Results 41 to 50 of about 505 (177)

Interlinked Dynamics of Rice Cultivation Intensity and Ground Subsidence: Spatio‐Temporal Insights Into Water Resource Implications From Multi‐Year Spaceborne SAR Analysis

Water Resources Research, Volume 62, Issue 4, April 2026.
Abstract Sustainable rice cultivation is vital to meet global food demands, particularly in regions relying on groundwater for irrigation. Over‐pumping, however, can cause significant ground subsidence, threatening both infrastructure and agricultural sustainability.
Ya‐Lun S. Tsai, Xun‐Yan Liu
wiley   +1 more source

PolSF: PolSAR image dataset on San Francisco

CoRR, 2019
Polarimetric SAR data has the characteristics of all-weather, all-time and so on, which is widely used in many fields. However, the data of annotation is relatively small, which is not conducive to our research. In this paper, we have collected five open polarimetric SAR images, which are images of the San Francisco area.
Xu Liu 0006, Licheng Jiao, Fang Liu 0001
openaire   +3 more sources

A Box Gradient‐Based Anisotropic Diffusion Framework for Polarimetric SAR Despeckling

Electronics Letters, Volume 62, Issue 1, January/December 2026.
This paper proposes a novel anisotropic diffusion framework for PolSAR despeckling, driven by a newly defined complex‐domain Box gradient. The method adaptively suppresses speckle while preserving structural and point‐target details, and experiments on real AIRSAR data confirm superior performance over existing filters.
Songli Han, Dawei Ren, Jian Yang
wiley   +1 more source

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

Multistatic Frequency and Polarimetry Adaptive Autofocus for Synthetic Aperture Radar Imaging of a Moving Target

IET Radar, Sonar &Navigation, Volume 20, Issue 1, January/December 2026.
This paper presents a multistatic, frequency‐ and polarimetry‐adaptive autofocus algorithm (F‐Pol) for SAR imaging of moving targets undergoing complex, six‐degrees‐of‐freedom (6‐DoF) motion. Building on Localised Threshold Sharpness (LTS), the method exploits agreement across frequency sub‐bands and polarisation channels to improve pulse‐by‐pulse ...
Anmol Rattan, Daniel Andre, Mark Finnis
wiley   +1 more source

Applications of the Mellin Transform in Analyzing Survival Data With the Cubic Transmuted Class

Journal of Probability and Statistics, Volume 2026, Issue 1, 2026.
The development of new models aims to provide probability distributions that can accurately describe unusual phenomena, such as those observed in survival analysis, which often pose challenges due to factors like time dependence and data censoring. Among the diverse classes and models available in the literature, there has been growing interest in ...
Marília Oliveira, Josimar Vasconcelos, Frank Gomes-Silva, Smritijit Sen   +3 more
wiley   +1 more source

CV-CPKAN: Complex-Valued Convolutional Kolmogorov–Arnold Framework for PolSAR Image Classification

Remote Sensing
Deep learning has significantly advanced PolSAR image processing, with a growing trend of integrating mathematical theories into deep neural networks to enhance their capabilities with regard to complex data.
Zuzheng Kuang, Shuxin Liu, Haixia Bi, Lijun He, Fan Li   +4 more
doaj   +1 more source

Prototype Theory Based Feature Representation for PolSAR Images

Leida xuebao, 2016
This study presents a new feature representation approach for Polarimetric Synthetic Aperture Radar (PolSAR) image based on prototype theory. First, multiple prototype sets are generated using prototype theory.
Huang Xiaojing, Yang Xiangli, Huang Pingping, Yang Wen   +3 more
doaj   +1 more source

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

An Unsupervised PolSAR Image Classification Algorithm Based on Tensor Product Graph Diffusion

Leida xuebao, 2019
To overcome the difficulty of similarity expression and the effects of speckle noise in unsupervised classification of Polarimetric Synthetic Aperture Radar (PolSAR) images, a novel unsupervised PolSAR image terrain classification algorithm based on ...
ZOU Huanxin, LI Meilin, MA Qian, SUN Jiachi, CAO Xu, QIN Xianxiang   +5 more
doaj   +1 more source