{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T13:20:37Z","timestamp":1770470437797,"version":"3.49.0"},"reference-count":70,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T00:00:00Z","timestamp":1732665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Xinjiang Uygur Autonomous Region","award":["2022B01012"],"award-info":[{"award-number":["2022B01012"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Land use\/cover change (LUCC) significantly alters the carbon storage capacity of ecosystems with a profound impact on global climate change. The influence of land use changes on carbon storage capacity and the projection of future carbon stock changes under different scenarios are essential for achieving carbon peak and neutrality goals. This study applied the PLUS-InVEST model to predict the land use pattern in China\u2019s arid Xinjiang Region in 2020\u20132050. The model assessed the carbon stock under four scenarios. Analysis of the historical LUCC data showed that the carbon storage in Xinjiang in 2000\u20132020 in five-year intervals was 85.69 \u00d7 108, 85.79 \u00d7 108, 85.87 \u00d7 108, 86.01 \u00d7 108, and 86.71 \u00d7 108 t. The rise in carbon sequestration capacity in the study area, attributable to the expansion of cropland, water, and unused land areas, brought a concomitant increment in the regional carbon storage by 1.03 \u00d7 108 t. However, prediction results for 2030\u20132050 showed that carbon storage capacity under the four scenarios would decrease by 0.11 \u00d7 108 and increase by 1.2 \u00d7 108, 0.98 \u00d7 108 t, and 1.28 \u00d7 108 t, respectively. The findings indicate that different land transfer modes will significantly affect Xinjiang\u2019s carbon storage quantity, distribution, and trend. This research informs the past, present, and future of carbon storage in arid ecosystems of Xinjiang. It offers a reference for Xinjiang\u2019s development planning and informs the efforts to achieve the carbon peak and neutrality goals.<\/jats:p>","DOI":"10.3390\/rs16234439","type":"journal-article","created":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T08:17:42Z","timestamp":1732695462000},"page":"4439","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Analyzing and Predicting LUCC and Carbon Storage Changes in Xinjiang\u2019s Arid Ecosystems Under the Carbon Neutrality Goal"],"prefix":"10.3390","volume":"16","author":[{"given":"Jie","family":"Song","sequence":"first","affiliation":[{"name":"College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China"}]},{"given":"Xin","family":"He","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1194-8513","authenticated-orcid":false,"given":"Fei","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0644-7498","authenticated-orcid":false,"given":"Xu","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830017, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4052-8363","authenticated-orcid":false,"given":"Chi Yung","family":"Jim","sequence":"additional","affiliation":[{"name":"Department of Social Sciences and Policy Studies, Education University of Hong Kong, Tai Po, Hong Kong 999077, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1911-3585","authenticated-orcid":false,"given":"Brian Alan","family":"Johnson","sequence":"additional","affiliation":[{"name":"Natural Resources and Ecosystem Services Area, Institute for Global Environmental Strategies, Hayama 2400115, Kanagawa, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3257-3922","authenticated-orcid":false,"given":"Ngai Weng","family":"Chan","sequence":"additional","affiliation":[{"name":"GeoInformatic Unit, Geography Section, School of Humanities, University Sains Malaysia, Penang 11800, Malaysia"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,27]]},"reference":[{"key":"ref_1","unstructured":"Field, C.B., and Barros, V.R. 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