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孙存举, 梁楠. 遥感光谱混合模型在成都城区植被信息提取中的应用[J]. 四川林业科技, 2014, 35(5): 84-87. DOI: 10.16779/j.cnki.1003-5508.2014.05.018
引用本文: 孙存举, 梁楠. 遥感光谱混合模型在成都城区植被信息提取中的应用[J]. 四川林业科技, 2014, 35(5): 84-87. DOI: 10.16779/j.cnki.1003-5508.2014.05.018
SUN Cun-ju, LIANG Nan. Application of the Spectral Mixture Model in Extracting Vegetation Information in Chengdu City[J]. Journal of Sichuan Forestry Science and Technology, 2014, 35(5): 84-87. DOI: 10.16779/j.cnki.1003-5508.2014.05.018
Citation: SUN Cun-ju, LIANG Nan. Application of the Spectral Mixture Model in Extracting Vegetation Information in Chengdu City[J]. Journal of Sichuan Forestry Science and Technology, 2014, 35(5): 84-87. DOI: 10.16779/j.cnki.1003-5508.2014.05.018

遥感光谱混合模型在成都城区植被信息提取中的应用

Application of the Spectral Mixture Model in Extracting Vegetation Information in Chengdu City

  • 摘要: 本文以2013年4月20日获取的美国陆地卫星Landsat8成都城区遥感数据为数据源,运用混合光谱模型技术从遥感影像中提取植被信息。通过线性光谱混合模型和最小噪音分离变换后的前3个分量,测算得到植被、低反照率、高反照率和土壤4个不同的城市土地覆盖的终端地类,最终得到研究区的植被覆盖度影像。

     

    Abstract: Landsat 8 images acquired on 20th of April in 2013 were used to extract vegetation information through a spectral mixture model in this research. Taking Chengdu city as an example, primary image was transferred into 7 bands through minimum noise fraction analysis and the first three bands were used to calculate the pure pixels. Four members including low-albedo building, high-albedo building, vegetation, and soil were selected as the input variables of land cover class terminal. Finally the vegetation coverage images in the study area were estimated.

     

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