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《Chinese Agricultural Science Bulletin》 2014-28
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Forest Vegetation Information Computer Automatic Extraction Base on Landsat-8

Zhang Ying;Wang Yuenan;Chen Li;Liu Xiuying;Henan Radio & Television University;Anhua Forestry;Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry & Technology;Agronomy College, Henan University of Science and Technology;  
Landsat-8 with two main load, OLI(operational land imager) and TIRS(thermal infrared sensor),can provide 15 m panchromatic band and 30 m resolution multispectral bands. OLI included nine bands, TIRS included two hot red bands, pan band 8 was narrower. This approach can better distinguish between vegetation and no vegetation characteristics on the full-color image. In this study, taking Youxian for example, after tasseled cap transformation and principal component analyzing and processing based on Lands at-8 remote sensing image, vegetation was extracted by using decision tree classification model. The results showed that:the Land sat-8 after tasseled cap transformation and principal component analyzing and processing could significantly enhance the texture information of the image, and highlight the land features. After tasseled cap transformation and processing of principal component analysis, put the gray values as a threshold of decisiontree classification and used the computer automatic extraction, the overall accuracy was 84.7%, with an area of forest vegetation of 150911.7 hm2. Compared with the previous threshold band using only gray values and vegetation index, the accuracy was significantly increased and the method was also improved, which could led to better extraction results.
【Fund】: 河南省2013年科技攻关项目“冬小麦主要生理指标的高光谱定量提取与应用研究”(132102110210)
【CateGory Index】: TP751;S718.5
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