The investigation of any kind of extensive spatial phenomena - by means of geospatial data - requires dedicated analysis strategies and software tools in order to properly understand and represent their interactions within the geographical context. In this study, Exploratory Spatial Data Analysis (ESDA) is suggested to investigate underlying spatial patterns of the soil consumption phenomenon in Italy, together with its interplay with another likely linked macroeconomic variable, i.e. the average income per capita. The analysis is carried out for the whole Italian territory by considering data at a municipal level. A plugin for the Free Open Source Software (FOSS) QGIS, called Hotspot Analysis, is here presented and employed for the study. The output consists of maps depicting the spatial interaction of the investigated variables which can be readily used to identify where spatial clusters and/or outliers are located. Results provide with meaningful insights for the comprehension of soil consumption patterns in Italy and their representation through maps, by demonstrating the benefits given by the integration between ESDA and GIS functionalities.
Hotspot analysis, an open source GIS tool for exploratory spatial data analysis: Application to the study of soil consumption in Italy
Oxoli, Daniele;Molinari, Monia Elisa;Brovelli, Maria Antonia
2018-01-01
Abstract
The investigation of any kind of extensive spatial phenomena - by means of geospatial data - requires dedicated analysis strategies and software tools in order to properly understand and represent their interactions within the geographical context. In this study, Exploratory Spatial Data Analysis (ESDA) is suggested to investigate underlying spatial patterns of the soil consumption phenomenon in Italy, together with its interplay with another likely linked macroeconomic variable, i.e. the average income per capita. The analysis is carried out for the whole Italian territory by considering data at a municipal level. A plugin for the Free Open Source Software (FOSS) QGIS, called Hotspot Analysis, is here presented and employed for the study. The output consists of maps depicting the spatial interaction of the investigated variables which can be readily used to identify where spatial clusters and/or outliers are located. Results provide with meaningful insights for the comprehension of soil consumption patterns in Italy and their representation through maps, by demonstrating the benefits given by the integration between ESDA and GIS functionalities.File | Dimensione | Formato | |
---|---|---|---|
2018_ROL_Oxoli_et_al.pdf
Accesso riservato
:
Publisher’s version
Dimensione
2.69 MB
Formato
Adobe PDF
|
2.69 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.