HistMapR: rapid digitization of historical land-use maps in R
Auffret, Alistair G.; Kimberley, Adam; Plue, Jan; Skånes, Helle; Jakobsson, Simon; Waldén, Emelie; Wennbom, Marika; Wood, Heather; Bullock, James M. ORCID: https://orcid.org/0000-0003-0529-4020; Cousins, Sara A.O.; Gartz, Mira; Hooftman, Danny A.P.; Tränk, Louise. 2017 HistMapR: rapid digitization of historical land-use maps in R. Methods in Ecology and Evolution, 8 (11). 1453-1457. https://doi.org/10.1111/2041-210X.12788
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Abstract/Summary
1. Habitat destruction and degradation represent serious threats to biodiversity, and quantification of land-use change over time is important for understanding the consequences of these changes to organisms and ecosystem service provision. 2. Comparing land use between maps from different time periods allows estimation of the magnitude of habitat change in an area. However, digitizing historical maps manually is time-consuming and analyses of change are usually carried out at small spatial extents or at low resolutions. 3. HistMapR contains a number of functions that can be used to semi-automatically digitize historical land use according to a map's colours, as defined by the RGB bands of the raster image. We test the method on different historical land-use map series and compare results to manual digitizations. 4. Digitization is fast, and agreement with manually digitized maps of around 80–90% meets common targets for image classification. We hope that the ability to quickly classify large areas of historical land use will promote the inclusion of land-use change into analyses of biodiversity, species distributions and ecosystem services.
Item Type: | Publication - Article |
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Digital Object Identifier (DOI): | https://doi.org/10.1111/2041-210X.12788 |
UKCEH and CEH Sections/Science Areas: | Biodiversity (Science Area 2017-) UKCEH Fellows |
ISSN: | 2041-210X |
Additional Keywords: | biodiversity, fragmentation, GIS, habitat destruction, historical ecology, landscape ecology, land-use change, mapping, species distribution modelling |
NORA Subject Terms: | Ecology and Environment Data and Information |
Date made live: | 30 Nov 2017 12:29 +0 (UTC) |
URI: | https://nora.nerc.ac.uk/id/eprint/518543 |
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