极化雷达与光学遥感森林雪灾破坏协同监测

doi:10.3969/j.issn.1000-2006.2014.04.001

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南京林业大学学报（自然科学版） ›› 2014, Vol. 38 ›› Issue (04): 1-6.doi: 10.3969/j.issn.1000-2006.2014.04.001

极化雷达与光学遥感森林雪灾破坏协同监测

徐茂松¹, 李坤^2*, 谢酬², 朱松³, 罗洪章³, 张风丽², 王雪军¹, 夏忠胜³,党永峰¹

1. 国家林业局调查规划设计院,北京 100714;
2. 中国科学院遥感与数字地球研究所,北京 100101;
3. 贵州省林业厅森林资源管理站,贵州贵阳 550001

出版日期:2014-07-31 发布日期:2014-07-31
基金资助:
收稿日期:2013-05-10 修回日期:2013-11-20
基金项目:中国科学院知识创新工程重要方向项目(KZCX2-EW-320); 国家高技术研究发展计划(2007AA12Z146); 贵州省省长基金项目([2008]82)
第一作者:徐茂松,高级工程师,硕士。*通信作者:李坤,助理研究员,博士。E-mail: kunli@irsa.ac.cn。
引文格式:徐茂松, 李坤, 谢酬,等. 极化雷达与光学遥感森林雪灾破坏协同监测[J]. 南京林业大学学报:自然科学版,2014,38(4):1-6.

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

XU Maosong¹, LI Kun^2*, XIE Chou², ZHU Song³, LUO Hongzhang³, ZHANG Fengli², WANG Xuejun¹, XIA Zhongsheng³, DANG Yongfeng¹

1. Academy of Forestry Inventory, Planning and Designing, State Forestry Administration, Beijing 100714, China;
2. Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;
3. Forest Resource Management and Conservation Station, Department of Forestry of Guizhou Province, Guiyang 550001, China

Online:2014-07-31 Published:2014-07-31

摘要/Abstract

摘要： 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。

Abstract: 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.

中图分类号:

S757
TP79

徐茂松,李坤,谢酬,等. 极化雷达与光学遥感森林雪灾破坏协同监测[J]. 南京林业大学学报（自然科学版）, 2014, 38(04): 1-6.

XU Maosong, LI Kun, XIE Chou, ZHU Song, LUO Hongzhang, ZHANG Fengli, WANG Xuejun, XIA Zhongsheng, DANG Yongfeng. Synergistically monitoring the snowstorm damaged forest with polarimetric SAR and optical remote sensing data[J].Journal of Nanjing Forestry University (Natural Science Edition), 2014, 38(04): 1-6.DOI: 10.3969/j.issn.1000-2006.2014.04.001.

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极化雷达与光学遥感森林雪灾破坏协同监测

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

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