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Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia / Adelia M.O. Sousa in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 101 (March 2015) . - pp 69 - 79 Titre : Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia Type de document : Article/Communication Auteurs : Adelia M.O. Sousa, Auteur ; Ana Cristina Goncalves, Auteur ; Paulo Mesquita, Auteur ; José R. Marques da Silva, Auteur Année de publication : 2015 Article en page(s) : pp 69 - 79 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse [Termes IGN] image à très haute résolution [Termes IGN] image Quickbird [Termes IGN] inventaire forestier étranger (données) [Termes IGN] Portugal [Termes IGN] Quercus ilex Résumé : (auteur) Forest biomass has had a growing importance in the world economy as a global strategic reserve, due to applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. Current techniques used for forest inventory are usually time consuming and expensive. Thus, there is an urgent need to develop reliable, low cost methods that can be used for forest biomass estimation and monitoring. This study uses new techniques to process high spatial resolution satellite images (0.70 m) in order to assess and monitor forest biomass. Multi-resolution segmentation method and object oriented classification are used to obtain the area of tree canopy horizontal projection for Quercus rotundifolia. Forest inventory allows for calculation of tree and canopy horizontal projection and biomass, the latter with allometric functions. The two data sets are used to develop linear functions to assess above ground biomass, with crown horizontal projection as an independent variable. The functions for the cumulative values, both for inventory and satellite data, for a prediction error equal or smaller than the Portuguese national forest inventory (7%), correspond to stand areas of 0.5 ha, which include most of the Q.rotundifolia stands. Numéro de notice : A2015-469 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.12.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.12.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77171 [article]

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