摘要
土地荒漠化是目前世界上最为严重的生态环境问题之一。监测土地荒漠化动态变化,掌握其变化规律对防治荒漠化有很重要的意义。中巴经济走廊是“一带一路”的重要组成部分,全长约3000公里,其中1300余公里为严寒高原、干旱和荒漠区段。尤其是在南段,干旱和大面积荒漠是其主要的生态环境约束因素。本文采用荒漠化差值指数(DDI)评价中巴经济走廊荒漠化程度,以归一化植被指数(NDVI)与地表反照率(Albedo)为监测指标,通过构造Albedo-NDVI特征空间,并利用Albedo和NDVI之间负相关的关系,构建DDI公式,完成2000–2017年中巴经济走廊荒漠化分类专题数据集。并通过高分辨率Landsat数据反演的植被覆盖度验证本数据集的质量和精度。以2010年数据为例,总体评价精度达到81.67%,Kappa系数为75.42%。本数据集直观反映中巴经济走廊荒漠化程度,为定量评价此区域的荒漠化严重程度提供参考,并为中巴经济走廊沿线国家进行荒漠化防治工作以及宏观决策的制定提供基础资料。
Desertification has caused severe ecological environment problems worldwide.It is very important to monitor the dynamic change of land desertification and grasp its change rule.The China-Pakistan Economic Corridor is critical part of the One Belt And One Road.The Corridor is about 3,000 kilometers long,covering more than 1,300 kilometers of permafrost,arid and desert regions.Especially its southern section is characterized by drought and large-scale desert,which constitutes the Corridor’s major ecological constraints.In this study,desertification difference index(DDI)was used to evaluate the degree of desertification in the Corridor.Based on Normalized Difference Vegetation Index(NDVI)and Albedo,we established the Albedo-NDVI space and a DDI formula through negative correlation between Albedo and NDVI.Based on DDI,we built the dataset of desert distributions along the China-Pakistan Economic Corridor during 2000–2017.The quality and accuracy of the dataset were verified by vegetation coverage inversed by Landsat ETM+.Taking 2010 data as an example,the overall evaluation accuracy reached 81.67%,and the Kappa coefficient was 75.42%.The dataset reflects the degree of desertification along the Corridor,providing information for desertification prevention and control in the countries around.
作者
敏玉芳
冯克庭
康建芳
艾鸣浩
Min Yufang;Feng Keting;Kang Jianfang;Ai Minghao(University of Chinese Academy of Science,Beijing 100049,P.R.China;Scientific Big Data Center,Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,P.R.China;Service Center,National Special Environment and Function of Observation and Research Stations Shared Service Platform,Lanzhou 730000,P.R.China)
基金
国家科技基础条件平台建设数据共享服务项目(Y719H71006)
十三五中国科学院信息化专项(XXH13506和XXH13505)
