{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T21:18:02Z","timestamp":1792271882897,"version":"4.4.0"},"reference-count":52,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Mingguo Ma; Lisheng Song","award":["41830648; 42071298"],"award-info":[{"award-number":["41830648; 42071298"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>An increase in the frequency and severity of droughts associated with global warming has resulted in deleterious impacts on forest productivity in Southwest China. Despite attempts to explore the response of vegetation to drought, less is known about forest\u2019s resilience in response to drought in Southwest China. Here, the reduced resilience of the forest was found based on remotely sensed optical and microwave vegetation products. The spatial distribution and temporal variation of resilience-reduced forest were assessed using the standardized precipitation evapotranspiration index (SPEI) and vegetation optical depth (VOD). Our findings showed that 40\u201350% of the forest appeared to have abnormally low resilience approximately 6 months after the severe drought. The spatial distributions of abnormally low resilience had a good agreement with the regions affected by the 2009\u20132011 drought events. In particular, our results indicated that areas of afforestation were more susceptible to drought than natural forest, maybe due to the different water uptake strategy of the diverse root systems. Our findings highlight the vulnerability of afforestation areas to climate change, and recommend giving more attention to soil water availability.<\/jats:p>","DOI":"10.3390\/rs14010032","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T02:02:57Z","timestamp":1640224977000},"page":"32","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Monitoring the Reduced Resilience of Forests in Southwest China Using Long-Term Remote Sensing Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2669-1909","authenticated-orcid":false,"given":"Hao","family":"Jiang","sequence":"first","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lisheng","family":"Song","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yan","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Earth Surface Processes and Resources Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3783-8363","authenticated-orcid":false,"given":"Mingguo","family":"Ma","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1834-5088","authenticated-orcid":false,"given":"Lei","family":"Fan","sequence":"additional","affiliation":[{"name":"Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China"},{"name":"Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1038\/s41467-019-13798-8","article-title":"Forest management in southern China generates short term extensive carbon sequestration","volume":"11","author":"Tong","year":"2020","journal-title":"Nat. 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