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Operationalizing measurement of forest degradation: Identification and quantification of charcoal production in tropical dry forests using very high resolution satellite imagery / K. Dons in International journal of applied Earth observation and geoinformation, vol 39 (July 2015)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 39 (July 2015) . - pp 18 - 27 Titre : Operationalizing measurement of forest degradation: Identification and quantification of charcoal production in tropical dry forests using very high resolution satellite imagery Type de document : Article/Communication Auteurs : K. Dons, Auteur ; C. Smith-Hall, Auteur ; H. Meilby, Auteur ; Rasmus Fensholt, Auteur Année de publication : 2015 Article en page(s) : pp 18 - 27 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse (combustible) [Termes IGN] charbon de bois [Termes IGN] classification dirigée [Termes IGN] déboisement [Termes IGN] extraction de traits caractéristiques [Termes IGN] image Quickbird [Termes IGN] pansharpening (fusion d'images) [Termes IGN] sous-bois [Termes IGN] Tanzanie Résumé : (auteur) Quantification of forest degradation in monitoring and reporting as well as in historic baselines is among the most challenging tasks in national REDD+ strategies. However, a recently introduced option is to base monitoring systems on subnational conditions such as prevalent degradation activities. In Tanzania, charcoal production is considered a major cause of forest degradation, but is challenging to quantify due to sub-canopy biomass loss, remote production sites and illegal trade. We studied two charcoal production sites in dry Miombo woodland representing open woodland conditions near human settlements and remote forest with nearly closed canopies. Supervised classification and adaptive thresholding were applied on a pansharpened QuickBird (QB) image to detect kiln burn marks (KBMs). Supervised classification showed reasonable detection accuracy in the remote forest site only, while adaptive thresholding was found acceptable at both locations. We used supervised classification and manual digitizing for KBM delineation and found acceptable delineation accuracy at both sites with RMSEs of 25–32% compared to ground measurements. Regression of charcoal production on KBM area delineated from QB resulted in R2s of 0.86–0.88 with cross-validation RMSE ranging from 2.22 to 2.29 Mg charcoal per kiln. This study demonstrates, how locally calibrated remote sensing techniques may be used to identify and delineate charcoal production sites for estimation of charcoal production and associated extraction of woody biomass. Numéro de notice : A2015-299 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2015.02.001 En ligne : http://www.sciencedirect.com/science/article/pii/S0303243415000331 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76475 [article]