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A study of the potential of using worldview-2 of images for the detection of red attack pine tree

机译:使用WorldView-2的潜力研究红色攻击杉树检测

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Forest disturbances in South China caused by pine wood nematode may result in widespread tree mortality. In order to decrease damage to forest ecosystem and huge loss to national economy, early detection, early diagnosis to individual infected tree is essential to forest management agencies. However field survey is hard to achieve the fine management requirements. Satellite remote sensing technology has the characteristics of landscape of coverage, convenient, and fast in formation acquisition, so it is one of the most important and most effective means of red attack monitoring. The support vector machine(SVM) classification algorithm have been proposed as an alternative for classification of remote sensing data. The study is based on a multispectral Worldview-2(WV-2) scene and uses support vector machine(SVM) methods. We compared the eight bands with three bands of the image based on SVM and came to the conclusion that WorldView-2 are suitable for individual tree identification. Three visible bands spectral data can also discriminate discolored individual tree successfully. In other words, three visible bands of remote sensing can meet the requirements of red attack pine estimation and extraction.
机译:华南地区森林骚乱由松木线虫引起的,可能导致广泛的树死亡率。为了减少森林生态系统的损害和国民经济的巨大损失,早期检测,对个体感染树的早期诊断对森林管理机构至关重要。然而,现场调查很难实现精细的管理要求。卫星遥感技术具有覆盖范围的特点,方便,在地层采集中快速,因此它是最重要,最有效的红色攻击监测手段之一。已经提出了支持向量机(SVM)分类算法作为遥感数据分类的替代方案。该研究基于多光谱WorldView-2(WV-2)场景,并使用支持向量机(SVM)方法。我们比较了基于SVM的三个频段的八个频带,并得出了普遍观点-2适用于个体树识别。三个可见频带谱数据也可以成功区分变色的单个树。换句话说,三个可见频带的遥感可以满足红色攻击松树估计和提取的要求。

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