Using Spatial Statistics In GIS

نویسنده

  • K. Krivoruchko
چکیده

A Geographical Information System (GIS) provides a powerful collection of tools for the management and visualization of spatial data. These tools can be even more powerful when they are integrated with methods for spatial data analysis. In this context, we provide several examples that show the power of exploratory spatial data analysis (ESDA) within a GIS and how this can provide the foundation for more sophisticated probabilistic modeling. While the ESRI’s ArcGIS software now facilitates the integration of spatial data analysis and GIS functionality, more tools are needed for comprehensive spatial data analysis. We suggest how to implement additional spatial statistical methods within a GIS, including methods for using non-Euclidean distances in the analysis of geostatistical, lattice, and point pattern data.

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تاریخ انتشار 2003