Dormant categories and spatial resolution affect the perception of land cover change model performance

Most models of land cover change predict change using physical and socio-economic factors in raster grids where temporal and spatial scales must be selected to optimize prediction and calculation time. This study tests the impacts of spatial extent and spatial resolution (cell size) on land cover ch...

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Autores principales:	Hari G. Roy, Dennis M. Fox, Karine Emsellem
Formato:	article
Lenguaje:	DE EN FR IT PT
Publicado:	Unité Mixte de Recherche 8504 Géographie-cités 2016
Materias:	land cover landscape modeling/modelling Land Change Modeler area spatial resolution Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/e2c20212c3c3467988fe5d11821966b7
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id	oai:doaj.org-article:e2c20212c3c3467988fe5d11821966b7
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spelling	oai:doaj.org-article:e2c20212c3c3467988fe5d11821966b72021-12-02T11:14:05ZDormant categories and spatial resolution affect the perception of land cover change model performance1278-336610.4000/cybergeo.27794https://doaj.org/article/e2c20212c3c3467988fe5d11821966b72016-09-01T00:00:00Zhttp://journals.openedition.org/cybergeo/27794https://doaj.org/toc/1278-3366Most models of land cover change predict change using physical and socio-economic factors in raster grids where temporal and spatial scales must be selected to optimize prediction and calculation time. This study tests the impacts of spatial extent and spatial resolution (cell size) on land cover change modelling. Spatial extent here is equivalent to increasing the area of a dormant category. Two extents (33.6 km² and 79.1 km²) and three resolutions (25 m, 50 m and 100 m) were tested on study zones located in SE France in the Var department. The 50 m and 100 m resolutions were downscaled back to 25 m and compared to the initial 25 m maps. Land cover maps dated from 1950, 1982, 2003 and 2011, and IDRISI’s Land Change Modeler (LCM) was used to predict 2011. Dormant category improved Cramer’s V values (1.3 to 1.5 time greater) and quantity and allocation disagreement values. Actual change predictions were similar for the two zones, but the high persistent forest in the large window artificially improved prediction statistics, so increasing dormant category area (spatial extent) artificially inflates prediction statistics. Spatial resolution appeared to have little impact at first, but upscaling/downscaling revealed that coarser cell sizes lose predictive power (1.5-2 times greater allocation errors). The dormant category area should be minimized and upscaling/downscaling should be done if data are modelled at coarser resolutions than original cell size.Hari G. RoyDennis M. FoxKarine EmsellemUnité Mixte de Recherche 8504 Géographie-citésarticleland coverlandscape modeling/modellingLand Change Modelerareaspatial resolutionGeography (General)G1-922DEENFRITPTCybergeo (2016)
institution	DOAJ
collection	DOAJ
language	DE EN FR IT PT
topic	land cover landscape modeling/modelling Land Change Modeler area spatial resolution Geography (General) G1-922
spellingShingle	land cover landscape modeling/modelling Land Change Modeler area spatial resolution Geography (General) G1-922 Hari G. Roy Dennis M. Fox Karine Emsellem Dormant categories and spatial resolution affect the perception of land cover change model performance
description	Most models of land cover change predict change using physical and socio-economic factors in raster grids where temporal and spatial scales must be selected to optimize prediction and calculation time. This study tests the impacts of spatial extent and spatial resolution (cell size) on land cover change modelling. Spatial extent here is equivalent to increasing the area of a dormant category. Two extents (33.6 km² and 79.1 km²) and three resolutions (25 m, 50 m and 100 m) were tested on study zones located in SE France in the Var department. The 50 m and 100 m resolutions were downscaled back to 25 m and compared to the initial 25 m maps. Land cover maps dated from 1950, 1982, 2003 and 2011, and IDRISI’s Land Change Modeler (LCM) was used to predict 2011. Dormant category improved Cramer’s V values (1.3 to 1.5 time greater) and quantity and allocation disagreement values. Actual change predictions were similar for the two zones, but the high persistent forest in the large window artificially improved prediction statistics, so increasing dormant category area (spatial extent) artificially inflates prediction statistics. Spatial resolution appeared to have little impact at first, but upscaling/downscaling revealed that coarser cell sizes lose predictive power (1.5-2 times greater allocation errors). The dormant category area should be minimized and upscaling/downscaling should be done if data are modelled at coarser resolutions than original cell size.
format	article
author	Hari G. Roy Dennis M. Fox Karine Emsellem
author_facet	Hari G. Roy Dennis M. Fox Karine Emsellem
author_sort	Hari G. Roy
title	Dormant categories and spatial resolution affect the perception of land cover change model performance
title_short	Dormant categories and spatial resolution affect the perception of land cover change model performance
title_full	Dormant categories and spatial resolution affect the perception of land cover change model performance
title_fullStr	Dormant categories and spatial resolution affect the perception of land cover change model performance
title_full_unstemmed	Dormant categories and spatial resolution affect the perception of land cover change model performance
title_sort	dormant categories and spatial resolution affect the perception of land cover change model performance
publisher	Unité Mixte de Recherche 8504 Géographie-cités
publishDate	2016
url	https://doaj.org/article/e2c20212c3c3467988fe5d11821966b7
work_keys_str_mv	AT harigroy dormantcategoriesandspatialresolutionaffecttheperceptionoflandcoverchangemodelperformance AT dennismfox dormantcategoriesandspatialresolutionaffecttheperceptionoflandcoverchangemodelperformance AT karineemsellem dormantcategoriesandspatialresolutionaffecttheperceptionoflandcoverchangemodelperformance
_version_	1718396143415590912

Dormant categories and spatial resolution affect the perception of land cover change model performance

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