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极化雷达与光学遥感森林雪灾破坏协同监测(PDF)

《南京林业大学学报(自然科学版)》[ISSN:1000-2006/CN:32-1161/S]

Issue:
2014年04期
Page:
1-6
Column:
专题报道
publishdate:
2014-07-01

Article Info:/Info

Title:
Synergistically monitoring the snowstorm damaged forest with polarimetric SAR and optical remote sensing data
Article ID:
1000-2006(2014)04-0001-06
Author(s):
XU Maosong1 LI Kun2* 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
Keywords:
forest monitoring snow damage polarimetric SAR optical remote sensing polarimetric decomposition
Classification number :
S757; TP79
DOI:
10.3969/j.issn.1000-2006.2014.04.001
Document Code:
A
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.

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Last Update: 2014-07-31