Results 51 to 60 of about 3,590 (264)
Remote SensingSupervised polarimetric synthetic aperture radar (PolSAR) image classification demands a large amount of precisely labeled data. However, such data are difficult to obtain.
Lei Wang +4 more
doaj +1 more source
Bias Correction and Modified Profile Likelihood under the Wishart Complex Distribution
, 2014 This paper proposes improved methods for the maximum likelihood (ML) estimation of the equivalent number of looks $L$. This parameter has a meaningful interpretation in the context of polarimetric synthetic aperture radar (PolSAR) images.
Cintra, Renato J. +2 more
core +1 more source
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 +8 more
wiley +1 more source
Semi-supervised PolSAR Image Change Detection using Similarity Matching [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information SciencesThe lack of precisely labeled data limits the development of supervised polarimetric synthetic aperture radar (PolSAR) image change detection. Therefore, semi-supervised deep learning methods have recently demonstrated their significant capability for ...
L. Wang +5 more
doaj +1 more source
Offshore Metallic Platforms Observation Using Dual-Polarimetric TS-X/TD-X Satellite Imagery: A Case Study in the Gulf of Mexico [PDF]
, 2017 Satellite-based synthetic aperture radar (SAR) has been proven to be an effective tool for ship monitoring. Offshore platforms monitoring is a key topic for both safety and security of the maritime domain.
Marino, Armando +2 more
core +3 more sources
Polarimetric Convolutional Network for PolSAR Image Classification [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2019 15 ...
Xu Liu +4 more
openaire +2 more sources
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 +10 more
wiley +1 more source
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 +3 more
wiley +1 more source
A Non-Parametric Texture Descriptor for Polarimetric SAR Data with Applications to Supervised Classification [PDF]
, 2014 The paper describes a novel representation of polarimetric SAR (PolSAR) data that is inherently non-parametric and therefore particularly suited for characterising data in which the commonly adopted hypothesis of Gaussian backscatter is not ...
Jäger, Marc, Reigber, Andreas
core
Consistency Regularization Semisupervised Learning for PolSAR Image Classification
International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.Polarimetric Synthetic Aperture Radar (PolSAR) images have emerged as an important data source for land cover classification research due to their all‐weather, all‐day monitoring capabilities. Deep learning‐based classification methods have recently gained significant attention in PolSAR image classification since they have demonstrated excellent ...
Yu Wang +3 more
wiley +1 more source