The impacts of spatial baseline on forest canopy height model and digital terrain model retrieval using P-band PolInSAR data
The impacts of spatial baseline on forest canopy height model and digital terrain model retrieval using P-band PolInSAR data
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空间基线对森林冠层高度模型和利用P波段PolInSAR数据反演数字地形模型的影响
DOI：
10.1016/j.rse.2018.03.033
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发表时间：
2018-06
影响因子：
13.5
通讯作者：
Quan Xingwen
中科院分区：
文献类型：
--
作者：
Liao Zhanmang;He Binbin;van Dijk Albert I J M;Bai Xiaojing;Quan Xingwen
Polarimetric Synthetic Aperture Radar Interferometry (PolInSAR) has shown potential for the retrieval of a forest canopy height model (CHM) and the underlying solid earth digital terrain model (DTM). However, because of non-volume decorrelation and other unavoidable errors, the robustness of retrieval heights is sensitive to the spatial baseline of the selected InSAR pairs, which relates forest parameters to measured coherence. Within the context of the random volume over ground (RVoG) model and the three-stage inversion method, we aimed to quantify the influence of spatial baseline on the inversions at P-band, which are distinct from the inversions at higher frequency due to the non-negligible ground contributions. This information assists in optimal baseline selection and the development of robust inversion schemes. Assumptions about the extinction coefficient and additional DTM or DEM were used to reduce the influence of ground contribution on CHM and DTM inversion, respectively. Inversions from published airborne repeat-pass P-band PolInSAR data with four different spatial baselines were validated against LiDAR-derived DTM and CHM data. The results show that a longer spatial baseline performed better in DTM inversion. The longest baseline produced the best R2of 0.995 and RMSE of 0.555 m, much better than the smallest baseline with an R2of 0.794 and RMSE of 3.74 m. A threshold height could be identified that determines the overestimation and underestimation of CHM inversion due to the non-volume decorrelation. Different baselines produced different threshold heights, making CHM inversion only accurate for a limited range of forest height around the threshold. The optimal baseline produced a CHM with R2of 0.605 and RMSE of 2.67 m. Additionally, we found that using multiple baselines has the potential to improve CHM inversion, improving the R2to 0.827 and RMSE to 0.876 m in our study.
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影响因子：
1.6
作者：
R. Treuhaft;S. Madsen;M. Moghaddam;J. V. Zyl
通讯作者：
R. Treuhaft;S. Madsen;M. Moghaddam;J. V. Zyl
影响因子：
20.6
作者：
GRAHAM, LC
通讯作者：
GRAHAM, LC
使用高分辨率 P 波段单基线 PolInSAR 数据对森林地区进行基础地形估计
影响因子：
5
作者：
Fu, Haiqiang;Zhu, Jianjun;Zhao, Rong
通讯作者：
Zhao, Rong
DOI：
10.1109/tgrs.2013.2296533
发表时间：
2014-10-01
影响因子：
8.2
作者：
Kugler, Florian;Schulze, Daniel;Papathanassiou, Konstantinos P.
通讯作者：
Papathanassiou, Konstantinos P.
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