路春燕, 王宗明, 贾明明, 张晶, 满卫东, 毛德华. 基于ENVISAT ASAR、Landsat TM与DEM的泥炭沼泽信息提取方法[J]. 武汉大学学报 ( 信息科学版), 2017, 42(2): 185-192. DOI: 10.13203/j.whugis20140669
引用本文: 路春燕, 王宗明, 贾明明, 张晶, 满卫东, 毛德华. 基于ENVISAT ASAR、Landsat TM与DEM的泥炭沼泽信息提取方法[J]. 武汉大学学报 ( 信息科学版), 2017, 42(2): 185-192. DOI: 10.13203/j.whugis20140669
shu
LU Chunyan, WANG Zongming, JIA Mingming, ZHANG Jing, MAN Weidong, MAO Dehua. Peatland Extraction Based on ENVISAT ASAR, Landsat TM and DEM Data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(2): 185-192. DOI: 10.13203/j.whugis20140669
Citation: LU Chunyan, WANG Zongming, JIA Mingming, ZHANG Jing, MAN Weidong, MAO Dehua. Peatland Extraction Based on ENVISAT ASAR, Landsat TM and DEM Data[J]. Geomatics and Information Science of Wuhan University, 2017, 42(2): 185-192. DOI: 10.13203/j.whugis20140669
shu

基于ENVISAT ASAR、Landsat TM与DEM的泥炭沼泽信息提取方法

Peatland Extraction Based on ENVISAT ASAR, Landsat TM and DEM Data

    摘要
  • 摘要: 泥炭沼泽是重要的湿地类型之一，对全球变化和生态平衡具有重要意义。本研究在野外实地调查和对比不同地物类型在不同极化方式下雷达影像后向散射系数差异的基础上，以ENVISAT ASAR、Landsat TM与数字高程模型（digital elevation model，DEM）数据为基本信息源，利用面向对象与决策树分类相结合的遥感影像分类方法，实现对小兴安岭西部泥炭沼泽典型分布区不同泥炭沼泽类型的空间分布信息提取，总体分类精度93.54%，Kappa系数0.92。结果表明，该方法在泥炭沼泽信息提取方面具有较大的应用潜力，相对于先前的研究，在分类精度上有一定的提高。

     

    Abstract: Peatlands are one of the most important types of wetlands and significant to the balance of global change and ecosystems. On the basis of field investigation and backscatter coefficient comparison of different land cover types in different polarization radar images, ENVISAT ASAR, Landsat TM, and DEM data were taken as basic data for a classification method combining object-oriented and decision tree approaches that were to extract peatlands and adjacent land cover types in a typical peatland zone located in West Xiao-Xing'an Mountains. The overall classification accuracy was 93.54% with a Kappa coefficient of 0.92, which indicates that the proposed method used is effective for peatland extraction. Compared to previous work, there is some improvement in classification accuracy.

     

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