This study aims at analyzing analogies and differences between the spatial relations regarding land surface temperature (LST) and land covers in May and August 2019. Land cover data are drawn from the most updated spatial datasets available from Copernicus, while LST is retrieved from Landsat 8 satellite images made available by the U.S. Geological Survey. The methodology couples GIS spatial analysis and regression analysis; the latter is used to implement spatial inferential analysis as regards LST. Moreover, on the basis of a “what if” assessment, the impact of future afforestation, as regards rural areas, is detected with respect to decrease in LST, building on the outcomes of the model which relates LST to land cover types. The Sardinian region is taken as case study because its climate homogeneity and its self-containment allow for a pretty straightforward identification of the regional boundaries. The correlation between the spatial distribution of LST and land cover reveals, in the two time periods, that urbanization and the spatial dynamics of heating phenomena are closely connected. The methodology can be easily implemented in other regional contexts, and comparison of analogies and differences are quite effective and useful in identifying stylized facts and policy implications.

Land surface temperature and land cover dynamics. A study related to Sardinia, Italy

Lai, Sabrina;Leone, Federica;Zoppi, Corrado
2020-01-01

Abstract

This study aims at analyzing analogies and differences between the spatial relations regarding land surface temperature (LST) and land covers in May and August 2019. Land cover data are drawn from the most updated spatial datasets available from Copernicus, while LST is retrieved from Landsat 8 satellite images made available by the U.S. Geological Survey. The methodology couples GIS spatial analysis and regression analysis; the latter is used to implement spatial inferential analysis as regards LST. Moreover, on the basis of a “what if” assessment, the impact of future afforestation, as regards rural areas, is detected with respect to decrease in LST, building on the outcomes of the model which relates LST to land cover types. The Sardinian region is taken as case study because its climate homogeneity and its self-containment allow for a pretty straightforward identification of the regional boundaries. The correlation between the spatial distribution of LST and land cover reveals, in the two time periods, that urbanization and the spatial dynamics of heating phenomena are closely connected. The methodology can be easily implemented in other regional contexts, and comparison of analogies and differences are quite effective and useful in identifying stylized facts and policy implications.
2020
Land surface temperature; Land cover; Regulating ecosystem services
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/304113
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