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Geocomputation and open source software: components and software stacks

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  • Bivand, Roger

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    (Dept. of Economics, Norwegian School of Economics and Business Administration)

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    Abstract

    Geocomputation, with its necessary focus on software development and methods innovation, has enjoyed a close relationship with free and open source software communities. These extend from communities providing the numerical infrastructure for computation, such as BLAS (Basic Linear Algebra Subprograms),through language communities around Python, Java and others, to communities supporting spatial data handling, especially the projects of the Open Source Geospatial Foundation. This chapter surveys the stack of software components available for geocomputation from these sources, looking in most detail at the R language and environment, and how OSGeo projects have been interfaced with it. In addition, attention will be paid to open development models and community participation in software development. Since free and open source geospatial software has also achieved a successively greater presence in proprietary software as computational platforms evolve, the chapter will close with some indications of future trends in software component stacks, using Terralib as an example.

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    Bibliographic Info

    Paper provided by Department of Economics, Norwegian School of Economics in its series Discussion Paper Series in Economics with number 23/2011.

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    Length: 37 pages
    Date of creation: 15 Dec 2011
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    Handle: RePEc:hhs:nhheco:2011_023

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    Keywords: Geocomputation; Open source software;

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    1. Oystein Foros & Hans Jarle Kind & Greg Shaffer, 2010. "Mergers and Partial Ownership," CESifo Working Paper Series 2912, CESifo Group Munich.
    2. Kunze, Astrid & Troske, Kenneth R., 2010. "Life-Cycle Patterns in Male/Female Differences in Job Search," Discussion Paper Series in Economics 2/2010, Department of Economics, Norwegian School of Economics.
    3. Sarah C. Goslee, . "Analyzing Remote Sensing Data in R: The landsat Package," Journal of Statistical Software, American Statistical Association, vol. 43(i04).
    4. Stefan Theußl & Uwe Ligges & Kurt Hornik, 2011. "Prospects and challenges in R package development," Computational Statistics, Springer, vol. 26(3), pages 395-404, September.
    5. Dirk Eddelbuettel & Romain Francois, . "Rcpp: Seamless R and C++ Integration," Journal of Statistical Software, American Statistical Association, vol. 40(i08).
    6. Sergio Rey, 2009. "Show me the code: spatial analysis and open source," Journal of Geographical Systems, Springer, vol. 11(2), pages 191-207, June.
    7. Micah Altman & Michael P. McDonald, . "BARD: Better Automated Redistricting," Journal of Statistical Software, American Statistical Association, vol. 42(i04).
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