【摘要】 遥感Rao’sQ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。更多还原

【Abstract】 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).更多还原