High-resolution global land-use maps from 1960 to 2100 for biodiversity modelling

Global-scale land-use and land-cover (LULC) datasets are essential for predicting biodiversity futures and developing solutions to the related challenges of biodiversity loss, climate change, and food security. Existing harmonised LULC datasets, that is without discontinuities when moving from past to present, have coarse spatial and temporal resolutions that do not match the scale on which environmental processes occur. Additionally, current harmonised LULC datasets do not consider landscape patterns, which are important for processes such as species movement and hydrological dynamics.
We present a downscaled global LULC dataset for five future socioeconomic and climatic scenarios, with 0.01° spatial (approximately 1 km at the equator) and yearly temporal resolutions, that is harmonised with historic LULC to span the period 1960 to 2100. Future LULC projections were generated by downscaling LULC change from a global land system model, LandSyMM, from 0.5° to 0.01° using the LandScaleR algorithm. Prior to downscaling, we calibrated LandScaleR with historic LULC data to ensure that it produced realistic landscape patterns. The spatial variation of historic LULC change was used to inform the spatial patterns of future change during the downscaling process. Calibration of LandScaleR revealed substantial regional variation in past patterns of LULC change. The future LULC projections indicate significant landscape change, and emphasise the importance of incorporating local-scale processes in global LULC projections.
Our harmonised LULC dataset will be beneficial for studying the impacts of LULC change on biodiversity because it was calibrated to ensure that future LULC projections have realistic landscape patterns. The dataset also has high spatial and temporal resolutions that better match the scale of environmental processes compared to existing products. We anticipate that our harmonised dataset will facilitate the integration of LULC with a range of environmental models, including those that model biodiversity, ecosystem services, fire, and hydrology. Overall, this new dataset offers an important tool for informing spatial planning and policy design, and addressing challenges including biodiversity loss and climate change.