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:利用遥感来绘制菲律宾棉兰老东北部萨戈棕榈的分布图: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:我们在本文中介绍了我们的研究结果,该研究旨在利用遥感数据和技术绘制菲律宾棉兰老岛东北部阿古桑德尔苏尔省的西米棕榈树(Metroxylon sagu)的分布图。据报道,西米棕榈存在于棉兰老岛东北部的沼泽地和湿地中,这些地方很难接近,如果使用常规的野外测绘技术进行测绘,成本将会很高。我们测试了Landsat ETM +图像的可行性,以定位南阿古桑省西米棕榈的分布和丰度。在进行辐射定标和大气校正之后,对图像进行了最大似然分类,以生成一张土地覆盖图,该地图显示了西米棕榈树和其他土地覆盖类型的分布。训练了分类器,并使用了西米棕榈和其他土地覆盖类型的地面真实数据(在2012年2月至2012年8月之间收集)来评估结果的准确性。使用所有多光谱波段,NDVI和SRTM DEM的组合进行监督分类的结果显示总分类准确度为94.88%。从图像分析中总共检测出597公顷的西棕榈。西米棕榈分类具有80.18%的生产者准确度和82.66%的用户准确度。西米棕榈分类的相对较低的生产者和使用者准确性可能归因于三个因素:(ⅰ)西米棕榈的光谱特征与其他棕榈植物,尤其是椰子和油棕的光谱特征相似; (ⅱ。)Landsat ETM +图像的30米空间分辨率可能不适用于分类特定的植物物种,例如西米棕榈,特别是在西米棕榈与其他土地覆盖类型点缀的区域中; (ⅲ。)采集西米地面实况数据时的图像获取日期与实地调查日期之间的差异。尽管西米棕榈的准确性较低,但在衍生的土地覆盖地图中所描绘的西米棕榈的位置,范围和分布仍可提供有关在南阿古桑省哪些地方的西米棕榈丰富的重要信息。

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