def pan_sharpen(path, meta, data_type):
'''Use the pan chromatic layer to pan-sharen the Blue, Green, Red, & NIR stack
@param stack: Input composite image stack
@ptype stack: c{string}
@param meta: Metadat built from MTL.txt
@ptype meta: Dictionary of landsat scene metadata
@return Output composite image with pan-sharpening
'''
ap.env.workspace = path
ap.CheckOutExtension("Spatial")
out_stack = str(
meta['L1_METADATA_FILE']['LANDSAT_SCENE_ID']) + 'STACK_PANSHARP.img'
rasters = ap.ListRasters()
rgb = [img for img in rasters if 'STACK_RGB.img' in img]
pan = [img for img in rasters if 'B8.img' in img]
print rgb
print pan
print ""
print "Begining Pan Sharpen"
if (data_type == "Landsat8"):
print "Landsat8"
ap.CreatePansharpenedRasterDataset_management(rgb[0], "4", "3", "2",
"5", out_stack, pan[0],
"Brovey")
else:
ap.CreatePansharpenedRasterDataset_management(rgb[0], "3", "2", "1",
"4", out_stack, pan[0],
"Brovey")
print ""
print "Pan Sharpen Complete"
def pansharpen(folder):
# init
arcpy.env.workspace = folder
nir_band, r_band, g_band, b_band, p_band = None, None, None, None, None
# find relevant file
for eachfile in os.listdir(folder):
if eachfile.endswith('B5.TIF'):
nir_band = eachfile
elif eachfile.endswith('B4.TIF'):
r_band = eachfile
elif eachfile.endswith('B3.TIF'):
g_band = eachfile
elif eachfile.endswith('B2.TIF'):
b_band = eachfile
elif eachfile.endswith('B8.TIF'):
p_band = eachfile
else:
pass
# make sure all bands are available
if nir_band and r_band and g_band and b_band and p_band:
temp_composite = r'in_memory\temp_composite' # in_memory space
# composite bands first
try:
arcpy.CompositeBands_management(
';'.join([r_band, g_band, b_band, nir_band]), temp_composite)
except Exception as e:
print(e)
return None
# pansharpen
try:
# construct new text
out_tif = os.path.splitext(nir_band)[0].split(
'_')[0] + '_' + 'PAN432' + '.tif'
# create out put
arcpy.CreatePansharpenedRasterDataset_management(
temp_composite, "1", "2", "3", "4", out_tif, p_band,
"Gram-Schmidt", "0.42", "0.51", "0.07", "0", "Landsat 8")
except Exception as e:
print(e)
return None
# clean up
arcpy.Delete_management(temp_composite)
return out_tif
else:
print('Error: some bands are missing, exit')
return None
arcpy.env.workspace = cur_dir + '/data/'
arcpy.env.overwriteOutput = True
arcpy.env.scratchWorkspace = SW = cur_dir + '/temp/'
for row in arcpy.da.SearchCursor(aoi_poly, ['Name', 'SHAPE@']):
if row[0] == "Dillon":
arcpy.env.extent = row[1].extent
ls_MS_C = arcpy.CopyRaster_management(in_raster=ls_MS, out_rasterdataset="#")
ls_pan_C = arcpy.CopyRaster_management(in_raster=ls_pan, out_rasterdataset="#")
ls_MS_C_P = arcpy.CreatePansharpenedRasterDataset_management(
in_raster=ls_MS_C,
red_channel=3,
green_channel=2,
blue_channel=1,
infrared_channel=4,
in_panchromatic_image=ls_pan_C,
)
print(ls_MS_C_P)
sigs = arcpy.sa.CreateSignatures(
in_raster_bands=ls_MS_C_P,
in_sample_data=sigs_shp,
sample_field='Classvalue',
out_signature_file="#"
)
# classed_rast = arcpy.ia.MLClassify(arcpy.sa.Raster(ls_MS_C_P), sigs)
# result = classed_rast.save('CLASSED.tif')
#
('tri', 'ms_tri.tif', 'pan_tri.tif', 5, 3, 2, 7, 0.3937, 0.03117,
0.4153, 0.1598),
('was', 'ms_was.tif', 'pan_was.tif', 3, 2, 1, 4, 0.3601, 0.09414,
0.3964, 0.1494)]
# Compute Weights (only required for Esri)
##for s in scenes:
## arcpy.ComputePansharpenWeights_management('{}'.format(s[1]),'{}'.format(s[2]),str('{}'.format(s[3]) + " " + '{}'.format(s[4]) + " " + '{}'.format(s[5]) + " " + '{}'.format(s[6])))
# Create pansharpened rasters using nested for loop
for s in scenes:
for a in algorithms:
arcpy.CreatePansharpenedRasterDataset_management(
'{}'.format(s[1]), # in_raster
'{}'.format(s[3]), # red_channel
'{}'.format(s[4]), # green_channel
'{}'.format(s[5]), # blue_channel
'{}'.format(s[6]), # infrared_channel
arcpy.env.workspace + '\Processed\\' + '{}'.format(a[0]) + '_' +
'{}'.format(s[0]) + '.tif', # out_raster_dataset
'{}'.format(s[2]), # in_panchromatic_image
'{}'.format(a[0]), # pansharpening_type
'{}'.format(s[7]), # red_weight
'{}'.format(s[8]), # green_weight
'{}'.format(s[9]), # blue_weight
'{}'.format(s[10]), # infrared_weight
'{}'.format(a[1])) # sensor
# Calculate NDVI, in separate script, <ndvi.py>
# Compute Weights (only required for Esri)
##for s in scenes:
## arcpy.ComputePansharpenWeights_management('{}'.format(s[1]),'{}'.format(s[2]),"4 3 2 5")
# Create pansharpened rasters using nested for loop
for s in scenes:
for a in algorithms:
arcpy.CreatePansharpenedRasterDataset_management(
'{}'.format(s[1]), # in_raster
4,
3,
2,
5, # r, g, b, nir channels
arcpy.env.workspace + '\Processed\\' + '{}'.format(a[0]) + '_' +
'{}'.format(s[0]) + '.tif' # out_raster_dataset
,
'{}'.format(s[2]) # in_panchromatic_image
,
'{}'.format(a[0]) # pansharpening_type
,
'{}'.format(s[3]) # red_weight
,
'{}'.format(s[4]) # green_weight
,
'{}'.format(s[5]) # blue_weight
,
'{}'.format(s[6]) # infrared_weight
,
'{}'.format(a[1])) # sensor