Results 61 to 70 of about 2,397 (207)

Exploring Polarimetric Properties Preservation for PolSAR Image Reconstruction With Complex‐Valued Convolutional Neural Networks

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
Polarimetric SAR data's inherent complex‐valued nature demands algorithms that work directly with complex representations, yet most deep‐learning approaches sidestep this by converting to the real domain. We implement and evaluate complex‐valued convolutional autoencoders that compress and accurately reconstruct full‐polarimetric SAR signals—preserving
Quentin Gabot, Joana Frontera‐Pons, Jérémy Fix, Chengfang Ren, Jean‐Philippe Ovarlez   +4 more
wiley   +1 more source

Polarimetric Incoherent Target Decomposition by Means of Independent Component Analysis [PDF]

, 2015
International audienceThis paper presents an alternative approach for polarimetric incoherent target decomposition dedicated to the analysis of very-high resolution POLSAR images.
Besic, Nikola, Chanussot, Jocelyn, Stankovic, Srdjan, Vasile, Gabriel   +3 more
core   +3 more sources

Using Texture‐Based Image Segmentation and Machine Learning With High‐Resolution Satellite Imagery to Assess Permafrost Degradation Landforms in the Russian High Arctic

Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 3, September 2025.
Abstract Amplified climate change across the Arctic causes significant permafrost thaw and an increase of permafrost degradation landforms. These landforms range from fine‐scale degrading ice wedge‐polygon‐networks to large‐scale features such as thermo‐erosional gullies and reshape entire landscapes.
Cornelia M. Inauen, Ingmar Nitze, Moritz Langer, Anne Morgenstern, Irena Hajnsek, Guido Grosse   +5 more
wiley   +1 more source

Improvement of PolSAR Decomposition Scattering Powers Using a Relative Decorrelation Measure

, 2017
In this letter, a methodology is proposed to improve the scattering powers obtained from model-based decomposition using Polarimetric Synthetic Aperture Radar (PolSAR) data.
Bhattacharya, A., Ratha, D., Surendar, M.   +2 more
core   +1 more source

Aboveground biomass estimation of an old‐growth mangrove forest using airborne LiDAR in the Philippines

Ecological Research, Volume 40, Issue 2, Page 120-132, March 2025.
Using airborne light ranging and light detection (LiDAR) data of the Phil‐LiDAR 1 project, we attempted to develop models to estimate the above‐ground biomass AGB of an old‐growth mangrove forest in the KII Ecopark, Panay Island, Philippines. The common allometric model method showed a large underestimation of AGB for plots with higher canopy heights ...
Mohammad Shamim Hasan Mandal, Rempei Suwa, Rene N. Rollon, Giannina Marie G. Albano, Green Ann A. Cruz, Kenji Ono, Yasmin H. Primavera‐Tirol, Ariel C. Blanco, Kazuo Nadaoka   +8 more
wiley   +1 more source

Polarimetric SAR Image Classification Based on Ensemble Dual-Branch CNN and Superpixel Algorithm

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Recently, convolutional neural networks (CNNs) have been successfully utilized in polarimetric synthetic aperture radar (PolSAR) image classification and obtained promising results. However, most CNN-based classification methods require a large number of
Wenqiang Hua, Cong Zhang, Wen Xie, Xiaomin Jin   +3 more
doaj   +1 more source

Isotropization of Quaternion-Neural-Network-Based PolSAR Adaptive Land Classification in Poincare-Sphere Parameter Space [PDF]

, 2018
Quaternion neural networks (QNNs) achieve high accuracy in polarimetric synthetic aperture radar classification for various observation data by working in Poincare-sphere-parameter space.
24434, 24435, 24436, 24437, Hirose, Akira, Kinugawa, Kazutaka, Shang, Fang, Usami, Naoto   +7 more
core   +2 more sources

Permafrost Dynamics Observatory: 3. Remote Sensing Big Data for the Active Layer, Soil Moisture, and Greening and Browning

Earth and Space Science, Volume 12, Issue 1, January 2025.
Abstract Because of the remote nature of permafrost, it is difficult to collect data over large geographic regions using ground surveys. Remote sensing enables us to study permafrost at high resolution and over large areas. The Arctic‐Boreal Vulnerability Experiment's Permafrost Dynamics Observatory (PDO) contains data about permafrost subsidence ...
Elizabeth Wig, Kevin Schaefer, Roger Michaelides, Richard Chen, Leah K. Clayton, Brittany Fager, Lingcao Huang, Andrew D. Parsekian, Howard Zebker, Yingtong Zhang, Yuhuan Zhao   +10 more
wiley   +1 more source

Coherency Matrix Decomposition-Based Polarimetric Persistent Scatterer Interferometry [PDF]

, 2019
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new ...
Mallorquí Franquet, Jordi Joan, Zhao, Feng   +1 more
core   +2 more sources

Training Sample Selection Based on SAR Images Quality Evaluation With Multi‐Indicators Fusion

IET Signal Processing, Volume 2025, Issue 1, 2025.
In recent years, with the development of artificial neural networks, efficiently training models for synthetic aperture radar (SAR) image classification tasks has garnered significant attention from researchers. Particularly when dealing with datasets containing a large number of redundant samples, the selection of training samples becomes crucial for ...
Pengcheng Wang, Huanyu Liu, Junbao Li, Hasan Mir   +3 more
wiley   +1 more source