•  
  •  
 

Creative Commons License

Creative Commons Attribution-No Derivative Works 3.0 License
This work is licensed under a Creative Commons Attribution-No Derivative Works 3.0 License.

Abstract

In a world where researchers are more and more confronted to large sets of micro- data, new algorithms are constantly developed that have to be translated into usable programs. Modular GIS toolkits such as GRASS GIS offer a middle way between low-level programming approaches and GUI-based desktop GIS. The modules can be seen as elements of a programming language which makes the implementation of algorithms for spatial analysis very easy for researchers. Using two examples of algorithms in economic geography, for estimating regional exports and for determining raster-object neighbourhood matrices, this paper shows how just a few module calls can replace more complicated low-level programs, as long as the re- searcher can change perspective from a pixel-by-pixel view to a map view of the problem at hand. Combining GRASS GIS with Python as general glue between modules also offers options for easy multi-processing, as well as supporting the increasingly loud call for open research, including open source computing tools in research.

DOI

https://doi.org/10.7275/R5QN64XN

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.