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Quantitative investigation of major fault zones with low slip rates and long recurrence intervals in densely populated regions is essential for understanding earthquake recurrence and assessing seismic hazard. The Tanlu Fault Zone, a major lithospher...

Currently, the PPP-B2b service faces challenges such as long convergence times and re-convergence issues after signal interruptions due to the lack of high-precision atmospheric enhancement. To address this, this study develops a multi-frequency unco...

As carbon cycling and global environmental protection gain increasing attention, forest disturbance research has intensified worldwide. Constrained by limited data availability, existing frameworks often rely on extracting individual spectral bands f...

In practical Synthetic Aperture Radar (SAR) applications, new-class objects can appear at any time as the rapid accumulation of large-scale and high-quantity SAR imagery and are usually supported by limited instances in most cooperative scenarios. He...

Atmospheric motion vector (AMV) products from EUMETSAT’s MetOp satellite series, including MetOp-B, MetOp-C, and the MetOp-B/C tandem (MetOp-Dual), have been assimilated at many numerical weather prediction centers worldwide. However, they have...

High-resolution air temperature (AT) data is essential for understanding urban heat dynamics, particularly in urban areas characterised by complex microclimates. However, AT is rarely available in such detail, emphasising the need for its modelling....

Henan Province, characterized by hills and mountains in its western, northern, and southern regions, is a high-risk area for geohazards in China. In this paper, we are the first to investigate the geohazards over Henan using the basic deformation pro...

In recent years, ecosystems in Saudi Arabia have experienced severe degradation due to factors such as hyperaridity, overgrazing, climate change, urban expansion, and an increase in uncontrolled wildfires. Among these, wildfires have emerged as the s...

Multispectral LiDAR point clouds, which integrate both geometric and spectral information, offer rich semantic content for scene understanding. However, due to data scarcity and distributional discrepancies, existing methods often struggle to balance...

Landslide deformation monitoring via InSAR is crucial for assessing the risk of hazards. Quick and accurate detection of active deformation zones is crucial for early warning and mitigation planning. While the application of deep learning has substan...