The backscattering characteristics of wetland vegetation and water-level changes detection using multi-mode SAR: A case study
The backscattering characteristics of wetland vegetation and water-level changes detection using multi-mode SAR: A case study
复制标题
湿地植被后向散射特性及多模SAR水位变化检测：案例研究
DOI：
10.1016/j.jag.2015.10.001
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发表时间：
2016-03
影响因子：
7.5
通讯作者：
Panpan Tang
中科院分区：
文献类型：
--
作者：
Meimei Zhang;Zhen Li;Bangsen Tian;Jianmin Zhou;Panpan Tang
A full understanding of the backscattering characteristics of wetlands is necessary for the analysis of the hydrological conditions. In this study, a temporal set of synthetic aperture radar (SAR) imagery, acquired at different frequencies, polarizations and incidence angles over the coastal wetlands of the Liaohe River Delta, China, were used to characterize seasonal variations in radar backscattering coefficient for reed marshes and rice fields. The combination of SAR backscattering intensity and an optical-based normalized difference vegetation index (NDVI) for long time series can provide additional insight into vegetation structural and its hydrological states. After identifying the factors that induce the backscattering and scattering mechanism changes, detailed analysis of L-band ALOS PALSAR interferometric SAR (InSAR) imagery was conducted to study water-level changes under different environmental conditions. In addition, ENVISAT altimetry was used to validate the accuracy of the water-level changes estimated using the InSAR technique—this is an effective tool instead of sparsely distributed gauge stations for the validation. Our study demonstrates that L-band SAR data with horizontal polarization is particularly suitable for the extraction of water-level changes in the study area; however, vertically-polarized C-band data may also be useful where the density of herbaceous vegetation is low at the initial stage. It is also shown that integrated analysis of the backscattering mechanism and interferometric characteristics using multi-mode SAR can considerably enhance the reliability of the water-level retrieval scheme and better capture the spatial distribution of hydrological patterns.
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影响因子：
1.3
作者：
E. Kasischke;L. Bourgeau-Chavez
通讯作者：
E. Kasischke;L. Bourgeau-Chavez
影响因子：
13.5
作者：
Jinwoo Kim;Zhong Lu;John W. Jones;C. Shum;H. Lee;Yuanyuan Jia;J.-W Kim
通讯作者：
Jinwoo Kim;Zhong Lu;John W. Jones;C. Shum;H. Lee;Yuanyuan Jia;J.-W Kim
影响因子：
8.2
作者：
Sang-Wan Kim;S. Wdowinski;F. Amelung;T. Dixon;Joong-Sun Won
通讯作者：
Sang-Wan Kim;S. Wdowinski;F. Amelung;T. Dixon;Joong-Sun Won
影响因子：
13.5
作者：
B. Martí-Cardona;J. Dolz-Ripollés;C. López-Martínez
通讯作者：
B. Martí-Cardona;J. Dolz-Ripollés;C. López-Martínez
DOI：
10.1007/978-3-642-11741-1_11
发表时间：
2010
期刊：
--
影响因子：
--
作者：
Ye Xia
通讯作者：
Ye Xia