GDAL command line tools¶

We have now tested some of the basic functions from the Python GDAL/OGR API for reading and inspecting raster files. However, GDAL also includes other powerful functions for data translation and processing which are not directly implemented in the library. We will have a closer look on a couple of such functions:

These tools need to be run from the Terminal/Command Prompt or as a subprocess in Python. We will now quickly test out these tools in the Terminal window.

Clipping image with gdalwarp¶

Among other tricks, gdalwarp is a very handy tool for quickly clipping your image. We will now practice how to clip the satellite image band based on a bounding box. Desired extent for the output file is specified using the option -te:

gdalwarp -te xmin ymin xmax ymax inputfile.tif outputfile.tif


Todo

Clip band 4 of the satellite image so that it covers cloud-free areas in the Turku archipelago (in the North-East corner of the scene).

You can open the band 4 manually in QGIS for defining the corner coordinates.

Next, let’s repeat the clipping for all the rest of the bands all at once. For doing this, we will use Python for generating the command for each spectral band in our scene.

import glob
import os

# List filepaths for all bands in the scence
FileList = glob.glob(os.path.join(r'/home/geo/LandsatData','*band*.tif'))

# Define clipping extent
xmin, ymin, xmax,ymax = (0, 0, 0, 0) # INSERT HERE THE CORRECT COORDINATES

# Generate gdalwarp command for each band
command = ""

for fp in FileList:
inputfile = fp
outputfile = inputfile[:-4] + "_clip.tif"

command += "gdalwarp -te %s %s %s %s %s %s \n" % (xmin, ymin, xmax, ymax, inputfile, outputfile)

# Write the commands to an .sh file
cmd_file = "ClipTurkufromLandsat.sh"
f = open(os.path.join(cmd_file), 'w')

f.write(command)
f.close()


Note

If you are working in an windows environment, change the .sh extension to .bat which is the Windows equivalent of a batch -file with similar functionalities.

After running the above script, you should have a file ClipTurkufromLandsat.sh in your working directory. Open the file (with a text editor) and check that the commands have been written correctly to the file.

Next, run the file in the Terminal window:

bash ClipTurkufromLandsat.sh


Now you should have a bunch of clipped .tif files ready and you might want to open a few of them in QGIS to check that the process was successful.

Stacking layers with gdal_merge.py¶

After clipping the image you can for example stack bands 3 (green), 4 (red), and 5 (nir) for visualizing a false-color composite. Merge the layers with gdal_merge.py and use the -separate option for indicating that you wish to save the inputs as separate bands in the output file.

Let’s try running the command as a subprocess in python:

import os

# Define input and output files
inputfiles =  "band3_clip.tif band4_clip.tif band5_clip.tif"
outputfile =  "Landsat8_GreenRedNir.tif"

# Generate the command
command = "gdal_merge.py -separate %s -o %s" % (inputfiles, outputfile)

# Run the command. os.system() returns value zero if the command was executed succesfully
os.system(command)


As a result, you have three bands stacked together in the file Landsat8_GreenRedNir.tif.

Calculations with rasters using gdal_calc.py¶

Gdal_calc.py is a command line raster calculator which can be useful for competing simple repetitive calculations for raster data.

Open the terminal window and execute following command:

Gdal_calc.py


You should see instructions on the usage and options for the tool. The basic syntax for gdal_calc.py is the following:

gdal_calc.py -A input1.tif - B input2.tif [other_options] --outfile=outputfile.tif


From other options, it is useful to notice at least the parameters --calc for specifying the calculation syntax and --creation-option (or --co) for controlling the output file size:

• In the case of two input files --calc="A+B" would add files A and B together.
• By default output files tend to be huge which will quickly result in problems with disk size and memory. With gdal_calc.py you can add parameter --co="COMPRESS=LZW" in order to reduce output file size.