It Takes a Village to Find a Village:
Solving complex problems with diverse geospatial tools
Stace Maples
Stanford Geospatial Center
https://link.springer.com/article/10.1186/s41018-018-0030-y
(or, GDAL)
http://www.gdal.org/
#Import modules
import glob, os, gdal, fnmatch
#Set base directory to location of script
base_directory = os.path.abspath('')
#Make a list of Multispectral directories with 'MUL' in the path
multi_directory_list = glob.glob(os.path.join(base_directory, '*MUL'))
#Make Panchromatic directory [pan_directory] path by replacing 'MUL' with 'PAN'
for multi_directory in multi_directory_list:
pan_directory = multi_directory.replace('MUL','PAN')
print(multi_directory)
print(pan_directory)
#Make a list of TIF files in the multi_directory
multi_tiffs_list = fnmatch.filter((os.listdir(multi_directory)), '*.TIF')
for multi_tiff_name in multi_tiffs_list:
print(multi_tiff_name)
#Get the matching panchromatic image for the current multispectral by searching for the RowCol
multi_rowcol_wildcard = '*'+multi_tiff_name[19:24]+'*'
#print(multi_rowcol)
pan_tiffs_list = fnmatch.filter((os.listdir(pan_directory)), '*.TIF')
pan_tiff_name = fnmatch.filter(pan_tiffs_list, multi_rowcol_wildcard)
#print(pan_tiff_name[0])
#Pan-sharpen the multispectral using it's corresponding panchromatic image using JPEG compression and internal tiles
print('pansharpen')
os.system('python gdal_pansharpen.py -co NBITS=12 -co COMPRESS=JPEG -co JPEG_QUALITY=50 -co PHOTOMETRIC=YCBCR -co TILED=YES ' + os.path.join(pan_directory,pan_tiff_name[0]) + ' ' + os.path.join(multi_directory,multi_tiff_name) + ',band=7 ' + os.path.join(multi_directory,multi_tiff_name) + ',band=5 ' + os.path.join(multi_directory,multi_tiff_name) + ',band=3 ' + base_directory + '/sharp_' + multi_tiff_name)
#Add overviews for resulting tiffs
os.system('gdaladdo --config COMPRESS_OVERVIEW JPEG --config PHOTOMETRIC_OVERVIEW YCBCR --config INTERLEAVE_OVERVIEW PIXEL -r average ' + base_directory + '/sharp_' + multi_tiff_name + ' 2 4 8 16')
#Create a Virtual Raster Mosaic of VRT type from all resulting sharpened TIFF images
print('create VRT mosaic from SHARP images')
os.system('gdalbuildvrt sharpmosaic.vrt *.TIF')
#Haven't finished figuring out how to get a decently stretched image out of this part. More to do!
print('MBtiles out')
print('gdal_translate sharpmosaic.vrt sharpmosaic.mbtiles -of MBTILES')
print('gdaladdo -r average sharpmosaic.mbtiles 2 4 8 16')
https://github.com/mapninja/DGF_parser
http://www.gdal.org/
DigitalGlobe Foundation
ICME
David Rumsey Map Center
Humanitarian OpenStreetMap Team
OSM Community
And part of my job is to leverage that brand for all I can to provide resources and connections for my Stanford Researchers
in your relationships with vendors, stakeholders and partners
The geospatial data science and mapping tools we are working with, this week, are part of that "Macroscope"
"I suppose it is tempting,if the only tool you have is a hammer, to treat everything as if it were a nail."
Abraham Maslow - "The Psychology of Science, 1966"
Don't be this...
...be this.
@mapninja
stacemaples@stanford.edu
slides.com/staceymaples/imw2018