首页> 外文会议>ACRS 2010;Asian conference on remote sensing >IDENTIFICATION OF WOODY PLANTATION SPECIES IN INSULAR SOUTHEAST ASIA USING 50M RESOLUTION ALOS PALSAR MOSAIC
【24h】

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

机译:使用50M分辨率ALOS PALSAR MOSAIC识别东南亚绝缘木造林树种

获取原文

摘要

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:东南亚岛屿地区主要有四种木本造林:油棕(Elaeis guineensis),橡胶(Hevea brasiliensis),荆棘(Acacia spp。)和椰子(Cocos nucifera)。由于其冠层穿透能力,Daichi-Advanced Land Observing Satellite(ALOS)相控阵型L波段合成孔径雷达(PALSAR)数据可提供有关冠层/人工林结构的信息,并有可能实现人工林物种识别。在这项研究中,我们使用在马来西亚半岛和印度尼西亚廖内市选定的41个采样点的50m分辨率正校正ALOS PALSAR双极化(HH和HV)数据分析了封闭冠层人工林中四种人工林的可分性。 HH和HV背向散射(HH-HV)之间的差异显示了棕榈和其他木本人工林之间的高度可分离性。此外,仅靠HV后向散射就可以使荆树园和橡胶园分开。在大约20000km2的区域内,基于决策树的分类测试(分为棕榈树,荆树和橡胶树)的准确性评估显示出86%的总体准确性,其中94%的用户对棕榈种植园进行识别的准确性。因此,我们的结果表明,ALOS PALSAR数据可以在已知的封闭树冠种植区中分离橡胶,荆树和棕榈(油棕和椰子)。但这并没有显示出将油棕和椰子种植园分开的潜力。但是,还揭示了人工林的反向散射值与其他土地覆被类型的反向散射值有很大的重叠。因此,在没有人工林面积的先验知识的情况下,需要数据源的组合来进行人工林监测。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号