首页> 外文会议>International Conference on Remote Sensing and Geoinformation of the Environment;Cyprus Remote Sensing Society;European Space Agency >Comparison of classification algorithms on optical satellite imagery for mapping Posidonia Oceanica meadows: The case study of Limassol, Cyprus
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Comparison of classification algorithms on optical satellite imagery for mapping Posidonia Oceanica meadows: The case study of Limassol, Cyprus

机译:光学卫星影像分类算法在大洋波塞冬草草甸制图中的比较:以塞浦路斯利马索尔为例

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Posidonia Oceanica meadows are important marine ecosystems that offer habitat to fish, organisms, and shelter forthreatened species as well. This study compares classification algorithms for the validity of Posidoniaoceanica mappingthrough optical satellite imagery in the region of Limassol – Akrotiri bay. More specifically, side-scan sonar mappeddata derived from the portal of the Department of Lands and Surveys and imported to the ArcGIS WMS service, as wellas a Landsat 8 satellite image for the region of Cyprus were used. Training data and regions of interest (ROI) werecreated, followed by supervised classification using Spectral Angle Mapper, Mahalanobis Distance, MaximumLikelihood and Minimum Distance algorithms in ENVI 5.4 software. A sample of 1,000 random points was added to thestudy area before conducting a relative comparison to test the performance of the algorithms used. Since, there weren’tany raw data to automate the comparison of the algorithms, a random manual selection of 30 points was considered.
机译:Posidonia Oceanica草甸是重要的海洋生态系统,为鱼类,生物和栖息地提供栖息地。 以及受威胁的物种。这项研究比较了Posidoniaoceanica制图有效性的分类算法 通过利马索尔–阿克罗蒂里海湾地区的光学卫星图像。更具体地说,侧面扫描声纳映射 数据来自国土测量部门户网站,也导入到ArcGIS WMS服务中 作为塞浦路斯地区的Landsat 8卫星图像,被使用。训练数据和感兴趣区域(ROI)为 创建,然后使用“光谱角度映射器”,“马氏距离”,“最大”进行监督分类 ENVI 5.4软件中的可能性和最小距离算法。将1000个随机点的样本添加到 在进行相对比较之前,先研究区域以测试所使用算法的性能。从那以后,没有 任何原始数据以自动比较算法,均考虑了30个点的随机手动选择。

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