Development of forest information measurement algorithms toward CO2 reduction by high-resolution polarimetric and interferometric synthetic aperture radars

在森林作为二氧化碳吸收来源需要一致和全球信息的背景下，通过融合机载合成孔径雷达(SAR)和星载高分辨率光学传感器获取的数据，以及北海道Tomakomai国家森林试验场的极化和干涉SAR数据，开发了提取森林破坏区域的算法。在此基础上，提出了一种新的基于雷达图像二次强度矩的稳健算法，用于森林生物量的测量，其精度高于常规方法。

Under the background that consistent and global information is required on the forests as being a source of CO2 absorption, algorithms were developed to extract areas of forest damage by fusing data acquired by airborne synthetic aperture radar (SAR) and spaceborne high-resolution optical sensor, and polarimetric and interferometric SAR over the test site of Tomakomai national forests in Hokkaido. Further, a new robust algorithm based on the second intensity moment of radar images was developed to measure forest biomass with accuracy higher than the conventional methods.