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Estimating forest and woodland aboveground biomass using active and passive remote sensing / Zhuoting Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 4 (April 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 4 (April 2016) . - pp 271 - 281 Titre : Estimating forest and woodland aboveground biomass using active and passive remote sensing Type de document : Article/Communication Auteurs : Zhuoting Wu, Auteur ; Dennis Dye, Auteur ; John Vogel, Auteur ; Barry Middleton, Auteur Année de publication : 2016 Article en page(s) : pp 271 - 281 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Arizona (Etats-Unis) [Termes IGN] biomasse aérienne [Termes IGN] biomasse forestière [Termes IGN] capteur actif [Termes IGN] capteur passif [Termes IGN] données lidar [Termes IGN] écosystème forestier [Termes IGN] hauteur des arbres [Termes IGN] image Landsat-8 [Termes IGN] surface forestière Résumé : (auteur) Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14 Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1. Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States. Numéro de notice : A2016-179 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.82.4.271 En ligne : http://dx.doi.org/10.14358/PERS.82.4.271 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80521 [article]