The analysis of spatial autocorrelation is a fundamental tool for the understanding of all the physical as well as anthropological processes which naturally take place within the geographical space, and which cannot be studied independently from it. The deployment of statistical techniques for investigating spatial autocorrelation has brought valuable results within manifold research fields ranging from the natural sciences to the socio-economic sciences. Moreover, the affinity between cartography and this kind of analysis has raised particular interest among GIS users as well as developers. This has led to the inclusion of many modules dedicated to the spatial autocorrelation mapping within both proprietary GIS software suites as well as free and open source programming libraries. Nevertheless, specific functionalities for spatial autocorrelation mapping have not yet been formally included-through dedicated user interfaces-within the most popular free and open source GIS software, such as QGIS. We present here the Hotspot Analysis Plugin, an experimental QGIS plugin-dedicated to the spatial autocorrelation mapping-based on the free and open source Python library PySAL (Python Spatial Analysis Library). Together with the technical specifications, two relevant examples of the plugin usage-connected to real case studies- A re reported. These are: The detection of significant variations in soil consumption for the Lombardy Region (northern Italy) and the spatial correlation analysis of performance indicators characterizing Airbnb(tm) lodgings for the city of Venice (Italy).

Enabling spatial autocorrelation mapping in QGIS: The Hotspot Analysis Plugin

BERTOCCHI, DARIO;
2017-01-01

Abstract

The analysis of spatial autocorrelation is a fundamental tool for the understanding of all the physical as well as anthropological processes which naturally take place within the geographical space, and which cannot be studied independently from it. The deployment of statistical techniques for investigating spatial autocorrelation has brought valuable results within manifold research fields ranging from the natural sciences to the socio-economic sciences. Moreover, the affinity between cartography and this kind of analysis has raised particular interest among GIS users as well as developers. This has led to the inclusion of many modules dedicated to the spatial autocorrelation mapping within both proprietary GIS software suites as well as free and open source programming libraries. Nevertheless, specific functionalities for spatial autocorrelation mapping have not yet been formally included-through dedicated user interfaces-within the most popular free and open source GIS software, such as QGIS. We present here the Hotspot Analysis Plugin, an experimental QGIS plugin-dedicated to the spatial autocorrelation mapping-based on the free and open source Python library PySAL (Python Spatial Analysis Library). Together with the technical specifications, two relevant examples of the plugin usage-connected to real case studies- A re reported. These are: The detection of significant variations in soil consumption for the Lombardy Region (northern Italy) and the spatial correlation analysis of performance indicators characterizing Airbnb(tm) lodgings for the city of Venice (Italy).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10278/3693514
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