{"title":"Comparison of DEM-derived determinants for modelling of long-term land cover change in a large scale: case studies from Slovak Western Carpathians","authors":"M. Druga, Adam Rusinko","doi":"10.33542/gc2023-1-02","DOIUrl":null,"url":null,"abstract":"Studies detecting land use/cover change (LUCC) in large scales are increasing in number, and so are the studies identifying spatial determinants of these changes and creating their models. Raster datasets derived from digital elevation models (DEM) belong to a limited group of determinants that are relatively available for LUCC modelling in large scales. This study compares the performance of 12 DEM-derived determinants in models of six distinct land cover changes: urbanisation, industrialisation, agricultural intensification and extensification, afforestation, and deforestation. The changes were identified in the 1949-2010 period in a reference scale of 1:10 000 on a total area of 176 km2 of 12 municipalities systematically selected to partially represent Western Carpathians in Slovakia. Nearly 45% of the area changed; afforestation, agricultural extensification and intensification were the most prevalent changes. Logistic regression and hierarchical partitioning were used to quantify the influence of the determinants on them. Among other commonly used determinants (elevation, slope, cost distance), vertical dissection and duration of solar radiation had an unexpectedly high influence, mostly on agricultural intensity and forest changes. However, further research is needed to verify these influences in other areas and to provide their sufficient causal interpretation.","PeriodicalId":42446,"journal":{"name":"Geographia Cassoviensis","volume":"1 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geographia Cassoviensis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.33542/gc2023-1-02","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOGRAPHY","Score":null,"Total":0}
引用次数: 0
Abstract
Studies detecting land use/cover change (LUCC) in large scales are increasing in number, and so are the studies identifying spatial determinants of these changes and creating their models. Raster datasets derived from digital elevation models (DEM) belong to a limited group of determinants that are relatively available for LUCC modelling in large scales. This study compares the performance of 12 DEM-derived determinants in models of six distinct land cover changes: urbanisation, industrialisation, agricultural intensification and extensification, afforestation, and deforestation. The changes were identified in the 1949-2010 period in a reference scale of 1:10 000 on a total area of 176 km2 of 12 municipalities systematically selected to partially represent Western Carpathians in Slovakia. Nearly 45% of the area changed; afforestation, agricultural extensification and intensification were the most prevalent changes. Logistic regression and hierarchical partitioning were used to quantify the influence of the determinants on them. Among other commonly used determinants (elevation, slope, cost distance), vertical dissection and duration of solar radiation had an unexpectedly high influence, mostly on agricultural intensity and forest changes. However, further research is needed to verify these influences in other areas and to provide their sufficient causal interpretation.
期刊介绍:
Geographia Cassoviensis is a biannual peer-reviewed journal published by the Pavol Jozef Šafárik University in Košice since 2007. It is available both in print and open-access electronic version. The journal publishes original research articles from Geography and other closely-related research fields. Since 2016 the journal is indexed in SCOPUS and ERIH PLUS - European Reference Index for Humanities and Social Sciences, and since 2017 also in Emerging Sources Citation Index by Clarivate Analytics.