Results 61 to 70 of about 840 (174)
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 +5 more
wiley +1 more source
An optimised scattering power decomposition model is proposed which comprises surface, double‐bounce, oriented dipole and volume scattering components. The authors derive the optimised four‐component decomposition model from mathematical and theoretical perspectives, and verify the rationality of the optimised decomposition model using large amounts of
Lu Fang, Wenxing Mu, Ning Wang, Tao Liu
wiley +1 more source
Heterogeneous Network-Based Contrastive Learning Method for PolSAR Land Cover Classification
Polarimetric synthetic aperture radar (PolSAR) image interpretation is widely used in various fields. Recently, deep learning has made significant progress in PolSAR image classification. Supervised learning (SL) requires a large amount of labeled PolSAR
Jianfeng Cai +4 more
doaj +1 more source
On ICA Based ICTD Classification of Polsar Data [PDF]
The Independent Component Analysis (ICA) has been recently introduced as a reliable alternative to identify canonical scattering mechanisms within PolSAR images. This paper addresses an important aspect for applying such methods on real data, namely statistical classification with ICA.
openaire +2 more sources
SAR GMTI is of great importance for both civlisation and military applications. The clutter suppression performance is an important assurance for the accuracy and precision of GMTI. To achieve better clutter suppression performance, it often requires extremely precise registration of multi‐channel data, including polarization and interferometric ...
Jing Xu +3 more
wiley +1 more source
Multiobjective Evolutionary Superpixel Segmentation for PolSAR Image Classification
Superpixel segmentation has been widely used in the field of computer vision. The generations of PolSAR superpixels have also been widely studied for their feasibility and high efficiency.
Boce Chu +7 more
doaj +1 more source
The authors propose a novel waveform, namely, the orthogonal double V‐linear frequency modulation (ODV‐LFM) and corresponding simultaneous polarimetric measurement and pointwise linear and non‐linear processing methods. The proposed waveform can mitigate the influence of delay‐Doppler coupling and reduce the risk of false targets and ghosts in multiple‐
Biao Shen +3 more
wiley +1 more source
Artificial Intelligence applications in Noise Radar Technology
Abstract Radar systems are a topic of great interest, especially due to their extensive range of applications and ability to operate in all weather conditions. Modern radars have high requirements such as its resolution, accuracy and robustness, depending on the application.
Afonso L. Sénica +2 more
wiley +1 more source
The manuscript mainly investigates the sparse distributed vegetation height inversion problem. By analysing the scattering mechanisms of the sparse distributed vegetation, the authors proposed a method to select the samples to estimate PolInSAR coherence and vegetation height in non‐local areas by using the amplitude‐normalised interferometric phase ...
Jing Xu +3 more
wiley +1 more source
Abstract Many communities coexist with wildfires that lead to loss of lives, property, and ecosystem services. Remote sensing tools can aid disaster response and post‐event assessment, offering fire agencies opportunities for additional surveillance with radar, an all‐weather instrument that can image day or night.
Karen An, Cathleen E. Jones, Yunling Lou
wiley +1 more source

