Results 51 to 60 of about 505 (177)

PolSAR Image Classification by Introducing POA and HA Variances

Remote Sensing, 2023
A polarimetric synthetic aperture radar (PolSAR) has great potential in ground target classification. However, current methods experience difficulties in separating forests and buildings, especially oriented buildings. To address this issue, inspired by the three-component decomposition method, multiple new scattering models were proposed to describe ...
Zeying Lan, Yang Liu, Jianhua He, Xin Hu
openaire   +2 more sources

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

Investigation of the capability of multitemporal RADARSAT-2 fully polarimetric SAR images for land cover classification: a case of Panyu, Guangdong province

European Journal of Remote Sensing, 2021
Synthetic aperture radar (SAR), with all-day and all-weather observation capabilities, can capture the phenology of crops with short growth cycles to improve land cover classification results.
Di Liu, Zhixin Qi, Hui Zhang, Xia Li, Anthony Gar-on Yeh, Jiao Wang   +5 more
doaj   +1 more source

Dual-Branch Fusion of Convolutional Neural Network and Graph Convolutional Network for PolSAR Image Classification

Remote Sensing, 2022
Polarimetric synthetic aperture radar (PolSAR) images contain useful information, which can lead to extensive land cover interpretation and a variety of output products.
Ali Radman, Masoud Mahdianpari, Brian Brisco, Bahram Salehi, Fariba Mohammadimanesh   +4 more
doaj   +1 more source

PolSAR Image Classification Based on Relation Network with SWANet

Remote Sensing, 2023
Deep learning and convolutional neural networks (CNN) have been widely applied in polarimetric synthetic aperture radar (PolSAR) image classification, and satisfactory results have been obtained. However, there is one crucial issue that still has not been solved. These methods require abundant labeled samples and obtaining the labeled samples of PolSAR
Wenqiang Hua, Yurong Zhang, Cong Zhang, Xiaomin Jin   +3 more
openaire   +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

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

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

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, Shan Jiang, Weijie Li, Mohamadreza (Mohammad) Khosravi   +3 more
wiley   +1 more source