Cheat sheet for GDAL/OGR command-line tools

Vector operations

Get vector information

ogrinfo -so input.shp layer-name

Or, for all layers

ogrinfo -al -so input.shp

Print vector extent

ogrinfo input.shp layer-name | grep Extent

List vector drivers

ogr2ogr --formats

Convert between vector formats

ogr2ogr -f "GeoJSON" output.json input.shp

Clip vectors by bounding box

ogr2ogr -f "ESRI Shapefile" output.shp input.shp -clipsrc <x_min> <y_min> <x_max> <y_max>

Clip one vector by another

ogr2ogr -clipsrc clipping_polygon.shp output.shp input.shp

Reproject vector:

ogr2ogr output.shp -t_srs "EPSG:4326" input.shp

Merge vectors:

ogr2ogr merged.shp input1.shp
ogr2ogr -update -append merged.shp input2.shp -nln merged

Extract from a vector file based on query

To extract features with STATENAME 'New York','New Hampshire', etc. from states.shp

ogr2ogr -where 'STATENAME like "New%"' states_subset.shp states.shp

To extract type 'pond' from water.shp

ogr2ogr -where "type = pond" ponds.shp water.shp

Subset & filter all shapefiles in a directory

Assumes that filename and name of layer of interest are the same...

ls -1 *.shp | sed 's/.shp//g' | xargs -n1 -I % ogr2ogr %-subset.shp %.shp -sql "SELECT field-one, field-two FROM '%' WHERE field-one='value-of-interest'"

Raster operations

Get raster information

gdalinfo input.tif

List raster drivers

gdal_translate --formats

Convert between raster formats

gdal_translate -of "GTiff" input.grd output.tif

Convert a directory of files to a different raster format

ls -1 *.img | sed 's/.img//g' | xargs -n1 -I % gdal_translate -of "GTiff" %.img %.tif

Reproject raster:

gdalwarp -t_srs "EPSG:102003" input.tif output.tif

Georeference an unprojected image with known bounding coordinates:

gdal_translate -of GTiff -a_ullr <top_left_lon> <top_left_lat> <bottom_right_lon> <bottom_right_lat> -a_srs EPSG:4269 input.png output.tif

Clip raster by bounding box

gdalwarp -te <x_min> <y_min> <x_max> <y_max> input.tif clipped_output.tif

Clip raster to SHP / NoData for pixels beyond polygon boundary

gdalwarp -dstnodata <nodata_value> -cutline input_polygon.shp input.tif clipped_output.tif

Merge rasters

gdal_merge.py -o merged.tif input1.tif input2.tif

Alternatively,

gdalwarp input1.tif input2.tif merged.tif

Or, to preserve nodata values:

gdalwarp input1.tif input2.tif merged.tif -srcnodata <nodata_value> -dstnodata <merged_nodata_value>

Create a hillshade from a DEM

gdaldem hillshade -of PNG input.tif hillshade.png

Change light direction:

gdaldem hillshade -of PNG -az 135 input.tif hillshade_az135.png 

Use correct vertical scaling in meters if input is projected in degrees

gdaldem hillshade -s 111120 -of PNG input_WGS1984.tif hillshade.png

Apply color ramp to a DEM
First, create a color-ramp.txt file:
(Height, Red, Green, Blue)

	0 110 220 110
	900 240 250 160
	1300 230 220 170
	1900 220 220 220
	2500 250 250 250

Then apply those colors to a DEM:

gdaldem color-relief input.tif color_ramp.txt color-relief.tif

Create slope-shading from a DEM
First, make a slope raster from DEM:

	gdaldem slope input.tif slope.tif 

Second, create a color-slope.txt file:
(Slope angle, Red, Green, Blue)

0 255 255 255
90 0 0 0  

Finally, color the slope raster based on angles in color-slope.txt:

gdaldem color-relief slope.tif color-slope.txt slopeshade.tif

Resample raster

gdalwarp -ts <width> <height> -r cubicspline dem.tif resampled_dem.tif

Entering 0 for either width or height guesses based on current dimensions.

Burn vector into raster

gdal_rasterize -b 1 -i -burn -32678 -l layername input.shp input.tif

Create contours from DEM

gdal_contour -a elev -i 50 input_dem.tif output_contours.shp

Other

Convert KML points to CSV (simple)

ogr2ogr -f CSV output.csv input.kmz -lco GEOMETRY=AS_XY

Convert KML to CSV (WKT)
First list layers in the KML file

ogrinfo -so input.kml

Convert the desired KML layer to CSV

ogr2ogr -f CSV output.csv input.kml -sql "select *,OGR_GEOM_WKT from some_kml_layer"

CSV points to SHP
This section needs retooling
Given input.csv

lon_column,lat_column,value
-81,32,13
-81,32,14
-81,32,15

Make a .dbf table for ogr2ogr to work with from input.csv

ogr2ogr -f "ESRI Shapefile" input.dbf input.csv

Use a text editor to create a .vrt file in the same directory as input.csv and input.dbf. This file holds the parameters for building a full shapefile based on values in the DBF you just made.

<OGRVRTDataSource>
  <OGRVRTLayer name="output_file_name">
    <SrcDataSource relativeToVRT="1">./</SrcDataSource>
    <SrcLayer>input</SrcLayer>
    <GeometryType>wkbPoint</GeometryType>
    <LayerSRS>WGS84</LayerSRS>
    <GeometryField encoding="PointFromColumns" x="lon_column" y="lat_column"/>
  </OGRVRTLayer>
</OGRVRTDataSource>

Create shapefile based on parameters listed in the .vrt

mkdir shp
ogr2ogr -f "ESRI Shapefile" shp/ inputfile.vrt

The VRT file can be modified to give a new output shapefile name, reference a different coordinate system (LayerSRS), or pull coordinates from different columns.

MODIS operations

First, download relevant .hdf tiles from the MODIS ftp site: ftp://ladsftp.nascom.nasa.gov/; use the MODIS sinusoidal grid for reference.

Create a file containing the names of all .hdf files in the directory

ls -1 *.hdf > files.txt

List MODIS Subdatasets in a given HDF (conf. the MODIS products table)

gdalinfo longFileName.hdf | grep SUBDATASET

Make TIFs from each file in list; replace 'MOD12Q1:Land_Cover_Type_1' with desired Subdataset name

mkdir output
cat files.txt | xargs -I % -n1 gdalwarp -of GTiff 'HDF4_EOS:EOS_GRID:%:MOD12Q1:Land_Cover_Type_1' output/%.tif

Merge all .tifs in output directory into single file

cd output
gdal_merge.py -o Merged_Landcover.tif *.tif

Sources

http://live.osgeo.org/en/quickstart/gdal_quickstart.html

https://github.com/nvkelso/geo-how-to/wiki/OGR-to-reproject,-modify-Shapefiles

ftp://ftp.remotesensing.org/gdal/presentations/OpenSource_Weds_Andre_CUGOS.pdf

http://developmentseed.org/blog/2009/jul/30/using-open-source-tools-make-elevation-maps-afghanistan-and-pakistan/

http://linfiniti.com/2010/12/a-workflow-for-creating-beautiful-relief-shaded-dems-using-gdal/

http://nautilus.baruch.sc.edu/twiki_dmcc/bin/view/Main/OGR_example

http://www.gdal.org/frmt_hdf4.html

http://planetflux.adamwilson.us/2010/06/modis-processing-with-r-gdal-and-nco.html

http://trac.osgeo.org/gdal/wiki/FAQRaster

http://www.mikejcorey.com/wordpress/2011/02/05/tutorial-create-beautiful-hillshade-maps-from-digital-elevation-models-with-gdal-and-mapnik/

http://dirkraffel.com/2011/07/05/best-way-to-merge-color-relief-with-shaded-relief-map/

http://gfoss.blogspot.com/2008/06/gdal-raster-data-tips-and-tricks.html