An ArcGIS software license cost about 1400$ per year per computer. Despite of its high cost, it is the most used software for mapping and geo-data analysis. In developing countries, this is an unbearable cost and most GIS specialists work with pirated software. It is a matter of time until ESRI (the company that distributes the ArcGIS software) will start suing organization lacking legal in licenses even in developing countries (something that already happens in the developed world).
Open source software offer a free alternative to the ESRI products (http://catherinepfeifer.blogspot.ch/2011/08/desperate-need-for-more-geographical.html). Open source software is software which code is freely available and therefore any modification of the code has to be shared freely. User and developer communities work together in developing the software thanks to forums, wiki and meetings. In short, it is nonprofit software.
Last week I joint the Geostat 2012 in Muenster, Germany (http://www.geostat-course.org/Muenster_2012). It is the European summer school (All classes have been recorded and can be streamed on the geostat website) followed by the meeting of the developers for open source GIS. It was for me the occasion to familiarize myself with the latest development in open source GIS (not yet released code), in spatial analysis, but also to familiarize myself with the existing open source GIS software (the stable version) and make up my mind about their usefulness in a developing world context, where users often have only very little GIS background.
|participants testing out some R code|
During the week I discovered how to use R (the open source version of Matlab, a statistical program) as GIS, Grass and Saga (both open source GIS). R is a relatively low level programing language, which needs initial investment to learn the coding language. Its spatial base package (SP developed by trainers of the summer school) and a whole other range of spatial package offer an amazing range of option to analyses spatial data. Visualization of data is feasible but reminds far behind the easy and good looking options given by ESRI. Also after one afternoon of programing with some R freaks, we did not manage to read and overlay two of my own maps L (mainly because projections and extend have to match). The most recent code development allow to link R with google earth for visualization, including the spatio-temporal visualizations. Other code recently developed or in development allow for spatio-temporal data analysis and data dissagragation (downscaling).
Grass is an open source software that has been initially developed for linux, but it is made compatible to all other operating systems and even got a relatively nice graphical user interface (GUI). It stays that the most efficient way to work with this software is to use the command window like with R. Unfortunately the nice options, such as easy copy paste, the automatic protocoling of work done, and the function history which allows to recall all the commands ever applied on a dataset are features that only work in the linux version, leaving the Microsoft user in a much less efficient environment. Also the graphical representation of data, the ease to change legends, colors and titles is relatively clumsy. Nonetheless, Grass comes with a set of amazing feature that the ArcGIS software will only offers years from now and probably at high costs. Among others Grass includes a new algorithm to compute water flow and therefore delineate basin without using the tradition “fill sink” opens, amazing 3D visualizations (available on Arc for an additional 3800 $ license), an up-coming spatio-temporal analysis tool (I have never worked this this type of data, I don’t really know what Arc offers, but I guess the base license will never allow manage spatio-temporal data so efficiently), terrain analysis tool and for the upcoming Grass 7 (to be released probably in about a year) will come with a tool that allows to compare two maps by swiping over it (an amazing visualization tool that will allow to show stakeholders in an easy way different spatial alternatives.)
|The GRASS 6.3 GUI|
Similarly SAGA GIS offers a whole range of tools, 3D visualizations and terrain(working with point clouds) that are incomparable to what Arc offers. Saga runs directly without installation from any external storage devise. The GUI is smartly organized and once the logics of it is well understood, allows to perform manipulations efficiently. But here again the layout options are very limited and it is difficult to come up with maps that looks as good as those easily produced in ArcGIS.
Both Grass and Saga can be linked to R, allowing to combine the statistical power of R with GIS tools and algorithm developed by the open source GIS software.
|A SAGA 3D visualization of Innsbruck|
In the developing world, the first objective is to train people to make simple geo-data analysis, to represent graphically geodata without great theoretical background. The open source options I have discovered last week require users that understand geographical data very well (no projections on the fly like in Arc), the layout options for producing good looking maps are limited, and often the GUIs are not as user friendly that the one from ArcGIS. None of the program I have seen really convinced me as an alternative of Arc GIS for stakeholders in the developing world. Other open source software exist that might mimic the Arc GIS option in terms of visualization, such as MapWindow or Qgis. It might be worth to look into these options.
The open source options nonetheless have convinced me as a scientist. Today, I combine stata, excel and ArcGIS, copy manually values, run simulation almost manually. If I make a mistake somewhere, it takes days to rerun. In principle all could be programmed with one R code that calls for data and routines with it owns suite of packages but also those from the open source software. It would decrease source of errors and allow to rerun code quickly in case of mistake. Also open source comes with a community of developer that support user and love to take up the challenges brought up by users. Therefore, features and tools might be up-coming faster than with ESRI.
|Tom and Gerard, two lecturers (and organizers) from Wageningen University|
Definitely, there is no such a thing as a free lunch. Open source GIS comes with amazing computational options and GIS analysis for free, with an amazing community of support full of very nice people. But it comes with relatively high cost. It is a relatively steep learning curve for reaching a decent level of programming language. It needs a lot of patience to adjust the settings of one’s computer to make the software run, especially for Microsoft users who need to learn how to trick their system, and accept that some fancy stuff is simply not possible, because one cannot change the Microsoft code. It is definitely not what a stakeholder who wants to produce some simple map in the developing world is looking for. I guess one needs to hide a little nerd in one’s heart to take up the open source challenge …
|one of the social evenings with beers and sausages|
Finally, I had a very good week. Not only did I learn about recent developments in open source GIS, but also that computer programmer are not autistic nerds with no social life. On the contrary, I met amazingly interesting, sociable and funny people. I would like to thank the organizer for the very smooth organization, for the trainers for sharing their passion and all the participants for the support and patience when my R was again sending an error message and for all the nice social evenings…