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Geocomputation and open source software: components and software stacks

  • Bivand, Roger


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

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    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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    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
    Date of revision:
    Handle: RePEc:hhs:nhheco:2011_023
    Contact details of provider: Postal: NHH, Department of Economics, Helleveien 30, N-5045 Bergen, Norway
    Phone: +47 55 959 277
    Fax: 5595 9100
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    1. Foros, Øystein & Kind, Hans Jarle & Shaffer, Greg, 2010. "Mergers and Partial Ownership," Discussion Paper Series in Economics 1/2010, Department of Economics, Norwegian School of Economics.
    2. Rey, S.J., 2008. "Show me the code: Spatial analysis and open source," MPRA Paper 9260, University Library of Munich, Germany.
    3. Kunze, Astrid & Troske, Kenneth R., 2012. "Life-cycle patterns in male/female differences in job search," Labour Economics, Elsevier, vol. 19(2), pages 176-185.
    4. Dirk Eddelbuettel & Romain Francois, . "Rcpp: Seamless R and C++ Integration," Journal of Statistical Software, American Statistical Association, vol. 40(i08).
    5. Sarah C. Goslee, . "Analyzing Remote Sensing Data in R: The landsat Package," Journal of Statistical Software, American Statistical Association, vol. 43(i04).
    6. Micah Altman & Michael P. McDonald, . "BARD: Better Automated Redistricting," Journal of Statistical Software, American Statistical Association, vol. 42(i04).
    7. Stefan Theußl & Uwe Ligges & Kurt Hornik, 2011. "Prospects and challenges in R package development," Computational Statistics, Springer, vol. 26(3), pages 395-404, September.
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