中国森林遥感Rao’s Q指数逐年数据集(2000‒2017)  

Remote Sensing Rao's Q Index Yearly Forest Dataset of China(2000-2017)

作　　者：蒋啸 蔡红艳[1] 杨小唤[1,2] Jiang,X.;Cai,H.Y.;Yang,X.H.(State Key Laboratory of Resources and Environmental Information Systems,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室,北京100101 [2]中国科学院大学,北京100101

出　　处：《全球变化数据学报（中英文）》2024年第1期14-20,V0014-V0020,共14页Journal of Global Change Data & Discovery

基　　金：中华人民共和国科学技术部(2023FY101000,2017YFC0503803)。

摘　　要：遥感Rao’s Q指数能够表征宏观森林植物功能多样性,是生态质量评估的重要指标,对于有效开展区域生物多样性保护工作具有重要意义。基于传统的Rao’s Q指数定义,利用NDVI植被光谱差异,以像元值表示森林植物性状,以邻域像元值之差构建距离矩阵,在R语言平台上计算得到2000‒2017年的森林遥感Rao’s Q指数。数据时间分辨率为年,空间分辨率为5 km,投影方式为阿尔伯斯等面积投影,坐标系为WGS-84。数据集存储为.tif格式,由72个数据文件组成,数据量为58.2 MB。The remote sensing Rao's Q index can characterize the functional diversity of macro-forest plants,making it a crucial metric for evaluating ecological quality and essential to efficiently carry out tasks related to regional biodiversity protection.According to the traditional definition of Rao's Q index,the forest plant features are represented by pixel values in the spectral difference of the normalized difference vegetation index(NDVI),and the neighborhood pixel values are used to generate the distance matrix.The yearly remote sensing Rao's Q index dataset of forest in China from 2000 to 2017 was calculated on the R language platform.The temporal resolution of the data was annual,the spatial resolution was 5 km,and the projection was based on Albers Conical Equal Area with the coordinate system of WGS-84.The dataset is archived in the.tif format and consists of 72 data files with data size of 58.2 MB(compressed into one file with 5.17 MB).

关 键 词：遥感 Rao’s Q指数 2000‒2017 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置] S771.8[自动化与计算机技术—控制科学与工程]