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However, generating a reliable estimate remains a considerable challenge, primarily due to the lack of representative in situ measurements and proper methods capable of addressing their complex spatial variation. Here, we proposed a deep learning-based method that combines Residual convolutional neural networks (ResNet) with in situ measurements, microwave (Sentinel-1 and VOD), and optical data (Sentinel-2 and Landsat) to estimate forest biomass and track its change over the mountainous regions. Our approach, integrating in situ measurements across representative elevations with multi-source remote sensing images, significantly improves the accuracy of biomass estimation in Tibet\u2019s complex mountainous forests (R2 = 0.80, root mean squared error = 15.8 MgC ha\u22121). Moreover, ResNet, which addresses the vanishing gradient problem in deep neural networks by introducing skip connections, enables the extraction of complex spatial patterns from limited datasets, outperforming traditional optical-based or pixel-based methods. The mean value of forest biomass was estimated as 162.8 \u00b1 21.3 MgC ha\u22121, notably higher than that of forests at comparable latitudes or flat regions in China. Additionally, our findings revealed a substantial forest biomass carbon sink of 3.35 TgC year\u22121 during 2015\u20132020, which is largely underestimated by previous estimates, mainly due to the underestimation of mountainous carbon stock. The significant carbon density, combined with the underestimated carbon sink in mountainous regions, emphasizes the urgent need to reassess mountain forests to better approximate the global carbon budget.<\/jats:p>","DOI":"10.3390\/rs16091481","type":"journal-article","created":{"date-parts":[[2024,4,23]],"date-time":"2024-04-23T08:08:27Z","timestamp":1713859707000},"page":"1481","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Toward a More Robust Estimation of Forest Biomass Carbon Stock and Carbon Sink in Mountainous Region: A Case Study in Tibet, China"],"prefix":"10.3390","volume":"16","author":[{"given":"Guanting","family":"Lyu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3843-2434","authenticated-orcid":false,"given":"Xiaoyi","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xieqin","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7189-0803","authenticated-orcid":false,"given":"Jinfeng","family":"Xu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"College of Ecology, Lanzhou University, Lanzhou 730000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Siyu","family":"Li","sequence":"additional","affiliation":[{"name":"College of Geography and Ocean Sciences, Yanbian University, Yanji 133002, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1748-4235","authenticated-orcid":false,"given":"Guishan","family":"Cui","sequence":"additional","affiliation":[{"name":"College of Geography and Ocean Sciences, Yanbian University, Yanji 133002, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huabing","family":"Huang","sequence":"additional","affiliation":[{"name":"School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,23]]},"reference":[{"key":"ref_1","unstructured":"Price, M.F., Gratzer, G., Duguma, L.A., Kohler, T., Maselli, D., and Romeo, R. 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