摘要
在"一带一路"倡议背景下,中国对外投资或承建的重大互联互通基础设施工程对当地环境的影响引起了国际社会的广泛关注,本文选择10个重大互联互通工程,采用遥感技术手段和Landsat-8遥感影像生产各工程沿线10km缓冲区内的植被覆盖度数据集。该数据集是以Landsat-8 Operational Land Imager(OLI)光学影像为基础数据,首先在Google Earth Engine云平台上计算归一化差异植被指数(Normalized Difference Vegetation Index,NDVI),然后合成研究区内2017年度最大NDVI,以此数据为本底,采用像元二分模型方法计算得到植被覆盖度数据集。植被覆盖度数值介于0–1之间。0表示无植被覆盖,数值越高表明植被覆盖程度越好。该数据集空间分辨率为30 m,存储为.tif格式,由30个文件组成,数据量为7.5 GB(压缩为10个文件,数据量516MB),可为工程建设对当地植被生态系统的影响等相关研究提供客观、科学的基础数据。
In the background of the Belt and Road Initiative,influences of key interconnection infrastructure projects invested or constructed by China on local environment have attracted wide attentions from the international society.In this study,10 key interconnection projects were chosen.Vegetation coverage dataset in the buffer zone of 10 km along these 10 projects was produced by the remote-sensing technical means and Landsat-8 remote-sensing image.This dataset used Landsat-8 Operational Land Imager(OLI)optical images as basic data.Firstly,the normalized difference vegetation index(NDVI)was calculated on the Google Earth Engine.Secondly,the annual maximum NDVI of the study area in 2017 was composited.Based on this annual maximum NDVI,the vegetation coverage dataset was calculated by the pixel binary model method.The fraction of vegetation coverage(FVC)ranged between 0 and 1,where 0 represented no vegetation coverage.Higher numerical values implied the better vegetation coverage.The spatial resolution of this dataset was 30 m and the dataset was archived in.tif format.It is consisted of 30 files,with a data size of 7.5 GB(compressed to 10 files,516 MB).This dataset can provide objective and scientific basic data for relevant studies concerning influences of engineering construction on local vegetation ecosystems.
作者
田海峰
牛铮
柳钦火
邬明权
付丹敏
李丽
吴俊君
裴杰
龚围
成陆
仲波
Tian,H.F;Niu,Z;Liu,Q.H;Wu,M.Q;Fu,D.M;Li,L;Wu,J.J;Pei,J;Gong,W;Cheng,L;Zhong,B(The State Key Laboratory of Remote Sensing Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences,Beijing 100101,China;College of Resources and Environment,Chinese Academy of Sciences,Beijing 100049,China;School of Land Science and Technology,China University of Geosciences(Beijing),Beijing 100083,China)
出处
《全球变化数据学报（中英文）》
CSCD
2019年第1期27-33,136-142,共14页
Journal of Global Change Data & Discovery
基金
中国科学院(XDA19030304)
国家自然科学基金(41730107,41771465).
