{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T08:18:17Z","timestamp":1791015497167,"version":"4.1.0"},"reference-count":52,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2022,11,25]],"date-time":"2022-11-25T00:00:00Z","timestamp":1669334400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Department of Science &amp; Technology\u2014Centre of Excellence in Climate Change (DST CoE), Government of India","award":["DST\/CCP\/CoE\/79\/2017(G), Dt. 30-03-2017"],"award-info":[{"award-number":["DST\/CCP\/CoE\/79\/2017(G), Dt. 30-03-2017"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Forest canopy height estimates, at a regional scale, help understand the forest carbon storage, ecosystem processes, the development of forest management and the restoration policies to mitigate global climate change, etc. The recent availability of the NASA\u2019s Global Ecosystem Dynamics Investigation (GEDI) LiDAR data has opened up new avenues to assess the plant canopy height at a footprint level. Here, we present a novel approach using the random forest (RF) for the wall-to-wall canopy height estimation over India\u2019s forests (i.e., evergreen forest, deciduous forest, mixed forest, plantation, and shrubland) by employing the high-resolution top-of-the-atmosphere (TOA) reflectance and vegetation indices, the synthetic aperture radar (SAR) backscatters, the topography and tree canopy density, as the proxy variables. The variable importance plot indicated that the SAR backscatters, tree canopy density and the topography are the most influential height predictors. 33.15% of India\u2019s forest cover demonstrated the canopy height &lt;10 m, while 44.51% accounted for 10\u201320 m and 22.34% of forests demonstrated a higher canopy height (&gt;20 m). This study advocates the importance and use of GEDI data for estimating the canopy height, preferably in data-deficit mountainous regions, where most of India\u2019s natural forest vegetation exists.<\/jats:p>","DOI":"10.3390\/rs14235968","type":"journal-article","created":{"date-parts":[[2022,11,28]],"date-time":"2022-11-28T07:01:30Z","timestamp":1669618890000},"page":"5968","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Predicting the Forest Canopy Height from LiDAR and Multi-Sensor Data Using Machine Learning over India"],"prefix":"10.3390","volume":"14","author":[{"given":"Sujit M.","family":"Ghosh","sequence":"first","affiliation":[{"name":"Solid World DAO, P\u00e4rnu mnt 15 \/\/ Tatari tn 2, 10141 Tallinn, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9976-6270","authenticated-orcid":false,"given":"Mukunda D.","family":"Behera","sequence":"additional","affiliation":[{"name":"Centre for Oceans, Rivers, Atmosphere and Land Sciences, IIT Kharagpur, Kharagpur 721302, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0590-686X","authenticated-orcid":false,"given":"Subham","family":"Kumar","sequence":"additional","affiliation":[{"name":"Centre for Oceans, Rivers, Atmosphere and Land Sciences, IIT Kharagpur, Kharagpur 721302, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0508-7219","authenticated-orcid":false,"given":"Pulakesh","family":"Das","sequence":"additional","affiliation":[{"name":"Sustainable Landscapes and Restoration, World Resources Institute India, New Delhi 110016, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ambadipudi J.","family":"Prakash","sequence":"additional","affiliation":[{"name":"Centre for Oceans, Rivers, Atmosphere and Land Sciences, IIT Kharagpur, Kharagpur 721302, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Prasad K.","family":"Bhaskaran","sequence":"additional","affiliation":[{"name":"Ocean Engineering and Naval Architecture, IIT Kharagpur, Kharagpur 721302, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6803-6785","authenticated-orcid":false,"given":"Parth S.","family":"Roy","sequence":"additional","affiliation":[{"name":"Sustainable Landscapes and Restoration, World Resources Institute India, New Delhi 110016, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saroj K.","family":"Barik","sequence":"additional","affiliation":[{"name":"CSIR-National Botanical Research Institute, Lucknow 226001, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2375-7677","authenticated-orcid":false,"given":"Chockalingam","family":"Jeganathan","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing, Birla Institute of Technology (BIT), Mesra, Ranchi 835215, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4155-630X","authenticated-orcid":false,"given":"Prashant K.","family":"Srivastava","sequence":"additional","affiliation":[{"name":"Institute of Environment & Sustainable Development, Banaras Hindu University, Varanasi 221005, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Soumit K.","family":"Behera","sequence":"additional","affiliation":[{"name":"CSIR-National Botanical Research Institute, Lucknow 226001, India"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Roy, S., Mudi, S., Das, P., Ghosh, S., Shit, P.K., Bhunia, G.S., and Kim, J. 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