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42 lines
1.3 KiB
Python
42 lines
1.3 KiB
Python
"""Landcover cleanup.
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Display the MODIS land cover classification image with appropriate colors.
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"""
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import ee
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import ee.mapclient
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ee.Initialize()
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ee.mapclient.centerMap(-113.41842, 40.055489, 6)
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# Force projection of 500 meters/pixel, which is the native MODIS resolution.
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VECTORIZATION_SCALE = 500
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image1 = ee.Image('MODIS/051/MCD12Q1/2001_01_01')
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image2 = image1.select(['Land_Cover_Type_1'])
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image3 = image2.reproject('EPSG:4326', None, 500)
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image4 = image3.focal_mode()
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image5 = image4.focal_max(3).focal_min(5).focal_max(3)
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image6 = image5.reproject('EPSG:4326', None, 500)
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PALETTE = [
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'aec3d4', # water
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'152106', '225129', '369b47', '30eb5b', '387242', # forest
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'6a2325', 'c3aa69', 'b76031', 'd9903d', '91af40', # shrub, grass, savannah
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'111149', # wetlands
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'cdb33b', # croplands
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'cc0013', # urban
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'33280d', # crop mosaic
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'd7cdcc', # snow and ice
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'f7e084', # barren
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'6f6f6f' # tundra
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]
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vis_params = {'min': 0, 'max': 17, 'palette': PALETTE}
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ee.mapclient.addToMap(image2, vis_params, 'IGBP classification')
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ee.mapclient.addToMap(image3, vis_params, 'Reprojected')
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ee.mapclient.addToMap(image4, vis_params, 'Mode')
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ee.mapclient.addToMap(image5, vis_params, 'Smooth')
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ee.mapclient.addToMap(image6, vis_params, 'Smooth')
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