{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T23:03:50Z","timestamp":1771023830711,"version":"3.50.1"},"reference-count":89,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T00:00:00Z","timestamp":1702598400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Program of the Institute","award":["E2Z211020F"],"award-info":[{"award-number":["E2Z211020F"]}]},{"name":"Key Program of the Institute","award":["NO. 42141007"],"award-info":[{"award-number":["NO. 42141007"]}]},{"name":"Key Program of the Institute","award":["2022-soical-key-4-1-1"],"award-info":[{"award-number":["2022-soical-key-4-1-1"]}]},{"name":"National Natural Science Foundation of China","award":["E2Z211020F"],"award-info":[{"award-number":["E2Z211020F"]}]},{"name":"National Natural Science Foundation of China","award":["NO. 42141007"],"award-info":[{"award-number":["NO. 42141007"]}]},{"name":"National Natural Science Foundation of China","award":["2022-soical-key-4-1-1"],"award-info":[{"award-number":["2022-soical-key-4-1-1"]}]},{"name":"Science and Technology Planning Project of Hohhot","award":["E2Z211020F"],"award-info":[{"award-number":["E2Z211020F"]}]},{"name":"Science and Technology Planning Project of Hohhot","award":["NO. 42141007"],"award-info":[{"award-number":["NO. 42141007"]}]},{"name":"Science and Technology Planning Project of Hohhot","award":["2022-soical-key-4-1-1"],"award-info":[{"award-number":["2022-soical-key-4-1-1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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 \u201cGrain-for-Green\u201d (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 \u201cGrain-for-Green\u201d is needed. Based on this, this study used the \u201cPressure (P)-State (S)-Response (R)\u201d 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 &gt; 0.65) and a decrease of 8.89% (ES &lt; 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 \u201cGFG\u201d project are not immediate but cumulative and persistent. The continuous implementation of \u201cGFG\u201d will likely alleviate the pressure exerted by human activities on the natural environment.<\/jats:p>","DOI":"10.3390\/rs15245732","type":"journal-article","created":{"date-parts":[[2023,12,15]],"date-time":"2023-12-15T08:12:57Z","timestamp":1702627977000},"page":"5732","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Ecological Security Assessment of \u201cGrain-for-Green\u201d Program Typical Areas in Northern China Based on Multi-Source Remote Sensing Data"],"prefix":"10.3390","volume":"15","author":[{"given":"Xingtao","family":"Liu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Hang","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"}]},{"given":"Shudong","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"},{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6102-0860","authenticated-orcid":false,"given":"Kai","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"},{"name":"Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China"}]},{"given":"Long","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]},{"given":"Dehui","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100194, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Smil, V. 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