Ecological Security Assessment of "Grain-for-Green" Program Typical Areas in Northern China Based on Multi-Source Remote Sensing Data

被引:2
作者
Liu, Xingtao [1 ,2 ]
Li, Hang [1 ]
Wang, Shudong [1 ,3 ]
Liu, Kai [1 ,3 ]
Li, Long [1 ,2 ]
Li, Dehui [1 ,2 ]
机构
[1] Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100194, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteorol, Nanjing 210044, Peoples R China
关键词
ecological security assessment; Grain-for-Green; P-S-R; early warning; YELLOW-RIVER BASIN; LAND-COVER; VEGETATION; CONVERSION; TRADEOFFS; DYNAMICS; PLATEAU;
D O I
10.3390/rs15245732
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Inner Mongolia segment of the Yellow River basin (IMYRB) is a typical area for ecological restoration in China. At the end of the 20th century, influenced by climate and human activities, such as mining, grazing, and farmland abandonment, the ecological security of the IMYRB was under more significant pressure. To alleviate the pressure on natural ecosystems and improve the fragile ecological situation, China implemented the "Grain-for-Green" (GFG) project in 1999. However, the evolutionary characteristics of the ecological security of the IMYRB in the first two decades of the 21st century are still lacking. Quantitative and long-term ecological security information of "Grain-for-Green" is needed. Based on this, this study used the "Pressure (P)-State (S)-Response (R)" method and proposed an ecological security assessment and early warning system based on multi-source remote sensing data. The evaluation results indicated a significant improvement in ecological security in the IMYRB from 2000 to 2020. Compared to 2000, the ecological security of the IMYRB had improved significantly in 2020, with an increase of 11.02% (ES > 0.65) and a decrease of 8.89% (ES < 0.35). For the early warning aspect of ecological security, there was a 26.31% growth in non-warning areas, with a 5% decrease in warning areas. Based on the analysis of ecologically critical factors, we proposed the implications for future ecological management as follows. (1) In ecologically fragile areas such as the IMYRB, continued implementation of the GFG was necessary. (2) Vegetation restoration should be scientific and tailored adaptive. (3) The protection of arable land also showed necessity. (4) The grazing management skills should be upgraded. Our study demonstrated that the ecological benefits derived from the "GFG" project are not immediate but cumulative and persistent. The continuous implementation of "GFG" will likely alleviate the pressure exerted by human activities on the natural environment.
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页数:17
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共 46 条
[41]   A novel alpine land cover classification strategy based on a deep convolutional neural network and multi-source remote sensing data in Google Earth Engine [J].
Qichi, Yang ;
Lihui, Wang ;
Jinliang, Huang ;
Linzhi, Liu ;
Xiaodong, Li ;
Fei, Xiao ;
Yun, Du ;
Xue, Yan ;
Feng, Ling .
GISCIENCE & REMOTE SENSING, 2023, 60 (01)
[42]   Sensitive Feature Evaluation for Soil Moisture Retrieval Based on Multi-Source Remote Sensing Data with Few In-Situ Measurements: A Case Study of the Continental US [J].
Zhang, Ling ;
Zhang, Zixuan ;
Xue, Zhaohui ;
Li, Hao .
WATER, 2021, 13 (15)
[43]   Three-Stage Up-Scaling and Uncertainty Estimation in Forest Aboveground Biomass Based on Multi-Source Remote Sensing Data Considering Spatial Correlation [J].
Ding, Xiangyuan ;
Chen, Erxue ;
Zhao, Lei ;
Fan, Yaxiong ;
Wang, Jian ;
Ma, Yunmei .
REMOTE SENSING, 2025, 17 (04)
[44]   Performance Evaluation of Mangrove Species Classification Based on Multi-Source Remote Sensing Data Using Extremely Randomized Trees in Fucheng Town, Leizhou City, Guangdong Province [J].
Wang, Xinzhe ;
Tan, Linlin ;
Fan, Jianchao .
REMOTE SENSING, 2023, 15 (05)
[45]   Quantification of spatial temporal variability of snow cover and hydro-climatic variables based on multi-source remote sensing data in the Swat watershed, Hindukush Mountains, Pakistan [J].
Anjum, Muhammad Naveed ;
Ding, Yongjian ;
Shangguan, Donghui ;
Liu, Junguo ;
Ahmad, Ijaz ;
Ijaz, Muhammad Wajid ;
Khan, Muhammad Imran .
METEOROLOGY AND ATMOSPHERIC PHYSICS, 2019, 131 (03) :467-486
[46]   Assessing the effects of 2D/3D urban morphology on the 3D urban thermal environment by using multi-source remote sensing data and UAV measurements: A case study of the snow-climate city of Changchun, China [J].
Yang, Chaobin ;
Zhu, Wenhao ;
Sun, Jiabin ;
Xu, Xinliang ;
Wang, Ranghu ;
Lu, Yuefeng ;
Zhang, Shuwen ;
Zhou, Weiqi .
JOURNAL OF CLEANER PRODUCTION, 2021, 321