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Application of topo-edaphic factors and remotely sensed vegetation indices to enhance biomass estimation in a heterogeneous landscape in the Eastern Arc mountains of Tanzania / Mercy Ojoyi in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)  

Public [article]  inGeocarto international > vol 31 n° 1 - 2 (January - February 2016) . - pp 1 - 21 Titre : Application of topo-edaphic factors and remotely sensed vegetation indices to enhance biomass estimation in a heterogeneous landscape in the Eastern Arc mountains of Tanzania Type de document : Article/Communication Auteurs : Mercy Ojoyi, Auteur ; Onisimo Mutanga, Auteur ; John Olindi, Auteur ; Elfatih M. Abdel-Rahman, Auteur Année de publication : 2016 Article en page(s) : pp 1 - 21 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] biomasse [Termes IGN] données topographiques [Termes IGN] estimation statistique [Termes IGN] facteur édaphique [Termes IGN] forêt tropicale [Termes IGN] image RapidEye [Termes IGN] indice de végétation [Termes IGN] montagne [Termes IGN] surveillance écologique [Termes IGN] Tanzanie Résumé : (Auteur) Estimating tropical biomass is critical for establishment of conservation inventories and landscape monitoring. However, monitoring biomass in a complex and dynamic environment using traditional methods is challenging. Recently, biomass estimates based on remotely sensed data and ecological variables have shown great potential. The present study explored the utility of remotely sensed data and topo-edaphic factors to improve biomass estimation in the Eastern Arc Mountains of Tanzania. Twenty-nine vegetation indices were calculated from RapidEye data, while topo-edaphic factors were taken from field measurements. Results showed that using topo-edaphic variables or vegetation indices, biomass could be predicted with an R2 of 0.4. A combination of topo-edaphic variables and vegetation indices improved the prediction accuracy to an R2 of 0.6. Results further showed a decrease in biomass estimates from 1162 ton ha−1 in 1980 to 285.38 ton ha−1 in 2012. This study demonstrates the value of combining remotely sensed data with topo-edaphic variables in biomass estimation. Numéro de notice : A2016-079 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1041557 Date de publication en ligne : 20/05/2015 En ligne : http://www.tandfonline.com/doi/full/10.1080/10106049.2015.1041557 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79865 [article]

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