极化雷达与光学遥感森林雪灾破坏协同监测

以贵州省扎佐林场为例,利用全极化雷达与光学遥感数据进行森林雪灾破坏状况协同监测,分析了倒伏森林与健康森林的后向散射特性及其差异,重点分析了倒伏森林与健康森林的极化响应特征、散射机制及其差异。基于雪灾破坏前后森林的散射机制变化,利用Freeman-Durden分解方法对倒伏森林进行了识别。为了进一步优化识别效果,引入了高分辨率光学数据,采用优选的融合方法, 将雷达与光学遥感数据融合,得到了较好的倒伏森林识别效果。研究结果表明,利用雷达与光学遥感数据协同监测森林雪灾破坏是可行的,而全极化雷达遥感数据在森林类型识别和森林破坏监测方面具有独特的优势,在我国西南地区的森林资源调查和灾害监测中具有广阔的应用前景。

Synergistically monitoring the snowstorm damaged forest with polarimetric SAR and optical remote sensing data

In this study, polarimetric SAR and optical remote sensing data were synergized to monitor snowstorm damaged forests in Zhazuo Forest Farm, Guizhou province, southwest of China. The backscatter coefficients of the snowstorm damaged forests, healthy forests and their difference were analyzed. In order to fully explore the potentiality of polarimetric SAR data, the polarimetric signature and scattering mechanism were investigated for both snowstorm damaged forests and healthy forests. Then, Freeman-Durden polarimetric decomposition was applied for the identification of snowstorm damaged forest based on the change of their scattering behaviors caused by snowstorm destruction. In order to further improve the results of snowstorm damaged forests identification, high-resolution optical data was introduced to synergize with polarimetric SAR data. The results showed that it was feasible using polarimetric SAR and optical remote sensing data to synergistically monitor the snowstorm damaged forests. Most notably, fully polarimetric SAR data had remarkable advantages in forest type identification and deforestation monitoring and was very promising for the survey of forest resources and disaster monitoring in southwestern of China.