摘要
土地覆盖是陆地表层的自然状态,表现为地表覆盖的类型、数量以及空间异质性特征(如景观多样性)等,是自然过程和人类活动共同作用的结果。土地覆盖数据是全球变化、物质与能量循环等研究和应用的基础数据。遥感技术为土地覆盖变化监测提供重要支撑,加深了人们对于土地覆盖变化的驱动机制以及景观多样性响应的认识。本文以欧空局气候变化中心生产的土地覆盖数据为基础,利用交叉步行表,经尺度转换将原数据的离散土地覆盖类型转换为具有连续数值的植被功能类型比例,并基于此计算香农多样性指数,生产得到1992–2018年逐年0.05°的中国及其毗邻地区(70°E–140°E,15°N–55°N)土地覆盖与香农多样性指数数据集。本数据集具有时序长、分辨率高、定量化等优点,可应用于区域的植被覆盖、景观格局动态等方面的研究,也可为模型模拟、遥感反演等研究提供基础底图。
Land cover,a natural condition of the land surface,presents 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 in studies and applications of global change,matter and energy cycles.The remote sensing technology provides an important foundation for land cover change monitoring,and deepens the understanding of driving mechanisms of land cover change and responses of landscape diversity.Based on the land cover data produced by the ESA Climate Change Initiative,we derived the plant functional type(PFT)ratio with continuous values from the discrete land cover type of the original data by using a cross walking table after scaling.Then,we calculated the Shannon’s diversity index on the basis of PFT.Finally,we obtained a dataset of land cover and Shannon’s diversity index of China and its adjacent areas(70°E–140°E,15°N–55°N)from 1992 to 2018 with a resolution of 0.05°.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.
作者
严涛
金佳鑫
朱青松
刘颖
YAN Tao;JIN Jiaxin;ZHU Qingsong;LIU Ying(College of Hydrology and Water Resources,Hohai University,Nanjing 211100,P.R.China;National Earth System Science Data Center,National Science&Technology Infrastructure of China,Beijing 100101,P.R.China;College of Global Change and Earth System Science,Beijing Normal University,Beijing 100875,P.R.China)
基金
国家重点研发计划项目(2018YFA0605402)
国家自然科学基金(41971374)
中央高校基本科研业务费项目(B200202016)。