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HistMapR: Rapid digitization of historical land‐use maps in R
Author(s) -
Auffret Alistair G.,
Kimberley Adam,
Plue Jan,
Skånes Helle,
Jakobsson Simon,
Waldén Emelie,
Wennbom Marika,
Wood Heather,
Bullock James M.,
Cousins Sara A.O.,
Gartz Mira,
Hooftman Danny A.P.,
Tränk Louise
Publication year - 2017
Publication title -
methods in ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.425
H-Index - 105
ISSN - 2041-210X
DOI - 10.1111/2041-210x.12788
Subject(s) - digitization , raster graphics , biodiversity , rgb color model , land use , land use, land use change and forestry , computer science , raster data , geography , cartography , land degradation , remote sensing , ecosystem services , ecosystem , environmental resource management , ecology , artificial intelligence , environmental science , computer vision , biology
Summary 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. 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. 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. 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.