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首页> 外文期刊>Journal of Forest Planning >Application of Automatic Binarization Method for Nationwide Forest Area Mapping using Satellite Imagery
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Application of Automatic Binarization Method for Nationwide Forest Area Mapping using Satellite Imagery

机译:自动二值化方法在卫星影像全国森林制图中的应用

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Article 3.3 of the Kyoto protocol obligates nations to report reduced amount of carbon dioxide (C0_2) emission, and allows including C0_2 absorption by Afforestation (A), Reforestation (R), and Deforestation (D) activities to the amount of carbon accounting. So it is necessary to clarify ARD location after the end of 1989. The primary objective of this study is developing a forest area mapping method using satellite images. We applied two classification methods, Decision Tree Classification (DTC) andSpectral Shape Classification (SSC) to classify forest area using a Landsat Thematic Mapper image over a test site in Higashi-Shirakawa village in Gifu Prefecture. An automatic binarization of digital number of a band (band 3 or band 7) and the normalized difference vegetation index was applied in DTC. The accuracy was evaluated using a ground truth map which was produced using aerial orthophotos by a visual interpretation, and DTC gave a slightly more accurate result than that of SSC. The binalizationusing band 3 showed better classification between forest and non-forest area than that using band 7. Moreover, DTC was better than SSC in classifying forest and non-forest area using two Enhanced Thematic Mapper Plus images in a validation of classification stability. Therefore, we concluded that DTC gave more stable results than SSC.
机译:《京都议定书》第3.3条规定各国有义务报告减少的二氧化碳(C0_2)排放量,并允许将造林活动(A),再造林活动(R)和毁林活动(D)吸收的C0_2纳入碳核算的数量。因此,有必要在1989年底后弄清ARD的位置。本研究的主要目的是开发一种利用卫星图像进行森林面积制图的方法。我们在岐阜县东白川村的一个测试点上,使用Landsat专题测绘仪图像,应用决策树分类(DTC)和光谱形状分类(SSC)这两种分类方法,使用Landsat Thematic Mapper图像对森林区域进行分类。在DTC中对波段(波段3或波段7)的数字和归一化的差异植被指数进行自动二值化。使用地面真相图评估准确性,该真相图是使用航空正射影像通过视觉解释生成的,而DTC的结果比SSC的结果稍准确。在使用波段3进行二值化处理时,在森林和非森林区域之间的分类要比使用波段7更好。而且,在验证分类稳定性方面,使用两张Enhanced Thematic Mapper Plus图像对森林和非森林区域进行分类时DTC优于SSC。因此,我们得出的结论是DTC比SSC提供了更稳定的结果。

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