bands):

24
landsat/image.py
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@@ -288,24 +288,22 @@ class BaseProcess(VerbosityMixin):
return numpy.percentile(color[numpy.logical_and(color > 0, color < 65535)], (low, high))
def _calculate_cloud_ice_perc(self):
""" Return the percentage of pixels that are either cloud or snow with
high confidence (> 67%).
"""
self.output('Calculating cloud and snow coverage from QA band', normal=True, arrow=True)
a = rasterio.open(join(self.scene_path, self._get_full_filename('QA'))).read_band(1)
count = 0
snow = [56320, 39936, 31744, 28590, 26656, 23552]
cloud = [61440, 59424, 57344, 53248, 28672, 36896, 36864, 24576]
for item in cloud:
count += numpy.extract(a == item, a).size
for item in snow:
count += numpy.extract(a == item, a).size * 2
perc = numpy.true_divide(count, a.size) * 100
cloud_high_conf = int('1100000000000000', 2)
snow_high_conf = int('0000110000000000', 2)
fill_pixels = int('0000000000000001', 2)
cloud_mask = numpy.bitwise_and(a, cloud_high_conf) == cloud_high_conf
snow_mask = numpy.bitwise_and(a, snow_high_conf) == snow_high_conf
fill_mask = numpy.bitwise_and(a, fill_pixels) == fill_pixels
perc = numpy.true_divide(numpy.sum(cloud_mask | snow_mask),
a.size - numpy.sum(fill_mask)) * 100.0
self.output('cloud/snow coverage: %s' % round(perc, 2), indent=1, normal=True, color='green')
return perc
def _filename(self, name=None, suffix=None, prefix=None):