Results 51 to 60 of about 11,244,032 (159)

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

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

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

PolSAR Image Classification Based on Statistical Distribution and MRF

, 2020
Classification is an important topic in synthetic aperture radar (SAR) image processing and interpretation. Because of speckle and imaging geometrical distortions, land cover mapping is always a challenging task especially in complex landscapes.
Xiyun Liu, Junjun Yin, Jian Yang, Chih-Yuan Chu, Yang-Lang Chang   +4 more
core   +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

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

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

Machine learning classification based on k-Nearest Neighbors for PolSAR data

Anais da Academia Brasileira de Ciências
In this work, we focus on obtaining insights of the performances of some well-known machine learning image classification techniques (k-NN, Support Vector Machine, randomized decision tree and one based on stochastic distances) for PolSAR (Polarimetric ...
JODAVID A. FERREIRA, ANNY K.G. RODRIGUES, RAYDONAL OSPINA, LUIS GOMEZ   +3 more
doaj   +1 more source

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

A Hierarchical Fully Convolutional Network Integrated with Sparse and Low-Rank Subspace Representations for PolSAR Imagery Classification

Remote Sensing, 2018
Inspired by enormous success of fully convolutional network (FCN) in semantic segmentation, as well as the similarity between semantic segmentation and pixel-by-pixel polarimetric synthetic aperture radar (PolSAR) image classification, exploring how to ...
Yan Wang, Chu He, Xinlong Liu, Mingsheng Liao   +3 more
doaj   +1 more source