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Mapping tropical forests and rubber plantations in complex landscapes by integrating PALSAR and MODIS imagery / J. Dong in ISPRS Journal of photogrammetry and remote sensing, vol 74 (Novembrer 2012)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 74 (Novembrer 2012) . - pp 20 - 33 Titre : Mapping tropical forests and rubber plantations in complex landscapes by integrating PALSAR and MODIS imagery Type de document : Article/Communication Auteurs : J. Dong, Auteur ; X. Xiao, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 20 - 33 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] afforestation [Termes IGN] carte de la végétation [Termes IGN] classification dirigée [Termes IGN] classification par réseau neuronal [Termes IGN] forêt tropicale [Termes IGN] Hainan (Chine) [Termes IGN] Hevea brasiliensis [Termes IGN] image ALOS-PALSAR [Termes IGN] image Terra-MODIS [Termes IGN] traitement d'image [Termes IGN] zone tropicale humide Résumé : (Auteur) Knowledge of the spatial distribution of forest types in tropical regions is important for implementation of Reducing Emissions from Deforestation and Forest Degradation (REDD), better understanding of the global carbon cycle, and optimal forest management. Frequent cloud cover in moist tropical regions poses challenges for using optical images to map and monitor forests. Recently, Japan Aerospace Exploration Agency (JAXA) released a 50 m orthorectified mosaic product from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS). PALSAR data provides information about the land surface without cloud interference. In this study we use the fine beam dual (FBD) polarization PALSAR 50 m mosaic imagery and a Neural Network (NN) method to produce a land cover map in Hainan Island, China. Subsequently, forest areas are classified into evergreen and deciduous forests and rubber plantations are mapped using vegetation and land surface water indices derived from 250 to 500 m resolution MODIS products. The PALSAR 50 m forest cover map, MODIS-based forest types and rubber plantation maps are fused to generate fractional maps of evergreen forest, deciduous forest and rubber plantation within 500 m or 250 m pixels. PALSAR data perform well for land cover classification (overall accuracy = 89% and Kappa Coefficient = 0.79) and forest identification (both the Producer’s Accuracy and User’s Accuracy are higher than 92%). The resulting land cover maps of forest, cropland, water and urban lands are consistent with the National Land Cover Dataset of China in 2005 (NLCD-2005). Validation from ground truth samples indicates that the resultant rubber plantation map is highly accurate (the overall accuracy = 85%). Overall, this study provides insight on the potential of integrating cloud-free 50 m PALSAR and temporal MODIS data on mapping forest types and rubber plantations in moist tropical regions. Numéro de notice : A2012-603 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.07.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.07.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32049 [article]

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