{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T04:22:27Z","timestamp":1773116547220,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T00:00:00Z","timestamp":1661126400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"CPFL (Companhia Paulista de Forca e Luz) Group","award":["PD-00063-3075\/2020"],"award-info":[{"award-number":["PD-00063-3075\/2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Continuous mapping of vegetation height is critical for many forestry applications, such as planning vegetation management in power transmission line right-of-way. Satellite images from different sensors, including SAR (Synthetic Aperture Radar) from Sentinel 1 (S1) and multispectral from Sentinel 2 (S2), can be used for producing high-resolution vegetation height maps at a broad scale. The main objective of this study is to assess the potential of S1 and S2 satellite data, both in a single and a multisensor approach, for modeling canopy height in a transmission line right-of-way located in the Atlantic Forest of Paran\u00e1, Brazil. For integrating S1 and S2 data, we used three machine learning algorithms (LR: Linear Regression, CART: Classification and Regression Trees, and RF: Random Forest) and airborne LiDAR (Light Detection and Ranging) measurements as the reference height. The best models were obtained using the RF algorithm and 20 m resolution features from only S2 data (cross-validated RMSE of 4.92 m and R2 of 0.58) or multisensor data (cross-validated RMSE of 4.86 m and R2 of 0.60). Although the multisensor model presented the best performance, it was not statistically different from the single-S2 model. Thus, the use of only S2 to estimate canopy height has practical advantages, as it reduces the need to process SAR images and the uncertainties due to S1 noise or differences between the acquisition dates of S2 and S1.<\/jats:p>","DOI":"10.3390\/rs14164112","type":"journal-article","created":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T23:49:56Z","timestamp":1661212196000},"page":"4112","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["Canopy Height Mapping by Sentinel 1 and 2 Satellite Images, Airborne LiDAR Data, and Machine Learning"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8140-2903","authenticated-orcid":false,"given":"Catherine","family":"Torres de Almeida","sequence":"first","affiliation":[{"name":"Department of Forest Sciences, \u201cLuiz de Queiroz\u201d College of Agriculture, University of S\u00e3o Paulo (USP\/ESALQ), Piracicaba 13418-900, SP, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5286-6584","authenticated-orcid":false,"given":"J\u00e9ssica","family":"Gerente","sequence":"additional","affiliation":[{"name":"CARUSO Environmental and Technological Solutions, Florian\u00f3polis 88010-500, SC, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2256-1207","authenticated-orcid":false,"given":"Jamerson","family":"Rodrigo dos Prazeres Campos","sequence":"additional","affiliation":[{"name":"CARUSO Environmental and Technological Solutions, Florian\u00f3polis 88010-500, SC, Brazil"}]},{"given":"Francisco","family":"Caruso Gomes Junior","sequence":"additional","affiliation":[{"name":"CARUSO Environmental and Technological Solutions, Florian\u00f3polis 88010-500, SC, Brazil"}]},{"given":"Lucas Antonio","family":"Providelo","sequence":"additional","affiliation":[{"name":"CPFL (Companhia Paulista de Forca e Luz) Renewables, Campinas 13088-900, SP, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7910-9644","authenticated-orcid":false,"given":"Guilherme","family":"Marchiori","sequence":"additional","affiliation":[{"name":"CPFL (Companhia Paulista de Forca e Luz) Renewables, Campinas 13088-900, SP, Brazil"}]},{"given":"Xinjian","family":"Chen","sequence":"additional","affiliation":[{"name":"CPFL (Companhia Paulista de Forca e Luz) Renewables, Campinas 13088-900, SP, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2022,8,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"4359","DOI":"10.1002\/ece3.2201","article-title":"Scaling up Functional Traits for Ecosystem Services with Remote Sensing: Concepts and Methods","volume":"6","author":"Fremier","year":"2016","journal-title":"Ecol. 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