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A Simple Class-Set Based Vegetation Classification of a South Pacific Volcanic Island (Moorea Island, French Polynesia) using Both AirSAR and MASTER Data

机译:一种简单的基于南太平洋火山岛(Moorea Island,法国波利尼西亚)的简单基于植被分类,使用了Airsar和掌握数据

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This paper addresses the vegetation mapping and land use of Opunohu Valley (Moorea Island -French Polynesia) using JPL-AirSAR and MASTER (MODIS/ASTER simulator) images. We first define an original set of classes based on the relative canopy-height of vegetation, out of a well-suited RGB SAR-composite image that visually discriminates our vegetation classes. An interesting "pineapple fields" class (an impoitant economic resource in Moorea island) proves to discriminate particularly from the height-related "Low Vegetation" class. Two supervised maximum likelihood classification maps have been processed on both the AirSAR and the MASTER images, using aerial photographs as a ground truth training set. The vegetal species included in each class as well as the classification results are discussed. Comparison of the MASTER and AirSAR based classification results leads us to propose a fusion of AirSAR and MASTER classification maps keeping the best of both worlds in order to improve the overall accuracy of the AirSAR classification.
机译:本文使用JPL-Airsar和Master(MODIS / ASTER SIMULICATOR)图像来解决Opunohu谷(Moorea Island-Fernch Polynesia)的植被映射和土地利用。我们首先根据植被的相对冠层高度定义一组原始的类,从视觉上辨别我们的植被课程的良好的RGB SAR型图像。一个有趣的“菠萝田”课程(Moorea Island中的实证经济资源)证明了特别是与与高度相关的“低植被”课歧视。两个监督的最大似然分类地图已经在Airsar和主图像上处理,使用空中照片作为地面真理训练集。讨论了每个班级中包含的植物和分类结果。基于硕士和航空的分类结果的比较导致我们提出了航空和主分类地图的融合,以保持两个世界的最佳措施,以提高航空分类的整体准确性。

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