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# need to rescale the values | |
gdal_translate -scale 200 350 0 1 air.59.tif air-rescaled.tif | |
# or batch it | |
find *.tif -exec gdal_translate -scale 200 350 0 1 {} {}.rescaled.tif \; | |
# make into png files | |
mogrify -format jpg *.rescaled.tif |
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find *_polygon.shp -exec ogr2ogr -s_srs EPSG:5070 -t_srs EPSG:102009 ../nasqan_polygons_lambert/{} {} \; |
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find *.shp -exec gdal_rasterize -burn 1 -tr 200 200 {} ../nasqan_raster_lambert/{}.tif \; | |
# improve performance by loading more data into memory at once | |
find *.shp -exec gdal_rasterize --config GDAL_CACHEMAX 2400 -burn 1 -tr 30 30 -a_srs EPSG:5070 -of HFA {} ../nasqan_raster_conus/{}30.img \; | |
# compress tiffs using LZW to vasty improve disk performance | |
find *.shp -exec gdal_rasterize --config GDAL_CACHEMAX 4000 -burn 1 -tr 30 30 -a_srs EPSG:5070 -co COMPRESS=LZW {} ../nasqan_raster_conus/{}30.tiff \; |
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require(ncdf) | |
require(raster) | |
file.nc <- 'air.sfc.2009.nc' | |
## Output: a GeoTIFF file | |
file.tiff <- paste('air/air.', sprintf('%.4d',day), '.tiff', sep ='') | |
r.temperature <- raster(file.nc, day) |
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# tried with gdalwarp, but ends up slow with a huge file | |
gdalwarp -q -cutline /Users/matthewxi/Documents/Projects/NASQAN/clip_columbia_extent_conus.shp -crop_to_cutline -co COMPRESS=LZW -of GTiff /Users/matthewxi/Documents/Projects/NASQAN/nasqan_raster_conus_compressed/b14246900_polygon.shp30.tiff /Users/matthewxi/Documents/Projects/NASQAN/b14246900_nlcd_clipped_3.tif | |
# gdal_translate seems to be the better option | |
# using extents to crop | |
gdal_translate -projwin -2191346 3275471 -1068667 2168385 -co "COMPRESS=LZW" /Users/matthewxi/Documents/Projects/NASQAN/nasqan_raster_conus_compressed/b14246900_polygon.shp30.tiff /Users/matthewxi/Documents/Projects/NASQAN/b14246900_nlcd_clipped_7.tif |
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#!/home/deepwinter/env/bin/python | |
# using virtual env | |
# http://wiki.dreamhost.com/Python | |
import datetime | |
import time | |
import wget | |
import datetime | |
import tarfile | |
import os.path | |
import urlgrabber |
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+proj=stere +lat_0=90 +lat_ts=60 +lon_0=-105 +k=1 +x_0=0 +y_0=0 | |
+a=6371200 +b=6371200 +to_meter=4762.5 +no_defs | |
["Degree",0.0174532925199433]],PROJECTION["Stereographic_North_Pole"], | |
PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0], | |
PARAMETER["Central_Meridian",-105.0],PARAMETER["Standard_Parallel_1", | |
60.0],UNIT["HRAP_Grid",4762.5]] |
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gdal_rasterize --config GDAL_CACHEMAX 4000 -burn 1 -tr 1.0 1.0 -te 562 -952 602 -853 -co COMPRESS=LZW CT_Watershed_Above_Haddam_HRAP_Projected.shp CT_Watershed_Above_Haddam_HRAP_Projected.tiff |
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+proj=aea +lat_1=29.5 +lat_2=45.5 +lat_0=23 +lon_0=-96 +x_0=0 +y_0=0 +ellps=GRS80 +datum=NAD83 +units=m +no_defs |
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# VIM regex commands | |
# Get ride of anything not from 2010 - 2015 | |
g!/\(.*\)\(201[0-5]\) /d | |
# Get ride of all areas not relevant to our study area | |
g!/^0601\|^0602\|^1901\|^1902\|^2701\|^2702\|^4301\|^4302\|^4303/d | |
# Split region code from year, get ride of variable code | |
%s/\(.*\)05\(201[0-5]\) /\1 \2/g |