Please use this identifier to cite or link to this item: https://doi.org/10.1080/01431161.2010.520345
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dc.titleSeparability of insular Southeast Asian woody plantation species in the 50 m resolution ALOS PALSAR mosaic product
dc.contributor.authorMiettinen, J.
dc.contributor.authorLiew, S.C.
dc.date.accessioned2014-12-12T07:13:29Z
dc.date.available2014-12-12T07:13:29Z
dc.date.issued2011-12
dc.identifier.citationMiettinen, J., Liew, S.C. (2011-12). Separability of insular Southeast Asian woody plantation species in the 50 m resolution ALOS PALSAR mosaic product. Remote Sensing Letters 2 (4) : 299-307. ScholarBank@NUS Repository. https://doi.org/10.1080/01431161.2010.520345
dc.identifier.issn2150704X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/115282
dc.description.abstractFour types of woody plantations dominate in insular Southeast Asia: oil palm (Elaeis guineensis), rubber (Hevea brasiliensis), wattles (Acacia spp.) and coconut (Cocos nucifera). Because of the economic importance and socio-environmental controversies related particularly to oil palm cultivation, capability to perform large-scale plantation monitoring is urgently needed in this region. In this letter we report initial findings on the potential of Daichi-Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data for regional level woody plantation monitoring. We found very high separability between rubber, wattles and palms (oil palm and coconut combined) in known closed canopy plantation areas using the annually created 50 m resolution orthorectified mosaic products. Further investigation is needed to find the best ways to implement this ability in practice. Nevertheless, the findings may enable regional plantation monitoring in insular Southeast Asia at an unprecedented level of accuracy and detail. © 2011 Taylor & Francis.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/01431161.2010.520345
dc.sourceScopus
dc.typeArticle
dc.contributor.departmentCTR FOR REM IMAGING,SENSING & PROCESSING
dc.description.doi10.1080/01431161.2010.520345
dc.description.sourcetitleRemote Sensing Letters
dc.description.volume2
dc.description.issue4
dc.description.page299-307
dc.identifier.isiut000292873200004
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