{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T20:40:20Z","timestamp":1770842420381,"version":"3.50.1"},"reference-count":128,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2024,11,10]],"date-time":"2024-11-10T00:00:00Z","timestamp":1731196800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Laboratory of Xinjiang Science and Technology Department","award":["2022D04009"],"award-info":[{"award-number":["2022D04009"]}]},{"name":"Key Laboratory of Xinjiang Science and Technology Department","award":["2023SNGGGGCC004"],"award-info":[{"award-number":["2023SNGGGGCC004"]}]},{"name":"Xinjiang \u2018Tianshan Yingcai\u2019 cultivation plan","award":["2022D04009"],"award-info":[{"award-number":["2022D04009"]}]},{"name":"Xinjiang \u2018Tianshan Yingcai\u2019 cultivation plan","award":["2023SNGGGGCC004"],"award-info":[{"award-number":["2023SNGGGGCC004"]}]},{"name":"China\u2019s Xinjiang Grassland Station","award":["2022D04009"],"award-info":[{"award-number":["2022D04009"]}]},{"name":"China\u2019s Xinjiang Grassland Station","award":["2023SNGGGGCC004"],"award-info":[{"award-number":["2023SNGGGGCC004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In the context of drought events caused by global warming, there is limited understanding of vegetation loss caused by drought and the subsequent recovery of vegetation after drought ends. However, employing a single index representing a specific vegetation characteristic to explore drought\u2019s impact on vegetation may overlook vegetation features and introduce increased uncertainty. We applied the enhanced vegetation index (EVI), fraction of vegetation cover (FVC), gross primary production (GPP), leaf area index (LAI), and our constructed remote sensing vegetation index (RSVI) to assess vegetation drought in Central Asia. We analyzed the differences in drought experiences for different climatic regions and vegetation types and vegetation loss and recovery following drought events. The results indicate that during drought years (2012 and 2019), the differences in vegetation drought across climatic regions were considerable. The vegetation in arid, semiarid, and Mediterranean climate regions was more susceptible to drought. The different indices used to assess vegetation loss exhibited varying degrees of dynamic changes, with vegetation in a state of mild drought experiencing more significantly during drought events. The different vegetation assessment indices exhibited significant variations during the drought recovery periods (with a recovery period of 16 days: EVI of 85%, FVC of 50%, GPP of 84%, LAI of 61%, and RSVI of 44%). Moreover, the required recovery periods tended to decrease from arid to humid climates, influenced by both climate regions and vegetation types. Sensitivity analysis indicated that the primary climatic factors leading to vegetation loss varied depending on the assessment indices used. The proposed RSVI demonstrates high sensitivity, correlation, and interpretability to dry\u2013wet variations and can be used to assess the impact of drought on vegetation. These findings are essential for water resource management and the implementation of measures that mitigate vegetation drought.<\/jats:p>","DOI":"10.3390\/rs16224189","type":"journal-article","created":{"date-parts":[[2024,11,11]],"date-time":"2024-11-11T11:34:11Z","timestamp":1731324851000},"page":"4189","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Assessment of Vegetation Drought Loss and Recovery in Central Asia Considering a Comprehensive Vegetation Index"],"prefix":"10.3390","volume":"16","author":[{"given":"Wanqiang","family":"Han","sequence":"first","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]},{"given":"Jianghua","family":"Zheng","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]},{"given":"Jingyun","family":"Guan","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]},{"given":"Yujia","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]},{"given":"Liang","family":"Liu","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]},{"given":"Chuqiao","family":"Han","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]},{"given":"Jianhao","family":"Li","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]},{"given":"Congren","family":"Li","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]},{"given":"Xurui","family":"Mao","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]},{"given":"Ruikang","family":"Tian","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Science, Xinjiang University, Urumqi 830046, China"},{"name":"Key Laboratory of Oasis Ecology, Autonomous Region, Xinjiang University, Urumqi 830046, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1419","DOI":"10.1111\/1365-2745.12273","article-title":"Vegetation Structure Is as Important as Climate for Explaining Ecosystem Function across Patagonian Rangelands","volume":"102","author":"Oliva","year":"2014","journal-title":"J. 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