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Sensing"],"abstract":"<jats:p>Aboveground carbon stocks (AGCs) in forests play an important role in understanding carbon cycle processes. The global forestry sector has been working to find fast and accurate methods to estimate forest AGCs and implement dynamic monitoring. The aim of this study was to explore the effects of backpack LiDAR and UAV multispectral imagery on AGC estimation for two tree species (Larix gmelinii and Betula platyphylla) and to emphasize the accuracy of the models used. We estimated the AGC of Larix gmelinii and B. platyphylla forests using multivariate stepwise linear regression and random forest regression models using backpack LiDAR data and multi-source remote sensing data, respectively, and compared them with measured data. This study revealed that (1) the diameter at breast height (DBH) extracted from backpack LiDAR and vegetation indices (RVI and GNDVI) extracted from UAV multispectral imagery proved to be extremely effective in modeling for estimating AGCs, significantly improving the accuracy of the model. (2) Random forest regression models estimated AGCs with higher precision (Xing\u2019an larch R2 = 0.95, RMSE = 3.99; white birch R2 = 0.96, RMSE = 3.45) than multiple linear regression models (Xing\u2019an larch R2 = 0.92, RMSE = 6.15; white birch R2 = 0.96, RMSE = 3.57). (3) After combining backpack LiDAR and UAV multispectral data, the estimation accuracy of AGCs for both tree species (Xing\u2019an larch R2 = 0.95, white birch R2 = 0.96) improved by 2% compared to using backpack LiDAR alone (Xing\u2019an larch R2 = 0.93, white birch R2 = 0.94).<\/jats:p>","DOI":"10.3390\/rs16213927","type":"journal-article","created":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T11:31:57Z","timestamp":1729596717000},"page":"3927","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Aboveground Carbon Stock Estimation Based on Backpack LiDAR and UAV Multispectral Imagery at the Forest Sample Plot Scale"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-8845-9268","authenticated-orcid":false,"given":"Rina","family":"Su","sequence":"first","affiliation":[{"name":"The Institute of Grassland Research of CAAS, Hohhot 010010, China"},{"name":"College of Resource and Environmental Sciences, Inner Mongolia Agricultural University, Hohhot 010018, China"}]},{"given":"Wala","family":"Du","sequence":"additional","affiliation":[{"name":"The Institute of Grassland Research of CAAS, Hohhot 010010, China"},{"name":"Forest and Grassland Disaster Prevention and Iitigation Field Scientific Observation and Research Station of Inner Mongolia Autonomous Region, Arshan 137400, China"}]},{"given":"Yu","family":"Shan","sequence":"additional","affiliation":[{"name":"The College of Geographic Science, Inner Mongolia Normal University, Hohhot 010022, China"}]},{"given":"Hong","family":"Ying","sequence":"additional","affiliation":[{"name":"The College of Geographic Science, Inner Mongolia Normal University, Hohhot 010022, China"}]},{"given":"Wu","family":"Rihan","sequence":"additional","affiliation":[{"name":"The College of Geographic Science, Inner Mongolia Normal University, Hohhot 010022, China"}]},{"given":"Rong","family":"Li","sequence":"additional","affiliation":[{"name":"The College of Geographic Science, Inner Mongolia Normal University, Hohhot 010022, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.ecoinf.2014.12.003","article-title":"Estimating Biomass and Carbon Mitigation of Temperate Coniferous Forests Using Spectral Modeling and Field Inventory Data","volume":"25","author":"Wani","year":"2015","journal-title":"Ecol. 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