Code release 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). Bug Fix Update v.1.0.1 Fixed error in the legend of Fig. 7b, changing abbreviation "s/c" to "satellite" for clarity v.1.0.2 Removed unnecessary cache from the repository for a cleaner file structure All results and conclusions from the manuscript remain valid What's Included InSAR Persistent Scatterer density prediction with previously published ML model Bridge risk assessment algorithms with geo-hazard analysis Geospatial processing workflows for global-scale infrastructure monitoring Data visualisation and plotting scripts for manuscript figures Key Features Machine learning-based PS availability prediction for 7 continental regions Risk calculation framework incorporating landslide and subsidence hazards Sentinel-1 satellite data availability analysis Automated bridge segmentation and zonal statistics extraction Requirements Python environment (Poetry-managed dependencies) AWS CLI and osmconvert tools Access to companion dataset: 10.5281/zenodo.15797029 Citation If you use this code, please cite the associated paper and dataset when published. This release corresponds to the code version used to generate results in the submitted manuscript.