CALC-2020: a new baseline land cover map at 10 m resolution for the circumpolar Arctic

• Main Authors: Liu, Chong, Xu, Xiaoqing, Feng, Xuejie, Cheng, Xiao, Liu, Caixia, Huang, Huabing
• Format: Text
• Language: English
• Published: 2022
• Subjects: Arctic; Climate change; Tundra
• Online Access: https://doi.org/10.5194/essd-2022-224; https://essd.copernicus.org/preprints/essd-2022-224/

The entire Arctic is rapidly warming, which brings in a multitude of environmental consequences far beyond the northern high-latitude limits. Land cover maps offer biophysical insights into the terrestrial environment and are therefore essential for understanding the transforming Arctic in the context of anthropogenic activity and climate change. Satellite remote sensing has revolutionized our ability to capture land cover information over large areas. However, circumpolar Arctic-scale fine resolution land cover mapping has been so far lacking. Here, we utilize a combination of multimode satellite observations and topographic data at 10 m resolution to provide a new baseline land cover product (CALC-2020) across the entire terrestrial Arctic for circa 2020. Accuracy assessments suggest that the CALC-2020 product exhibits satisfactory performances, with overall accuracies of 79.63 % and 67.27 %, respectively, at validation sample locations and field/flux tower sites. The derived land cover map also displays reasonable agreement with three pre-existing global products, meanwhile depicting much more subtle polar biome patterns. Based on the CALC-2020 dataset, we show that over half of the Arctic landmass is covered by graminoid tundra or lichen/moss. Spatially, the land cover distribution exhibits regional dominance, reflecting the complex suite of both biotic and abiotic processes that jointly determine the Arctic landscape. The CALC-2020 product we developed can be used to improve earth system modelling, and benefit the ongoing efforts on sustainable Arctic land management by public and non-governmental sectors. The CALC-2020 land cover product is freely available on Science Data Bank: http://cstr.cn/31253.11.sciencedb.01869 (Xu et al., 2022a).