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ISPRS Int. J. Geo-Inf. 2015, 4(2), 815-836; doi:10.3390/ijgi4020815

Open Geospatial Analytics with PySAL

GeoDa Center for Geospatial Analysis and Computation, School of Geographical Sciences and Urban Planning at Arizona State University
Author to whom correspondence should be addressed.
Academic Editors: Barend Kobben, Serena Coetzee and Wolfgang Kainz
Received: 6 February 2015 / Revised: 1 April 2015 / Accepted: 20 April 2015 / Published: 13 May 2015
(This article belongs to the Special Issue Open Geospatial Science and Applications)
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This article reviews the range of delivery platforms that have been developed for the PySAL open source Python library for spatial analysis. This includes traditional desktop software (with a graphical user interface, command line or embedded in a computational notebook), open spatial analytics middleware, and web, cloud and distributed open geospatial analytics for decision support. A common thread throughout the discussion is the emphasis on openness, interoperability, and provenance management in a scientific workflow. The code base of the PySAL library provides the common computing framework underlying all delivery mechanisms. View Full-Text
Keywords: spatial analysis; spatial econometrics; spatial decision support systems; cyberGIS; open source software; high performance computing spatial analysis; spatial econometrics; spatial decision support systems; cyberGIS; open source software; high performance computing

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Rey, S.J.; Anselin, L.; Li, X.; Pahle, R.; Laura, J.; Li, W.; Koschinsky, J. Open Geospatial Analytics with PySAL. ISPRS Int. J. Geo-Inf. 2015, 4, 815-836.

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