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Envisat卫星ASAR传感器的双极化数据对区域森林监测十分有效。通过分别采用SRTM DEM和Landsat TM图像对地形起伏区域和平坦区域的SAR图像进行地理编码,发展了一种SAR图像自动预处理方法。基于冬季单时相ASAR数据的HH(水平发射,水平接收)、HV(水平发射,垂直接收)极化比值和HV极化图像,提出了一种面向对象的森林-非森林分类方法。将之应用于中国东北森林/非森林制图,分类总体精度、森林用户精度和生产者精度分别为83.7%,85.6%和75.7%。结果表明,本文提出的方法十分适合区域森林-非森林制图的业务化运行。
Dual polarization data from the Envisat satellite ASAR sensor is very useful for regional forest monitoring. By using SRTM DEM and Landsat TM images respectively to geocode the SAR image of relief area and flat area, an automatic SAR image preprocessing method is developed. Based on the HH (horizontal emission, horizontal reception), HV (horizontal emission, vertical reception) polarization ratio and HV polarization image of single-phase ASAR data in winter, an object-oriented forest-non-forest classification method is proposed. Applying it to forest / non-forest mapping in Northeast China, the overall classification accuracy, forest user accuracy and producer precision were 83.7%, 85.6% and 75.7%, respectively. The results show that the proposed method is very suitable for the operationalization of regional forest-non-forest mapping.