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Mapping of Prosopis Juliflora by a Fusion assisted Pattern Based Classification

机译:基于融合辅助模式的分类对朱s的映射

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This paper proposes a fusion assisted classification method to locate and map invasive plant species, Prosopis Juliflora using remote sensing techniques towards conservation of biodiversity. This is two stage method. At first, wavelet based fusion method is proposed for the multispectral image to produce high resolution multispectral image.In the second stage a texture based classification is performed ith pattern study.Minimum distance classifier is used to classify the input image based on weighted texture features. Accuracy is computed by collecting the ground truth points from the study site. Similar procedure is repeated for the Google Maps data and accuracy comparison of World View 2 and Google Maps is carried out. Thus World View 2 data outperform Google Maps data by achieving accuwracy of 80 percentage.
机译:本文提出了一种融合辅助分类方法,利用遥感技术对生物多样性的保护进行定位和作图,对入侵的植物物种Prosopis Juliflora进行定位和作图。这是两个阶段的方法。首先提出了基于小波的融合方法来产生高分辨率的多光谱图像。在第二阶段,通过图案研究进行了基于纹理的分类。使用最小距离分类器基于加权纹理特征对输入图像进行分类。准确度是通过从研究地点收集地面真实点来计算的。对Google Maps数据重复类似的过程,并进行World View 2和Google Maps的准确性比较。因此,World View 2数据的准确度达到80%,胜过Google Maps数据。

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