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Here are many questions with great answers about open source GIS software.

I am wondering, what is the best open source software package for Remote Sensing? I would like to learn it and to use in my work.

I used to work with IDRISI, and I've heard about Erdas and ENVI, but they all are not free. I am looking for a free and powerful leader, like Qgis for GIS or R for statistics. With powerful classification, segmentation, Fourier, filters, PCA, etc.

Can anyone please advise me a good free RS software? What are the capabilities, user friendly or with command line? Do any comparison matrices exist?

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  • Please provide more details like use cases, your workflows etc. Otherwise this thread would just turn into a list of open source RS software. In its current form, there would be no definitive answer for your question.
    – R.K.
    Commented Oct 15, 2012 at 4:19
  • Thanks, I tried to edit. I would like to have powerful classification, segmentation, Fourier, filters, PCA, etc. I thought that there could be a leader among free RS softwares (like Qgis for GIS)
    – nadya
    Commented Oct 15, 2012 at 5:55
  • If you have a new question, please ask it by clicking the Ask Question button. Include a link to this question if it helps provide context.
    – MappaGnosis
    Commented Jul 22, 2015 at 14:54

12 Answers 12

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There are a few good ones around:

All with the bonus of being able to be used though the QGIS interface using the SEXTANTE plugin like so http://blog.orfeo-toolbox.org/uncategorized/otb-inside-sextante-inside-qgis

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    Re GRASS GIS: See also grass.osgeo.org/wiki/GRASS_and_Sextante and especially grass.osgeo.org/wiki/Image_processing (it offers classification, segmentation, Fourier, filters, PCA, and much more).
    – markusN
    Commented Oct 15, 2012 at 16:33
  • The list of GRASS image processing functions looks very inspiring! But, can I access ALL the image processing functions of GRASS through QGIS, or I still need to add some modules or type commands? (I have never worked with GRASS before). The path GRASS -> Sextante -> QGIS looks rather long... Can some features be lost? Is the installation tricky? Thanks!
    – nadya
    Commented Oct 16, 2012 at 4:48
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    The path is either GRASS directly (it has a new GUI), or QGIS -> Sextante -> GRASS (it will auto-recognize the maps loaded in the QGIS canvas).
    – markusN
    Commented Oct 16, 2012 at 19:04
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For processing of Landsat, I can recommend GRASS. I tried many others.

You may need to refine your question with regard to the type of imagery you propose to use. There are workflows which have been more or less developed and implemented in various software.

Not only the type of imagery, but the purpose of the processing and final analysis. For Landsat, I am interested in a quantitative value. Which is different to qualititive methods used in regional classification of vegetation for instance, methods and tools for this work are more common.

You will not likely find a Swiss Army Knife for free. But you will find very specialised tools which do one job well.

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    See also the dedicated page: grass.osgeo.org/wiki/LANDSAT
    – markusN
    Commented Oct 15, 2012 at 16:34
  • Thanks. I didn't know that GRASS is good for RS as well
    – nadya
    Commented Oct 15, 2012 at 17:17
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R is also suitable as a GIS. Many of the standard GIS functionality is available in pure R, e.g. interpolation (gstat, automap, fields), raster operations (raster, sp), or polygon operations (rgeos). In addition, many of the statistical techniques (e.g. regression, PCA, classification), can be used also for spatial data and are readily available in R. For any missing stuff, you can interface R with GRASS and SAGA. See the spatial data task view for R for a good list of spatial data analysis in R.

Ofcourse, R is a programming language which has a rather steep learning curve, especially when you are used to GUI based GIS software. However, in return for your investment you get a statistical environment in which you can do just about anything out-of-the-box, or create it yourself if it is not already available in a package. Also, in comparison to GUI based software you can easily script your analyses, making them easy to repeat, and version control.

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  • Thank you, I know a little of R, but it's mainly statistical. I'm not sure that it's a good way for me to program RS functions and image processing in R
    – nadya
    Commented Oct 16, 2012 at 2:33
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Opticks is also worth a look. It is particularly strong in handling (hyperspectral) imagery.

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The "best" software is somewhat subjective and dependent on your needs. All of the options provided thus far are worth exploring. I would like to add SPRING software to the current suggestions. This is a very robust free GUI-driven software for remote sensing. All of the functionality that you mentioned is available.

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  • As I see it has its own format ASCII-SPRING. Is it easy to export-import more common formats, without problems? Both raster and vector?
    – nadya
    Commented Oct 15, 2012 at 21:15
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    Note that Spring is not free software according to their dpi.inpe.br/spring/english/license.html
    – markusN
    Commented Oct 16, 2012 at 19:08
  • Thank you, now I see. At least free of charge. I will try this one and GRASS.
    – nadya
    Commented Oct 16, 2012 at 20:53
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In addition to what has been mentioned above, OSSIM.

Another option is pktools, which is a suite of utilities written in C++ for image processing with a focus on remote sensing applications. It relies on the Geospatial Data Abstraction Library (GDAL). It includes programs for image classification that use Support Vector Machine and Neural Network classifiers.

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I would like to mention a serious open source attempt at providing a remote sensing package for watershed and terrain analysis called Whitebox GAT. It can be found here.

http://www.uoguelph.ca/~hydrogeo/Whitebox/

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Very well power tools has been developed by http://km.fao.org/OFwiki/index.php/Open_Foris_Geospatial_Toolkit, http://www.spatial-ecology.net/dokuwiki/doku.php?id=wiki:pk_tools and see also Geo Tools under the spatial-ecology page . You just need install and combine under bash language. They are very fast and you can even using for massive data procession under parallel computing. Have a nice computation. Giuseppe

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Other than what is mentioned above:

Fiji has been helpful with some image processing and classification in our office.

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Meanwhile I also found a nice list of free RS software with descriptions.

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ESA provides free toolboxes for the processing of SAR and optical images:

The **Sentinel-1 Toolbox (S1TBX) consists of a collection of processing tools, data product readers and writers and a display and analysis application to support the large archive of data from ESA SAR missions including SENTINEL-1, ERS-1 & 2 and ENVISAT, as well as third party SAR data from ALOS PALSAR, TerraSAR-X, COSMO-SkyMed and RADARSAT-2. The various processing tools could be run independently from the command-line and also integrated within the graphical user interface. The Toolbox includes tools for calibration, speckle filtering, coregistration, orthorectification, mosaicking, data conversion, polarimetry and interferometry.

The Sentinel-2 Toolbox consists of a rich set of visualisation, analysis and processing tools for the exploitation of optical high-resolution products including the upcoming Sentinel-2 MSI sensor. As a multi-mission remote sensing toolbox, it also provides support for third party data from RapidEye, SPOT, MODIS (Aqua and Terra), Landsat (TM) and others.

The Sentinel-3 Toolbox consists of a rich set of visualisation, analysis and processing tools for the exploitation of OLCI and SLSTR data from the upcoming Sentinel-3 mission. As a multi-mission remote sensing toolbox, it also supports the ESA missions Envisat (MERIS & AATSR), ERS (ATSR), SMOS as well as third party data from MODIS (Aqua and Terra), Landsat (TM), ALOS (AVNIR & PRISM) and others. The various tools can be run from an intuitive desktop application or via a command-line interface. A rich application programming interface allows for development of plugins using Java or Python.

I haven't tried out the new tool boxes, but I worked with the previous version "NEST" of the SAR toolbox. It was sometimes a bit buggy, but generally very easy to use!

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As you wanted something free, check out this new package for R - RStoolbox.

https://cran.r-project.org/web/packages/RStoolbox/index.html

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