{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,27]],"date-time":"2026-02-27T03:54:57Z","timestamp":1772164497064,"version":"3.50.1"},"reference-count":49,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,5,30]],"date-time":"2019-05-30T00:00:00Z","timestamp":1559174400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Strategic Priority Research Program of the Chinese Academy of Sciences","award":["XDA19070504"],"award-info":[{"award-number":["XDA19070504"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Permafrost is degrading on the Qinghai-Tibet Plateau (QTP) due to climate change. Permafrost degradation can result in ecosystem changes and damage to infrastructure. However, we lack baseline data related to permafrost thermal dynamics at a local scale. Here, we model climate change impacts on permafrost from 1986 to 2075 at a high resolution using a numerical model for the Beiluhe basin, which includes representative permafrost environments of the QTP. Ground surface temperatures are derived from air temperature using an n-factor vs Normalized Differential Vegetation Index (NDVI) relationship. Soil properties are defined by field measurements and ecosystem types. The climate projections are based on long-term observations. The modelled ground temperature (MAGT) and active-layer thickness (ALT) are close to in situ observations. The results show a discontinuous permafrost distribution (61.4%) in the Beiluhe basin at present. For the past 30 years, the permafrost area has decreased rapidly, by a total of 26%. The mean ALT has increased by 0.46 m. For the next 60 years, 8.5\u201335% of the permafrost area is likely to degrade under different trends of climate warming. The ALT will probably increase by 0.38\u20130.86 m. The results of this study are useful for developing a deeper understanding of ecosystem change, permafrost development, and infrastructure development on the QTP.<\/jats:p>","DOI":"10.3390\/rs11111294","type":"journal-article","created":{"date-parts":[[2019,5,30]],"date-time":"2019-05-30T11:07:44Z","timestamp":1559214464000},"page":"1294","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["High Spatial Resolution Modeling of Climate Change Impacts on Permafrost Thermal Conditions for the Beiluhe Basin, Qinghai-Tibet Plateau"],"prefix":"10.3390","volume":"11","author":[{"given":"Jing","family":"Luo","sequence":"first","affiliation":[{"name":"State Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8855-8388","authenticated-orcid":false,"given":"Guoan","family":"Yin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}]},{"given":"Fujun","family":"Niu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}]},{"given":"Zhanju","family":"Lin","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}]},{"given":"Minghao","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Frozen Soils Engineering, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,30]]},"reference":[{"key":"ref_1","unstructured":"Arctic Climate Impact Assessment (ACIA) (2005). 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