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Title: Identification of woody plantation species in insular southeast Asia using 50m resolution ALOS PALSAR mosaic
Authors: Miettinen, J. 
Tan, W.J. 
Liew, S.C. 
Kwoh, L.K. 
Plantations monitoring
Species identification
Issue Date: 2010
Citation: Miettinen, J.,Tan, W.J.,Liew, S.C.,Kwoh, L.K. (2010). Identification of woody plantation species in insular southeast Asia using 50m resolution ALOS PALSAR mosaic. 31st Asian Conference on Remote Sensing 2010, ACRS 2010 1 : 252-257. ScholarBank@NUS Repository.
Abstract: Four types of woody plantations dominate in insular Southeast Asia: oil palm (Elaeis guineensis), rubber (Hevea brasiliensis), wattles (Acacia spp.) and coconut (Cocos nucifera). Due to its canopy penetrating ability, Daichi-Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) data offer information on the canopy/plantation structure and potentially enable plantation species identification. In this study we analyse the separability of the four plantation species in closed canopy plantations using 50m resolution orthorectified ALOS PALSAR dual polarization (HH and HV) data on 41 sample sites selected over Peninsular Malaysia and Riau, Indonesia. The difference between HH and HV backscatter (HH-HV) showed high separability between palms and other woody plantations. Furthermore, HV backscatter alone enabled separation between wattle and rubber plantations. Accuracy assessment of a decision tree based classification test (into palms, wattle and rubber) in an area of around 20000km 2 revealed an overall accuracy of 86%, including 94% user's accuracy for palm plantation identification. Thus, our results indicate that ALOS PALSAR data enable separation between rubber, wattle and palms (oil palm and coconut combined) in known closed canopy plantation areas. But it does not show potential for separation between oil palm and coconut plantations. However, it was also revealed that plantation backscatter values greatly overlapped with those of other land cover types. Therefore, without prior knowledge of plantation area, a combination of data sources is needed for plantation monitoring.
Source Title: 31st Asian Conference on Remote Sensing 2010, ACRS 2010
ISBN: 9781617823978
Appears in Collections:Staff Publications

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