{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T15:52:39Z","timestamp":1785858759528,"version":"3.56.0"},"reference-count":65,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T00:00:00Z","timestamp":1532563200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key R&amp;D Program of China","award":["2017YFC0503905, 2016YFC0500202"],"award-info":[{"award-number":["2017YFC0503905, 2016YFC0500202"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41471363, 31741016"],"award-info":[{"award-number":["41471363, 31741016"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["EAR 0922307"],"award-info":[{"award-number":["EAR 0922307"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Canopy height is an important forest structure parameter for understanding forest ecosystem and improving global carbon stock quantification accuracy. Light detection and ranging (LiDAR) can provide accurate canopy height measurements, but its application at large scales is limited. Using LiDAR-derived canopy height as ground truth to train the Random Forest (RF) algorithm and therefore predict canopy height from other remotely sensed datasets in areas without LiDAR coverage has been one of the most commonly used method in large-scale canopy height mapping. However, how variances in location, vegetation type, and spatial scale of study sites influence the RF modelling results is still a question that needs to be addressed. In this study, we selected 16 study sites (100 km2 each) with full airborne LiDAR coverage across the United States, and used the LiDAR-derived canopy height along with optical imagery, topographic data, and climate surfaces to evaluate the transferability of the RF-based canopy height prediction method. The results show a series of findings from general to complex. The RF model trained at a certain location or vegetation type cannot be transferred to other locations or vegetation types. However, by training the RF algorithm using samples from all sites with various vegetation types, a universal model can be achieved for predicting canopy height at different locations and different vegetation types with self-predicted R2 higher than 0.6 and RMSE lower than 6 m. Moreover, the influence of spatial scales on the RF prediction accuracy is noticeable when spatial extent of the study site is less than 50 km2 or the spatial resolution of the training pixel is finer than 500 m. The canopy height prediction accuracy increases with the spatial extent and the targeted spatial resolution.<\/jats:p>","DOI":"10.3390\/rs10081183","type":"journal-article","created":{"date-parts":[[2018,7,26]],"date-time":"2018-07-26T11:32:07Z","timestamp":1532604727000},"page":"1183","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":51,"title":["The Transferability of Random Forest in Canopy Height Estimation from Multi-Source Remote Sensing Data"],"prefix":"10.3390","volume":"10","author":[{"given":"Shichao","family":"Jin","sequence":"first","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"},{"name":"University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanjun","family":"Su","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"},{"name":"University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China"},{"name":"Sierra Nevada Research Institute, School of Engineering, University of California Merced, Merced, CA 95343, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shang","family":"Gao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"},{"name":"University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tianyu","family":"Hu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinghua","family":"Guo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"},{"name":"University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China"},{"name":"Sierra Nevada Research Institute, School of Engineering, University of California Merced, Merced, CA 95343, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,7,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1038\/387253a0","article-title":"The value of the world\u2019s ecosystem services and natural capital","volume":"387","author":"Costanza","year":"1997","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"945","DOI":"10.1111\/j.1365-2486.2005.00955.x","article-title":"Aboveground forest biomass and the global carbon balance","volume":"11","author":"Houghton","year":"2005","journal-title":"Glob. 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