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IDENTIFICATION OF WOODY PLANTATION SPECIES IN INSULAR SOUTHEAST ASIA USING 50M RESOLUTION ALOS PALSAR MOSAIC

机译:使用50M分辨率识别绝缘东南亚的木本植物种类Alos Palsar Mosaic

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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 20000km2 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.
机译:四种类型的木质种植园占主导地位,占地面积南亚:油棕{elaeisguineensis),橡胶(Hevea brasiliensis),Wattles {acacia spp。)和椰子(Cocos Nucifera)。由于其冠层穿透能力,Daichi-Advanced Land观察卫星(ALOS)相控阵型L波段合成孔径雷达(PALSAR)数据提供有关冠层/种植结构的信息,并且可能使种植型物种鉴定。在这项研究中,我们使用50米分辨率的Alos Palsar双极化(HH和HV)数据,在41种样本位点上选择的41种样本位点,分析了封闭冠层种植园中的四种植种类的可分离性。 HH和HV反向散射(HH-HV)之间的差异显示了棕榈树和其他木质种植园之间的高可分离性。此外,单独的HV反向散射能够在荆棘和橡胶园之间的分离。大约20000km2面积的基于决策树的分类测试(进入手掌,篱笆和橡胶)的准确性评估显示了86%的总体精度,包括94%的棕榈种植型识别的用户准确性。因此,我们的结果表明,Alos Palsar数据能够在已知的封闭冠层地区的橡胶,荆棘和棕榈树(油棕和椰子组合)之间分离。但它并不显示油棕和椰子种植园之间的分离潜力。然而,还揭示了种植园反向散射值与其他土地覆盖类型的重叠大大重叠。因此,在没有先验的种植园区域的知识,种植园监测需要数据源的组合。

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