Abstract:?Land cover is a natural condition of the land surface, presenting types and quantity of the observed (bio)physical cover, and spatial heterogeneity (e.g., landscape diversity), etc. It is shaped by the combined effect of natural processes and human activities. Land cover data play a crucial role of studies and applications of global change, matter and energy cycles. Remote sensing technology provides an important foundation of land cover change monitoring, and deepens understandings of driving mechanisms of land cover change and responses of landscape diversity. In this paper, the land cover data produced by the ESA Climate Change Initiative were applied to derive the plant functional type (PFT) ratio with continuous values from the discrete land cover type of the original data using a cross walking table after scaling. Then, the Shannon diversity index was calculated based on PFT. Finally, a dataset of land cover and landscape diversity of China and its adjacent areas (70-140°E, 15-55°N) from 1992 to 2018 with a resolution of 0.05° was produced. This dataset has the advantages of long time series, high resolution, and quantification. It can be applied to studies on regional vegetation coverage and landscape pattern dynamics. Besides, it can also provide basic maps for model simulation and remote sensing inversion.
Keywords:?land cover;?plant functional type;?Shannon diversity index;?remote sensing