Libraries and command line tools for geospatial data processing and analysis
- Resample/warp rasters to common resolution/extent/projection
- Many functions to handle rasters with NoData gaps using NumPy masked arrays
- Point data coordinate transformations, sampling, and interpolation routines (e.g., arrays of xyz points)
- Common raster filtering operations
Libraries pygeotools/lib
- geolib - Coordinate transformations, raster to vector, vector to raster
- malib - NumPy Masked Array operations, DEMStack class
- warplib - On-the-fly GDAL warp operations for abitrary number of input datasets
- iolib - File input/output, wrappers for GDAL I/O, masked array write to disk
- timelib - Time conversions, extract timestamps from filenames, useful for raster time series analysis
- filtlib - Collection of filters for 2D masked arrays (Gauss, rolling median, high pass, etc.)
- warptool.py - Warp arbitrary rasters to common res/extent/proj
- make_stack.py - Create a "stack" of input rasters (a raster time series object) and compute stats
- clip_raster_by_shp.py - Clip and mask an input raster using a polygon shapefile
- apply_mask.py - Apply mask from one raster to another
- filter.py - Apply various filters available in filtlib
- trim_ndv.py - Remove rows/cols containing only NoData from raster margins
- replace_ndv.py - Replace NoData value
- proj_select.py - Automatically determine projection for input lat/lon or raster
- raster2shp.py - Create polygon shapefile of input raster footprints
- ogr_merge.sh - Merge shapefiles
- ...
from pygeotools.lib import iolib, warplib, malib
fn1 = 'raster1.tif'
fn2 = 'raster2.tif'
ds_list = warplib.memwarp_multi_fn([fn1, fn2], res='max', extent='intersection', t_srs='first', r='cubic')
r1 = iolib.ds_getma(ds_list[0])
r2 = iolib.ds_getma(ds_list[1])
rdiff = r1 - r2
malib.print_stats(rdiff)
out_fn = 'raster_diff.tif'
iolib.writeGTiff(rdiff, out_fn, ds_list[0])
or, from the command line...
Warp all to match raster1.tif projection with common intersection and largest pixel size:
warptool.py -tr max -te intersection -t_srs first raster1.tif raster2.tif raster3.tif
Create version of raster1.tif that matches resolution, extent, and projection of raster2.tif:
warptool.py -tr raster2.tif -te raster2.tif -t_srs raster2.tif raster1.tif
Reproject and clip to user-defined extent, preserving original resolution of each input raster:
warptool.py -tr source -te '439090 5285360 458630 5306450' -t_srs EPSG:32610 raster1.tif raster2.tif
from pygeotools.lib import malib
fn_list = ['20080101_dem.tif', '20090101_dem.tif', '20100101_dem.tif']
s = malib.DEMStack(fn_list, res='min', extent='union')
#Stack standard deviation
s.stack_std
#Stack linear trend
s.stack_trend
or, from the command line...
make_stack.py -tr 'min' -te 'union' 20*.tif
http://pygeotools.readthedocs.io
Install the latest release from PyPI:
pip install pygeotools
Note: by default, this will deploy executable scripts in /usr/local/bin
Clone the repository and install:
git clone https://github.com/dshean/pygeotools.git
pip install -e pygeotools
The -e flag ("editable mode", setuptools "develop mode") will allow you to modify source code and immediately see changes.
This originated as a personal repo that I am slowly cleaning up and distributing. There are some useful things that work very well, other things that were hastily written for a one-off task several years ago, and some confusing things that were never finished.
Contributions, bug reports, and general feedback are all welcome. My time is limited, I have some bad habits, and I could really use some help. Thanks in advance.
This was all originally developed for Python 2.X, but should now also work with Python 3.X thanks to @dlilien
Some of this functionality now exists in the excellent, mature, well-supported rasterio. Eventually, I will integrate rasterio API calls where appropriate.
This project is licensed under the terms of the MIT License.