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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：利用世界观2图像检测红色攻击松树的潜力的研究

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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：松木线虫引起的华南森林干扰可能导致广泛的树木死亡。为了减少对森林生态系统的破坏和对国民经济的巨大损失，对早期被感染树的早期发现，早期诊断对于森林管理机构至关重要。但是，实地调查很难达到精细管理的要求。卫星遥感技术具有覆盖面广，方便，编队获取快的特点，是红色攻击监测最重要，最有效的手段之一。提出了支持向量机（SVM）分类算法作为遥感数据分类的一种替代方法。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。我们将基于SVM的8个波段与3个波段的图像进行了比较，得出的结论是WorldView-2适合于单个树的识别。三个可见波段的光谱数据还可以成功地区分变色的单个树。换句话说，三个可见的遥感波段可以满足红松的估计和提取要求。

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