Underlying topography and forest height estimation from SAR tomography based on a nonparametric spectrum estimation method with low sidelobes

Youjun Wanga School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, People’s Republic of China

https://orcid.org/0000-0003-2461-2477 View further author information

Xing Penga School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, People’s Republic of ChinaCorrespondence[email protected]
View further author information

Qinghua Xiea School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, People’s Republic of ChinaView further author information

Xinwu Lib Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, People’s Republic of ChinaView further author information

Xiaomin Luoa School of Geography and Information Engineering, China University of Geosciences (Wuhan), Wuhan, People’s Republic of ChinaView further author information

Yanan Duc School of Geographical Sciences, Guangzhou University, Guangzhou, People’s Republic of ChinaView further author information

Bing Zhangd School of Geomatics, Liaoning Technical University, Fuxin, People’s Republic of ChinaView further author information

show all

Underlying topography and forest height estimation from SAR tomography based on a nonparametric spectrum estimation method with low sidelobes

Information for

Open access

Opportunities

Help and information

Your download is now in progress and you may close this window

Login or register to access this feature

Underlying topography and forest height estimation from SAR tomography based on a nonparametric spectrum estimation method with low sidelobes

Reprints and Permissions

Related research

To cite this article:

Download citation

Information for

Open access

Opportunities

Help and information

Keep up to date