Landsat-derived impervious surface area expansion in the Arctic from 1985 to 2021

Abstract

Accurate and timely impervious surface mapping is essential for assessing land cover change, urban heat island, and monitoring human activity intensity and ecological change. While various global impervious surface datasets become available, these datasets exhibit significant omissions in Arctic regions. Hence, in this study, we present a 30-m impervious surface area (ISA) dataset of Arctic from 1985 to 2021 (GISA_Arcitc). To this aim, we proposed to combine visually interpreted ISA samples and automatically generated NonISA samples for Arctic ISA mapping. Then, adaptive random forest (RF) classifiers were used for long time-series ISA mapping and the result was post-processed to improve the spatial-temporal consistency. Finally, the accuracy of GISA_Arcitc was assessed using the 37,800 independent test samples. GISA_Arctic possessed an overall accuracy of 93.59 % and a F-score of 0.934. It is found that the Arctic ISA increased from 857.83 km2 to 2115.49 km2 during the past 37 years. More than 84 % of the Arctic ISA increment is embraced by three countries: Russia, Finland, and Norway. Courtesy of the long time-series GISA_Arctic, the sources of Arctic ISA expansion were further analyzed. It was found that the top three land covers transformed to ISA are tundra, forest and grassland. The GISA_Arctic could contribute to further understanding of human activities and Arctic ecological changes, which can be accessed from http://irsip.whu.edu.cn/resources/resources_v2.php.