首页> 外文会议>Asian conference on remote sensing >USING REMOTE SENSING TO MAP THE DISTRIBUTION OF SAGO PALMS IN NORTHEASTERN MINDANAO, PHILIPPINES: RESULTS BASED ON LANDSAT ETM+ IMAGE ANALYSIS
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USING REMOTE SENSING TO MAP THE DISTRIBUTION OF SAGO PALMS IN NORTHEASTERN MINDANAO, PHILIPPINES: RESULTS BASED ON LANDSAT ETM+ IMAGE ANALYSIS

机译:利用遥感来映射东北甘肃,菲律宾的Sago Palms的分布:基于Landsat ETM +图像分析的结果

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We present in this paper the results of our study that aims to map the distribution of the sago palm (Metroxylon sagu) in Agusan del Sur province in northeastern Mindanao, Philippines using remote sensing data and techniques. The sago palms have been reported to exist in marshlands and wetlands of northeastern Mindanao which are difficult to access and would be costly if mapped using conventional field mapping techniques. We tested the viability of Landsat ETM+ image to locate the distribution and abundance of the sago palm in the Agusan del Sur province. After radiometric calibration and atmospheric correction, the image was subjected to Maximum Likelihood classification to produce a land cover map showing the distribution of sago palms and other land-cover types. The classifier was trained and the accuracy of the results assessed using ground truth data of sago palm and other land-cover types that were collected between February and August 2012. Results of the supervised classification using combination of all the multispectral bands, NDVI and SRTM DEM showed an overall classification accuracy of 94.88%. A total of 597 hectares of sago palms were detected from the image analysis. The sago palm classification has 80.18% Producer's Accuracy and 82.66% User's Accuracies. This relatively low Producer and User's Accuracies of the sago palm classification may be attributed to three factors: (ⅰ) the similarities in the spectral characteristics of sago palm with other palm vegetation, especially coconut and oil palm; (ⅱ.) the 30-m spatial resolution of the Landsat ETM+ image may not be optimal for classifying specific vegetation species such as the sago palms, especially in areas where sago palms are interspersed with other land-cover types; and (ⅲ.) the differences in the date of image acquisition and the date of field surveys when the sago ground truth data were collected. Despite these low accuracies for sago palms, the location, extent and distribution of sago palms depicted in the derived land-cover map provides vital information as to where sago palms are deemed to be abundant in Agusan del Sur province.
机译:我们目前在本文中我们的研究结果,旨在映射西谷椰子(Metroxylon SAGU)在南阿古桑省东北部的棉兰老岛,菲律宾利用遥感数据和技术的分布。西米棕榈已报道在沼泽地和东北峨的湿地,其是难以进入的,并且如果使用常规的字段映射技术映射将是昂贵的存在。我们测试的Landsat ETM +图像的生存能力定位在南阿古桑省的西谷椰子的分布和数量。辐射校正和大气校正之后,图像进行最大似然分类,以产生表示西谷椰子和其他土地覆盖类型的分布的土地覆盖图。分类器进行训练,并且使用收集二月和八月间使用所有组合的多光谱波段监督分类的2012年结果西米棕榈等土地覆盖类型的地面真实数据,评估结果的准确性,NDVI和SRTM DEM显示出的94.88%的总体分类精度。共597公顷西谷椰子的从图像分析进行检测。西谷椰子分类有80.18%监制的精度和82.66%用户的准确度。此相对低的生产者和西谷椰子分类用户准确度可能是由于以下三个因素:(ⅰ)在西谷椰子与其它棕榈植被,尤其是椰子和油棕榈的光谱特性的相似; (ⅱ)陆地卫星ETM +图像的30米的空间分辨率可能不是特定植物种类进行分类,如西谷椰子的,特别是在西谷椰子的穿插着其他土地覆盖类型区域最佳;和(ⅲ)在图像采集的日期的差异和实地调查的日期时收集西米地面实况数据。尽管这些低精度为西谷椰子,位置,范围和西谷椰子的分布描绘在派生土地覆盖图提供了重要信息在何处西谷椰子的被认为是在南阿古桑省丰富。

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