Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/70908
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dc.contributorDepartment of Land Surveying and Geo-Informatics-
dc.creatorGwenzi, D-
dc.creatorHelmer, EH-
dc.creatorZhu, XL-
dc.creatorLefsky, MA-
dc.creatorMarcano-Vega, H-
dc.date.accessioned2017-12-28T06:18:28Z-
dc.date.available2017-12-28T06:18:28Z-
dc.identifier.issn2072-4292en_US
dc.identifier.urihttp://hdl.handle.net/10397/70908-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2017 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Gwenzi, D.; Helmer, E.H.; Zhu, X.; Lefsky, M.A.; Marcano-Vega, H. Predictions of Tropical Forest Biomass and Biomass Growth Based on Stand Height or Canopy Area Are Improved by Landsat-Scale Phenology across Puerto Rico and the U.S. Virgin Islands. Remote Sens. 2017, 9, 123, 1-18 is available at https://dx.doi.org/10.3390/rs9020123en_US
dc.subjectLandsaten_US
dc.subjectPhenologyen_US
dc.subjectForest deciduousnessen_US
dc.subjectForest biomassen_US
dc.subjectForest biomass growthen_US
dc.subjectForest carbon stocksen_US
dc.titlePredictions of tropical forest biomass and biomass growth based on stand height or canopy area are improved by landsat-scale phenology across Puerto Rico and the U.S. Virgin Islandsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1en_US
dc.identifier.epage18en_US
dc.identifier.volume9en_US
dc.identifier.issue2en_US
dc.identifier.doi10.3390/rs9020123en_US
dcterms.abstractRemotely-sensed estimates of forest biomass are usually based on various measurements of canopy height, area, volume or texture, as derived from LiDAR, radar or fine spatial resolution imagery. These measurements are then calibrated to estimates of stand biomass that are primarily based on tree stem diameters. Although humid tropical forest seasonality can have low amplitudes compared with temperate regions, seasonal variations in growth-related factors like temperature, humidity, rainfall, wind speed and day length affect both tropical forest deciduousness and tree height-diameter relationships. Consequently, seasonal patterns in spectral measures of canopy greenness derived from satellite imagery should be related to tree height-diameter relationships and hence to estimates of forest biomass or biomass growth that are based on stand height or canopy area. In this study, we tested whether satellite image-based measures of tropical forest phenology, as estimated by indices of seasonal patterns in canopy greenness constructed from Landsat satellite images, can explain the variability in forest deciduousness, forest biomass and net biomass growth after already accounting for stand height or canopy area. Models of forest biomass that added phenology variables to structural variables similar to those that can be estimated by LiDAR or very high-spatial resolution imagery, like canopy height and crown area, explained up to 12% more variation in biomass. Adding phenology to structural variables explained up to 25% more variation in Net Biomass Growth (NBG). In all of the models, phenology contributed more as interaction terms than as single-effect terms. In addition, models run on only fully-forested plots performed better than models that included partially-forested plots. For forest NBG, the models produced better results when only those plots with a positive growth, from Inventory Cycle 1 to Inventory Cycle 2, were analyzed, as compared to models that included all plots.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationRemote sensing, Feb. 2017, v. 9, no. 2, 123-
dcterms.isPartOfRemote sensing-
dcterms.issued2017-
dc.identifier.isiWOS:000397013700025-
dc.identifier.scopus2-s2.0-85013671662-
dc.identifier.ros2016003804-
dc.identifier.artn123en_US
dc.identifier.rosgroupid2016003735-
dc.description.ros2016-2017 > Academic research: refereed > Publication in refereed journalen_US
dc.description.validatebcrcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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