R.pi: A grass gis package for semi‐automatic spatial pattern analysis of remotely sensed land cover data. Issue 1 (25th July 2017)

• Record Type: Journal Article
• Authors: Wegmann, Martin; Leutner, Benjamin F.; Metz, Markus; Neteler, Markus; Dech, Stefan; Rocchini, Duccio
• Editors: Golding, Nick
• Is Part Of: Methods in ecology and evolution. Volume 9:Issue 1(2018)
• Page Start: 191
• Page End: 199
• Publication Date: 2017-07-25
• Subjects: connectivity -- GIS -- landscape fragmentation -- patch irreplaceability -- remote sensing -- spatial ecology; Ecology -- Periodicals; Evolution -- Periodicals; 577
• DOI: 10.1111/2041-210X.12827
• Languages: English
• ISSNs: 2041-210X

Abstract

Abstract: Analysing the changing spatial patterns of landscapes due to climate change or anthropogenic impact is important for various disciplines. Land cover change and its resulting modification of spatial patterns in the landscape influence various geographical or ecological parameters. Changing formerly continuous into discontinuous ecosystems due to land cover conversion causes isolated fragments in the landscape. Maintaining the connectivity of a fragmented landscape is relevant for, e.g. in nutrient cycle, water‐runoff or species population persistence. Satellite imagery derived land cover can be used to analyse continuously the changing spatial arrangement of land cover types. However, analyses are computer intensive and require robust and efficient processing routines. We developed a patch‐based spatial analysis system ( r.pi ) integrated natively into a Free and Open Source GIS (grass gis ) to be able to analyse large amounts of satellite derived land cover data in a semi‐automatic manner, and to ensure high reproducibility and robustness. Various established and newly developed indices for spatial pattern analysis are provided in this program, to derive further meaningful information like spatial configuration, patch irreplaceability or connectivity of fragments based on a dispersal model approach.