首页 | 本学科首页   官方微博 | 高级检索  
     检索      

2000年来中国生态状况时空变化格局
引用本文:何盈利,尤南山,崔耀平,肖桐,郝媛媛,董金玮.2000年来中国生态状况时空变化格局[J].自然资源学报,2021,36(5):1176-1185.
作者姓名:何盈利  尤南山  崔耀平  肖桐  郝媛媛  董金玮
作者单位:1.中国科学院地理科学与资源研究所陆地表层格局与模拟重点实验室,北京 1001012.中国科学院大学资源与环境学院,北京 1000493.河南大学环境与规划学院,开封 4750044.生态环境部卫星环境应用中心,北京 1000945.蒙草生态大数据研究院,呼和浩特 010000
基金项目:中国科学院战略性先导科技专项(XDA19040301)
摘    要:21世纪以来,我国在经济快速发展的同时高度重视生态环境保护,一系列生态修复工程和空间管控措施使生态状况发生了巨大变化;然而目前对于全国生态状况宏观格局的认识仍十分有限。借助 Google Earth Engine(GEE)遥感云计算平台,采用主成分分析方法和MODIS数据构建的绿度NDVI、热度LST、湿度WET和干度NDSI四个指标,生成长时间序列的遥感生态指数RSEI数据集,完整刻画了中国2000年来生态状况的时空连续变化格局。研究发现:在空间格局上,东南沿海地区生态状况优于西北地区;变化趋势上,全国生态状况除上海、西藏和澳门之外均显著改善,RSEI增长最多的三个省份为山西、陕西和河北。进一步采用遥感云计算定量评价了2000年来生态状况变化的宏观格局,以期为国土空间管控和生态保护提供科学支持。

关 键 词:生态状况  遥感生态指数RSEI  遥感云计算  MODIS  GEE  时空分析  
收稿时间:2020-05-11
修稿时间:2021-01-14

Spatio-temporal changes in remote sensing-based ecological index in China since 2000
HE Ying-li,YOU Nan-shan,CUI Yao-ping,XIAO Tong,HAO Yuan-yuan,DONG Jin-wei.Spatio-temporal changes in remote sensing-based ecological index in China since 2000[J].Journal of Natural Resources,2021,36(5):1176-1185.
Authors:HE Ying-li  YOU Nan-shan  CUI Yao-ping  XIAO Tong  HAO Yuan-yuan  DONG Jin-wei
Abstract:Since the beginning of the 21st century, China has responded to a national land-system sustainability emergency via an integrated portfolio of large-scale programmes. A series of ecological restoration projects and land regulating and planning policies have been implemented for sustainable development, which substantially improved the security status of the country's ecology. However, comprehensive assessments of the ecological status based on objective data and framework are still limited. Remote sensing-based ecological index (RSEI) has been proposed as an objective and effective approach for assessing ecological security on a regional scale. However, a national scale application has not been conducted yet. Here we generated the annual RSEI products from 2000 to 2019 by using four indicators (Normalized Difference Vegetation Index (NDVI), Normalized Difference Soil Index (NDSI), Wetness Index (Wet), and Land Surface Temperature (LST) based on Moderate Resolution Imaging Spectroradiometer (MODIS) data as well as the Google Earth Engine (GEE)-a cloud computing platform. The results showed that the multi-year average RSEI showed higher values in the southeast coastal regions compared with the northwestern regions, the regions with superior hydrothermal conditions have high RSEI values, while the arid and semi-arid inland areas with higher elevations and cold-dry climates have low RSEI values and fragile ecological conditions. In general, the whole country experienced a significant improvement of RSEI, and all the provincial-level regions in China, except Shanghai, Tibet, and Macao, have shown an increasing RSEI. The three provinces with the fastest growing rates were Shanxi, Shaanxi, and Hebei, with increases of 0.29, 0.25, and 0.19, respectively. The RSEI increased significantly in the Northeast China Plain, Loess Plateau, south and north of the North China Plain, the north of the middle and lower reaches of the Yangtze River Plain, and the south of the Junggar Basin in the northwest desert region, while the RSEI decreased in the Tianshan Mountain range, the southwest of the Qinghai-Tibet Plateau, the central part of the North China Plain and the Yangtze River Delta. This study quantitatively evaluated the macro patterns of RSEI changes based on GEE since 2000, and expecte to support decision making on land use management and ecological protection.
Keywords:ecological status  remote sensing-based ecological index (RSEI)  remote sensing cloud computing  MODIS  Google Earth Engine (GEE)  spatio-temporal analysis  
点击此处可从《自然资源学报》浏览原始摘要信息
点击此处可从《自然资源学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号