Hybrid Algorithm for Deforestation Detection Using Satellite Data by Using Support Vector Machine (SVM) Algorithm

J. S. Babu, T. Sudha
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引用次数: 1

Abstract

There are many applications of Remote sensing Satellite images like (astronomy, military, forecasting, and geographical information). Using satellite remote sensing data sets we developed the mapping forest area cover change. This kind of multiple improvement and identifying methods have a Training Data Automation algorithm which is used for advanced vector machines procedure. This TDM technique capable of automatically generating exact image enhanced patches. The obtained high resolute training data allow in producing the dependable forest cover change products with the help of SVM. This process was tested in study areas selected from major forest areas across the globe. In each area, a forest cover change map was produced using a pair of real time Land sat images acquired around 1999 and 2015.
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基于支持向量机(SVM)算法的卫星毁林检测混合算法
遥感卫星图像在天文学、军事、气象预报、地理信息等方面有着广泛的应用。利用卫星遥感数据集开发了森林面积变化制图。这种多重改进和识别方法有一个用于高级向量机程序的训练数据自动化算法。这种TDM技术能够自动生成精确的图像增强补丁。得到的训练数据分辨率高,可以利用支持向量机生成可靠的森林覆盖变化产品。这一过程在从全球主要森林地区选择的研究区域进行了测试。在每个地区,使用1999年和2015年左右获得的一对实时陆地卫星图像制作了森林覆盖变化图。
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