{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,7,23]],"date-time":"2024-07-23T17:13:11Z","timestamp":1721754791209},"reference-count":89,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,4,25]],"date-time":"2018-04-25T00:00:00Z","timestamp":1524614400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Accurate estimation of above ground biomass (AGB) is required to better understand the variability and dynamics of tropical peat swamp forest (PSF) ecosystem function and resilience to disturbance events. The objective of this work is to examine the relationship between tropical PSF AGB and small-footprint airborne Light Detection and Ranging (LiDAR) discrete return (DR) and full waveform (FW) derived metrics, with a view to establishing the optimal use of this technology in this environment. The study was undertaken in North Selangor peat swamp forest (NSPSF) reserve, Peninsular Malaysia. Plot-based multiple regression analysis was performed to established the strongest predictive models of PSF AGB using DR metrics (only), FW metrics (only), and a combination of DR and FW metrics. Overall, the results demonstrate that a Combination-model, coupling the benefits derived from both DR and FW metrics, had the best performance in modelling AGB for tropical PSF (R2 = 0.77, RMSE = 36.4, rRMSE = 10.8%); however, no statistical difference was found between the rRMSE of this model and the best models using only DR and FW metrics. We conclude that the optimal approach to using airborne LiDAR for the estimation of PSF AGB is to use LiDAR metrics that relate to the description of the mid-canopy. This should inform the use of remote sensing in this ecosystem and how innovation in LiDAR-based technology could be usefully deployed.<\/jats:p>","DOI":"10.3390\/rs10050671","type":"journal-article","created":{"date-parts":[[2018,4,25]],"date-time":"2018-04-25T15:15:39Z","timestamp":1524669339000},"page":"671","source":"Crossref","is-referenced-by-count":14,"title":["Tropical Peatland Vegetation Structure and Biomass: Optimal Exploitation of Airborne Laser Scanning"],"prefix":"10.3390","volume":"10","author":[{"given":"Chloe","family":"Brown","sequence":"first","affiliation":[{"name":"School of Geography, University of Nottingham, Nottingham NG7 2RD, UK"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-3040-552X","authenticated-orcid":false,"given":"Doreen S.","family":"Boyd","sequence":"additional","affiliation":[{"name":"School of Geography, University of Nottingham, Nottingham NG7 2RD, UK"}]},{"given":"Sofie","family":"Sj\u00f6gersten","sequence":"additional","affiliation":[{"name":"School of Biosciences, University of Nottingham, Nottingham NG7 2RD, UK"}]},{"given":"Daniel","family":"Clewley","sequence":"additional","affiliation":[{"name":"Plymouth Marine Laboratory, Plymouth PL1 3DH, UK"}]},{"given":"Stephanie L.","family":"Evers","sequence":"additional","affiliation":[{"name":"School of Natural Sciences and Psychology, Liverpool John Moores University, Liverpool L3 3AF, UK"},{"name":"School of Environmental and Geographical Sciences, University of Nottingham Malaysia Campus, Semenyih 43500, Selangor, Malaysia"},{"name":"Tropical Catchment Research Initiative (TROCARI), Semenyih 43500, Selangor, Malaysia"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-9394-5630","authenticated-orcid":false,"given":"Paul","family":"Aplin","sequence":"additional","affiliation":[{"name":"School of Geography, Edge Hill University, Ormskirk L39 4QP, UK"}]}],"member":"1968","published-online":{"date-parts":[[2018,4,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Page, S.E., Rieley, J.O., Shotyk, \u00d8.W., and Weiss, D. 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