Global Geo-hazard Risk Assessment of Long-Span Bridges Enhanced with InSAR Availability - research data

Global Geo-hazard Risk Assessment of Long-Span Bridges Enhanced with InSAR Availability - Research Data Description This dataset contains processed geospatial data, risk assessment results, and visualisation materials supporting the research paper "Global geo-hazard risk assessment of long-span bridges enhanced with InSAR availability", published in Nature Communications, DOI: 10.1038/s41467-025-64260-x. Contents Hazard Data (hazard/): Normalised geotiff rasters for landslide susceptibility and ground subsidence hazards. The hazard data was originally published by Herrera-García, G. et al, while the landslide dataset was created by Redshaw, P. & Bottomley, J.. This dataset only contains normalised versions of the aforementioned datasets. Herrera-García, G. et al. Mapping the global threat of land subsidence. Science 371, 34–36 (2021). DOI: 10.1126/science.abb8549 Redshaw, P. & Bottomley, J. The Global Landslide Hazard Map: Final Project Report. Tech. Rep., The World Bank (2020). Persistent Scatterer Predictions (predicted_PS/): Machine learning-generated MT-InSAR PS availability predictions by continent (7 continental regions). Generated using methodology proposed by Malinowska, D., Milillo, P., Briggs, K., Reale, C., and Giardina, G. Malinowska, D., Milillo, P., Briggs, K., Reale, C. & Giardina, G. Coherence-based Prediction of Multi-Temporal InSAR Measurement Availability for Infrastructure Monitoring. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 1–22 (2024). DOI: 10.1109/JSTARS.2024.3449688 Risk Assessment Results (risk_assessment/): Bridge risk analysis outputs with multiple monitoring factor thresholds (1.15-1.55), provided in both CSV and pickle formats Satellite Data Availability (snt_availability/): Sentinel-1 coverage shapefiles for current conditions and pre-failure scenarios. Those were derived using Sentinel acquisition plans Visualisation Data (plots/): Source data (CSV) for all manuscript figures and supplementary materials Generated plot images (JPG format) World administrative boundaries for mapping Data Formats Raster data: GeoTIFF (.tif) Vector data: ESRI Shapefiles (.shp, .dbf, .prj, .shx) Tabular data: CSV and Python pickle (.pkl) files Images: JPEG (.jpg) Usage Data can be processed using the companion code repository. Risk assessment results are ready for analysis, while source data enables reproduction of all manuscript figures. Geospatial data requires GIS software or Python packages (rasterio, geopandas) for processing. Related Publication Dataset supports: "Global geo-hazard risk assessment of long-span bridges enhanced with InSAR availability", published in Nature Communications, DOI: 10.1038/s41467-025-64260-x. Code repository: bridge-risk-assessment-insar; archived on Zenodo: 10.5281/zenodo.15831783