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.

Envisat Advanced Synthetic Aperture Radar (ASAR) dual-polarization data are shown to be effective for regional forest monitoring. To this scope, an automatic SAR image preprocessing procedure was developed using SRTM DEM and Landsat TM image for geocoding in rugged terrain and smooth terrain areas, respectively. An object-oriented forest and non-forest classif ication method was then proposed based on the HH (horizontal transmit and horizontal receive) to HV (horizontal transmit and vertical receive) polarization intensity ratio and HV images of ASAR data at single acquisition time in winter. The developed method was applied to forest and non-forest mapping in Northeast China. The overall accuracy, the user’s accuracy and the producer’s accuracy of forest were 83.7%, 85.6% and 75.7%, respectively. These results indicate that the proposed method is promising for operational forest mapping at regional scale.