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Communities & Collections
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A framework to embed a spatial statistics toolbox in open-source GIS software: kernel density estimation example
Date
2017-01-01
Author
Cavur, M.
Düzgün, Hafize Şebnem
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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It is widely known that geographic information systems (GIS) should include more spatial data analysis (SDA) techniques. The issues of which techniques should be included and how statistical analysis can be integrated with GIS are still widely debated. This paper focuses on the development of a framework that implements R SDA techniques in the uDig. For this purpose, a simple interface is designed between two open-source software applications, uDig and the R statistical software package. The tight coupling strategy is adopted with the RCaller interpreter. Overall, the integration is successfully implemented and tested by users and developers. Fourteen geospatial and four non-geospatial techniques are integrated into uDig successfully, which demonstrates the success of the proposed framework. Among these techniques, the kernel density estimation (KDE) technique is explained with a sample data set to show every step of the implementation. The user tests also prove the success of the integration.
Subject Keywords
R SDA
,
Tightly coupled SDA
,
Integration
,
SDA
,
GIS
URI
https://hdl.handle.net/11511/57083
Journal
JOURNAL OF SPATIAL SCIENCE
DOI
https://doi.org/10.1080/14498596.2016.1230837
Collections
Department of Mining Engineering, Article