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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]

Vegetation Burn Severity Mapping Using Landsat-8 and WorldView-2 / Zhuoting Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 2 (February 2015)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 2 (February 2015) . - pp 143 - 154 Titre : Vegetation Burn Severity Mapping Using Landsat-8 and WorldView-2 Type de document : Article/Communication Auteurs : Zhuoting Wu, Auteur ; Barry Middleton, Auteur ; Robert Hetzler, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 143 - 154 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Arizona (Etats-Unis) [Termes IGN] canopée [Termes IGN] carte thématique [Termes IGN] dommage matériel [Termes IGN] données multitemporelles [Termes IGN] image Landsat-8 [Termes IGN] image Worldview [Termes IGN] incendie de forêt [Termes IGN] ressources forestières Résumé : (auteur) We used remotely sensed data from the Landsat-8 and WorldView-2 satellites to estimate vegetation burn severity of the Creek Fire on the San Carlos Apache Reservation, where wildfire occurrences affect the Tribe’s crucial livestock and logging industries. Accurate pre- and post-fire canopy maps at high (0.5-meter) resolution were created from WorldView-2 data to generate canopy loss maps, and multiple indices from pre- and post-fire Landsat-8 images were used to evaluate vegetation burn severity. Normalized difference vegetation index based vegetation burn severity map had the highest correlation coefficients with canopy loss map from WorldView-2. Two distinct approaches - canopy loss mapping from WorldView-2 and spectral index differencing from Landsat-8 - agreed well with the field-based burn severity estimates and are both effective for vegetation burn severity mapping. Canopy loss maps created with WorldView-2 imagery add to a short list of accurate vegetation burn severity mapping techniques that can help guide effective management of forest resources on the San Carlos Apache Reservation, and the broader fire-prone regions of the Southwest. Numéro de notice : A2015-968 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.2.143 En ligne : https://doi.org/10.14358/PERS.81.2.143 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80026 [article]