Multi-temporal radar remote sensing for rapid assessment of earthquake-induced infrastructure damage: A comparative study of the 2024 Noto and 2019 Mianeh earthquakes

Analysis Of Surface Deformation Due To The Manay Earthquake, Philippines, Using The Interferometric Synthetic Aperture Radar (InSAR) Method Based On Sentinel-1c Data

The Philippines is one of the most tectonically active regions in the world, situated at the convergence of several major and minor plates, including the Philippine Sea Plate, the Sunda Plate, and the Eurasian Plate. This complex tectonic setting makes the archipelago highly susceptible to frequent and often destructive earthquakes, which can trigger significant deformation of the ground surface, infrastructure damage, and secondary hazards such as landslides and liquefaction. One notable seismic event occurred in the Manay region, Mindanao, Philippines, generating measurable surface displacement that requires accurate spatial assessment for effective disaster response and mitigation planning. However, ground-based monitoring alone is often insufficient to capture the spatial extent and pattern of coseismic deformation, particularly in remote or rapidly affected areas. This study addresses this gap by employing the Interferometric Synthetic Aperture Radar (InSAR) technique to analyze surface deformation associated with the Manay earthquake, utilizing Sentinel-1C Single Look Complex (SLC) imagery. Pre-event and post-event SAR acquisitions were processed to generate interferograms, phase decomposition, and line-of-sight surface displacement maps. The InSAR approach enables wide-area deformation monitoring with high spatial resolution and centimeter-level accuracy, offering advantages over conventional in-situ measurement techniques. The resulting deformation maps reveal the spatial distribution and magnitude of ground displacement induced by the earthquake. These findings are expected to enhance the understanding of coseismic surface behavior in tectonically active regions and to serve as a valuable reference for future disaster risk assessment, seismic hazard mapping, and mitigation strategies in the Philippines and similar geodynamic settings.

Near-Real-Time Flood Disaster Monitoring Based on Moonlight and Multi-Source Remote Sensing: A Case Study of Zhengzhou Rainstorm

The increasing frequency of natural disasters such as floods has led to severe casualties and substantial economic losses. Consequently, near-real-time flood disaster monitoring has become critical for effective disaster response and accurate damage assessment. However, traditional approaches relying on daytime optical imagery and SAR data often suffer from long satellite revisit cycles and data acquisition latency, while nighttime Earth observation remains limited by the absence of adequate illumination. This study proposes an innovative framework that integrates moonlight Earth observation to enable near-real-time flood monitoring and loss assessment and is applied to the 7.20 Zhengzhou rainstorm event. Compared to conventional disaster monitoring techniques, integrating moonlight observations shortens the effective data acquisition period to approximately one day, significantly improving temporal responsiveness compared with conventional techniques. The innovative framework identifies a flood-affected area of 722.93 km2 and estimated economic losses of 107.96 billion yuan in the disaster-affected region. The results indicate that the moonlight data source has significant capacity for near-real-time disaster monitoring and disaster loss assessment and highlight the potential broad impact of this study in relevant fields.

Rapid Post-earthquake Damage Detection Using UAV Imagery and YOLO: A Case Study from the Kahramanmaras Earthquake

Open-Source Sentinel-1 SBAS InSAR Monitoring of Ground Deformation in Pantnagar (Indian Terai) Using HyP3 and MintPy

Aims: The study aims to measure ground-surface displacement and assess land subsidence along the under-monitored Terai belt of the Himalayan foothills using an open-source remote-sensing workflow. Study Design: Observational time-series analysis utilising satellite radar interferometry to monitor surface deformation. Place and Duration of Study: Pantnagar region, Udham Singh Nagar district, Uttarakhand, with acquisitions covering 8 January 2023 to 21 June 2026. Methodology: Sentinel-1 interferograms were generated via the Alaska Satellite Facility’s HyP3 service and analysed using MintPy with the Small Baseline Subset (SBAS) method across 88 acquisitions. Following network inversion and digital elevation model error correction, pixels were masked at a temporal coherence threshold of 0.7, retaining 80.8% of the ~40 m grid. Results were evaluated against Dynamic World land-cover data, rainfall, and modelled groundwater storage. Results: Most of the scene remained stable, showing a median line-of-sight velocity of −0.4 cm yr−1 (interquartile range: −1.2 to 0.0 cm yr−1; 1σ uncertainty: 0.06 cm yr−1). A distinct, linear subsiding zone in the south-west reached ~−6.1 cm yr−1, representing roughly 21 cm of cumulative line-of-sight displacement over 3.45 years. This deformation persisted over cropped farmland and showed no seasonal rebound during monsoons. Conclusion: The persistent, non-rebounding subsidence points to inelastic aquifer-system compaction driven by sustained irrigation pumping. Although the rates remain provisional because nearby ground-station verification is unavailable, this methodology provides a reproducible template for regional Terai subsidence monitoring.

Detection and analysis of cyclonic events through satellite-based remote sensing techniques for coastal areas of Pakistan

This study reviews the unusual lifecycle and reach of Cyclone Asna (August–September 2024) over the North Arabian Sea with special focus on its inland re-intensification after landfall, a behavior not typically seen in that region. Remote sensing satellite platforms combined with geographic information systems (GIS) allow a multi-parameter assessment of Asna's track, rain patterns, flood extents, and resulting damage across Pakistan's coastal belt and deeper inland areas. Sentinel's 2 NDWI images map surface water changes before and after the storm, while integrated IMERG rainfall estimates and time-stamped damage reports identify high-risk areas and illuminate the cyclone's social and economic costs. Karachi and adjacent coastal towns recorded isolated totals above 266 mm, sparking extensive urban floods, power outages, and collapse of key transport links, all driven by Asna's slow forward motion and prolonged onshore presence. Asna's inland intensification was caused by a rare overlap of monsoon moisture feeding in from both the Arabian Sea and Bay of Bengal, upper-level divergence, saturated soils, high surface heat flux, and persistent mid- to upper-level cyclonic vorticity factors that together sustained the storm's vertical structure far beyond normal landfall limits. Broadly speaking, both the warmer Arabian Sea and its greater moisture-holding capacity are driving a recent increase in hybrid cyclone systems across the region. This study confirms that trend and points to satellite monitoring as an invaluable tool for bettering disaster preparedness and adaptive planning. As the case of cyclone Asna shows, predictive models and urban resilience plans must now be revised to reflect unusual cyclone behavior strengthened by evolving climate dynamics.

GF-2/sentinel-2 fusion for active fault detection: a case study of the yilan-yitong fault (liaoning segment)

The Yilan-Yitong Fault Zone, a core part of the northern Tanlu Fault Zone, is a key seismogenic structure in Northeast Asia. Its Liaoning segment suffers from unclear surface distribution, insufficient late Quaternary activity evidence and lack of refined research based on optimized multi-source remote sensing data, which restricts regional seismic hazard assessment and major engineering safety layout. This study aimed to conduct fine detection and activity evaluation of this fault segment using high-resolution satellite data. We took GF-2 panchromatic and Sentinel-2 multispectral images as core data, compared four fusion algorithms (PCA, GS, HSV, Brovey) via qualitative and quantitative evaluation, and combined UAV remote sensing, field surveys of 28 key observation points and large-scale trench (25 m × 8 m) verification in Kaiyuan for systematic analysis. Results showed the PCA algorithm had the optimal comprehensive performance, suitable for fine geological interpretation. The fault was divided into three subsegments, with the Tieling-Kaiyuan segment showing distinct linear geomorphology and strong late Quaternary activity. The trench provides evidence suggestive of Holocene activity, and flower structures plus multi-phase faulting events reflected multistage activity characteristics, with preliminary identification of paleoseismic relics. This study verifies the application potential of domestic high-resolution satellites, fills the gap in refined activity research of the fault’s Liaoning segment, and provides high-precision scientific support for Liaoning’s seismic hazard assessment and major engineering safety layout.