Results 51 to 60 of about 9,039 (172)

Polar‐low track prediction using machine‐learning methods

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Machine‐learning models are developed to produce reliable and efficient forecasts of polar‐low (PL) trajectories 12 hours ahead. A temporal model (RLSTM) benefiting from the rolling‐forecast strategy, improves overall prediction accuracy and is suitable for quick experimentation, while a spatiotemporal model (PL‐UNet), incorporating both historical and
Ziying Yang, Rune Grand Graversen, Filippo Maria Bianchi, Jiping Liu, Ruibo Lei   +4 more
wiley   +1 more source

Dual Polarimetric Radar Vegetation Index for monitoring forest moisture stress using time series of Sentinel‐1 SAR data

Plant Biology, EarlyView.
This study demonstrates the potential of the Sentinel‐1 Dual Polarimetric Radar Vegetation Index, combined with climate variables and the Standardized Precipitation–Evapotranspiration Index, to effectively detect and monitor drought‐induced stress in temperate broadleaf deciduous forests.
B. Ranjit, W. Bijker, H. Aghababaei, A. Stein   +3 more
wiley   +1 more source

Parameter selection in sparsity-driven SAR imaging [PDF]

, 2009
We consider a recently developed sparsity-driven synthetic aperture radar (SAR) imaging approach which can produce superresolution, feature-enhanced images.
Batu, Ozge, Batu, Özge, Cetin, Mujdat, Çetin, Müjdat   +3 more
core   +2 more sources

Terrestrial Analogs to Titan for Geophysical Research

Reviews of Geophysics, Volume 64, Issue 2, June 2026.
Abstract Saturn's moon Titan exhibits remarkable parallels to the Earth in many geophysical and geological processes not found elsewhere in the solar system at the present day. These include a nitrogen atmosphere with a condensible gas—methane—replacing the Earth's water, leading to an active meteorology with rainfall and surface manifestations ...
Conor A. Nixon, Samuel Birch, Audrey Chatain, Charles Cockell, Kendra K. Farnsworth, Peter M. Higgins, Stéphane Le Mouélic, Rosaly M. C. Lopes, Michael J. Malaska, Mohit Melwani Daswani, Kelly E. Miller, Catherine D. Neish, Olaf G. Podlaha, Jani Radebaugh, Lauren R. Schurmeier, Ashley Schoenfeld, Krista M. Soderlund, Anezina Solomonidou, Christophe Sotin, Nicholas A. Teanby, Tetsuya Tokano, Steven D. Vance   +21 more
wiley   +1 more source

Joint Sparsity for TomoSAR Imaging in Urban Areas Using Building POI and TerraSAR-X Staring Spotlight Data

Sensors, 2021
Synthetic aperture radar (SAR) tomography (TomoSAR) can obtain 3D imaging models of observed urban areas and can also discriminate different scatters in an azimuth–range pixel unit.
Lei Pang, Yanfeng Gai, Tian Zhang
doaj   +1 more source

Sparse representation-based SAR imaging [PDF]

, 2009
There is increasing interest in using synthetic aperture radar (SAR) images in automated target recognition and decision-making tasks. The success of such tasks depends on how well the reconstructed SAR images exhibit certain features of the underlying ...
Cetin, Mujdat, Masnadi-Shirazi, Mohammad Ali, Samadi, Sadegh, Çetin, Müjdat   +3 more
core   +1 more source

Assessing Structure Collapse and Vegetation Loss After the 2025 Eaton Fire Using Optical Remote Sensing

Earth and Space Science, Volume 13, Issue 4, April 2026.
Abstract On 7–8 January, 2025, the Eaton fire destroyed >9,000 structures and >40 km2 of forest in the northeastern region of the Los Angeles metropolitan area, California. Building damage was primarily assessed through ground investigations, a process that took several weeks due to hazardous conditions and the difficulty of accessing burnt areas. This
Solene L. Antoine
wiley   +1 more source

Deep learning in remote sensing: a review [PDF]

, 2017
Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich, Mou, Lichao, Tuia, Devis, Xia, Gui-Song, Xu, Feng, Zhang, Liangpei, Zhu, Xiao Xiang   +6 more
core   +4 more sources

Intelligent Shanghai Typhoon Model (ISTM): A Diffusion‐Based Downscaling Emulator From AIFS to Kilometer‐Scale Regional Reanalysis for Typhoon Forecasts

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Artificial‐intelligence weather prediction models have recently surpassed numerical models in large‐scale skill, but they still systematically underestimate typhoon intensity due to their reliance on coarse‐resolution training data from ERA5. To overcome this limitation, we constructed a bespoke 9‐km high‐resolution typhoon reanalysis (HiRes ...
Zeyi Niu, Wei Huang, Sirong Huang, Bo Qin, Mengqi Yang, Haofei Sun, Zhaoyang Huo, Haixia Xiao, Kairui Feng   +8 more
wiley   +1 more source

An innovative semantically guided SAR imaging and target enhancement method

Electronics Letters
Conventional sparse synthetic aperture radar (SAR) imaging methods apply regularisation to constrain scene priors. However, these methods often neglect specific target regions, resulting in undifferentiated imaging. This letter introduces a novel network
Guoru Zhou, Zhe Zhang, Bingchen Zhang, Yirong Wu   +3 more
doaj   +1 more source