Data4Land: How to enrich land-use/land-cover with historical vector(s)

Abstract

Land-use/land-cover (LULC) datasets produced from remote sensing may not consistently capture small/linear features of interest, including ecological barriers, eg. roads, railways and water objects. To overcome this challenge, a flexible workflow was developed to enrich the LULC with vector data (OpenStreetMap and World Database on Protected Areas). Users apply the Data4Land tool through a series of Jupyter Notebooks that address different mandatory and optional functions. The tool was used to enrich example LULC datasets and compute habitat connectivity indices for Catalonia (Spain) and Northern England. If vector data represent ecological barriers, connectivity indices tend to drop at all scales once the enriched LULC datasets are implemented.