Results 61 to 70 of about 131 (85)

L-Band UAVSAR Tomographic Imaging in Dense Forests: Gabon Forests

Remote Sensing, 2019
Developing and enhancing strategies to characterize actual forests structure is a timely challenge, particularly for tropical forests. P-band synthetic aperture radar (SAR) tomography (TomoSAR) has previously been demonstrated as a powerful tool for ...
Ibrahim El Moussawi, Dinh Ho Tong Minh, Nicolas Baghdadi, Chadi Abdallah, Jalal Jomaah, Olivier Strauss, Marco Lavalle   +6 more
doaj   +1 more source

Three-dimensional forest structure features extraction based on TomoSAR [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Forest structure is an important indicator for evaluating forest ecosystem and an indispensable input parameter for estimating forest carbon sink. Synthetic Aperture Radar (SAR) Tomography (TomoSAR), as a novel microwave remote sensing technique with 3D ...
Z. Hu, X. Peng, Q. Xie, T. Huang, Y. Wu
doaj   +1 more source

Single Target SAR 3D Reconstruction Based on Deep Learning. [PDF]

Sensors (Basel), 2021
Wang S, Guo J, Zhang Y, Hu Y, Ding C, Wu Y.   +5 more
europepmc   +1 more source

Demonstration of Spaceborne Multi-static SAR Tomography and Forest Height Estimation

Leida xuebao
Synthetic Aperture Radar Tomography (TomoSAR), by virtue of its three-dimensional (3D) resolution capability, can be used to study the 3D structure of semitransparent targets, such as forests, icebergs, and snowpacks.
Guobing ZENG, Huaping XU, Yuan WANG, Le ZHANG, Xianghua LIU   +4 more
doaj   +1 more source

Sparse Matching Filtering Algorithm for Tomographic SAR Imaging

Leida xuebao
Synthetic Aperture Radar Tomography (TomoSAR) has emerged as the primary technique for generating 3D SAR point clouds. In practice, ignoring the quadratic phase distribution in the elevation dimension causes defocusing artifacts due to inherent Fresnel ...
Hui LIU, Chunmeng ZHAO, Pengfei CHEN, Yanzhi WANG, Minghao QU, Ning XIAO   +5 more
doaj   +1 more source

STAMI: A machine learning-based small-scale tomography-aided multibaseline (Pol)InSAR forest height inversion framework

International Journal of Applied Earth Observations and Geoinformation
The complementary measurements of model-based multibaseline (polarimetric) synthetic aperture radar interferometry ((Pol)InSAR) and data-driven SAR tomography (TomoSAR) have become the development trend of forest height mapping missions.
Tianyi Song, Jie Yang, Weidong Sun, Lei Shi, Changcheng Wang, Pingxiang Li, Haiqiang Fu, Lingli Zhao, Peng Shen, Pingping Huang   +9 more
doaj   +1 more source

Hough Transform and Clustering for a 3-D Building Reconstruction with Tomographic SAR Point Clouds. [PDF]

Sensors (Basel), 2019
Liu H, Pang L, Li F, Guo Z.
europepmc   +1 more source

Automatic Regularization of TomoSAR Point Clouds for Buildings Using Neural Networks. [PDF]

Sensors (Basel), 2019
Zhou S, Li Y, Zhang F, Chen L, Bu X.
europepmc   +1 more source

A Maximum Likelihood Based Nonparametric Iterative Adaptive Method of Synthetic Aperture Radar Tomography and Its Application for Estimating Underlying Topography and Forest Height. [PDF]

Sensors (Basel), 2018
Peng X, Li X, Wang C, Fu H, Du Y.
europepmc   +1 more source

Azimuth Sidelobes Suppression Using Multi-Azimuth Angle Synthetic Aperture Radar Images. [PDF]

Sensors (Basel), 2019
Wang Y, Yang W, Chen J, Kuang H, Liu W, Li C.   +5 more
europepmc   +1 more source