Nepal Flash Flood: Damage Assessment using Sentinel-1 Radar

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Nepal

About this dataset

This dataset provides a rapid damage screening assessment for the 26 August 2026 Nepal flash flood and debris-flow event using 10-m Sentinel-1 Synthetic Aperture Radar (SAR) data. A post-event radar acquisition acquired on 28 August 2026 was compared with a one-year pre-event Sentinel-1 baseline to identify unusually strong changes in radar backscatter. The resulting damage proxy was spatially averaged using a 50 m neighbourhood and restricted to a built-environment search domain (residential and non-residential) defined from pre-event Overture building footprints and a 30 m surrounding buffer. A conservative operational threshold (K50 absolute z-score ≥ 1.60) was used to identify high-confidence likely-damage/change areas. The resulting layer was visually reviewed at post-processing level to remove identified artefacts. Across the assessed area, approximately 245.13 ha of high-confidence change were identified within approximately 4755 ha of assessed built-environment domain across 58,557 ha of assessed AOI. Admin-3 summary statistics are provided for 16 municipalities intersecting the analysis area. The product is a likely-damage / unusual-change proxy and not proof of structural or building-level damage. It is intended to support rapid geographic prioritisation, complementary imagery review and field assessment.

Documentation

General methodology Sentinel-1 IW VV/VH radar backscatter amplitude observations covering the analysis area from 26 August 2025 to 26 August 2026 were used to establish the pre-event baseline. The 28 August 2026 post-event Sentinel-1 acquisition was pre-processed consistently and standardized against the baseline using z-score anomaly. The maximum absolute VV/VH z-score was spatially averaged with a normalized 50 m circular kernel (K50). Results were restricted to areas within 30 m of pre-event Overture building footprints. A K50 absolute z-score threshold of greater or equal to 1.60 defines the operational high-confidence screening layer. Post-processing The thresholded screening layer was visually reviewed and manually edited to remove identified artefacts before publication. Validation The underlying K50 ≥1.60 operational threshold was evaluated against spatially held-out Copernicus Emergency Management Service (CEMS EMSR927) building-grading observations across AOI01, AOI02 and AOI03. It detected 53.1% of CEMS Damaged/Destroyed observations (recall; F1 = 69.4%), while 0 (zero) of 92 CEMS Possibly Damaged observations in the held-out comparison sample exceeded the threshold. As “Possibly damaged” is not a verified undamaged class, the resulting nominal precision and specificity should not be interpreted as conventional wall-to-wall damage-versus-undamaged accuracy. These validation statistics apply to the underlying automated threshold; the published polygon was subsequently visually reviewed and edited. Our Sentinel-1-based method measures changes in radar backscatter rather than direct structural damage. Strong signals may reflect damaged or removed structures, debris and sediment deposition, inundation, changes in surface moisture or roughness, vegetation disturbance, clearance activities, or other event- and non-event-related changes. Conversely, damaged structures may produce little detectable radar change. Terrain and viewing geometry are additional limitations in the assessed steep Himalayan environment. These two latter limitations are prevalent here because we have not applied a dedicated pre-processing (e.g., Radiometric Terrain Flattening). Absence of a detected signal therefore does not imply absence of damage. The 30-m Overture building-proximity domain is an analysis/search domain and does not represent actual building footprint or floor area. Individual screening polygons should not be interpreted as individually confirmed damaged buildings.

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