A Collection of Flood Hazard Layers for New York City.

Turn Japan's PLATEAU 3D city models into a queryable, hazard-aware buildings.parquet. Pre-built bundles for 29 cities; SQL via DuckDB; 3D Tiles + PMTiles + FlatGeobuf out of the box.

A presentation on leveraging Jupyter Notebooks for automating large scale flood risk studies

Flood risk prediction using machine learning and SHAP explainability

NASA ACRES fellowship project mapping wildfire and flood risk in Kula and South Maui using satellite remote sensing.

Mangrove Flood Risk Assessment 🌳🌊

Exploring the Building Elevation and Subgrade (BES) Dataset for New York City in Python

Municipality-Scale Flood Risk Mapping across Colombia — 7 departments (Antioquia, Bolívar, Cauca, Chocó, Guajira, Magdalena, Nariño) — Sentinel-1 SAR + RF/XGBoost/LightGBM ensemble + JRC water + WorldPop — GEE (2015–2025)

End-to-end spatial ML pipeline predicting flood vulnerability at the census tract level using FEMA flood zones, OSM waterways, and Census demographics — Harris County, TX.

Flood-retention investment MVP that ranks where extra capacity can reduce downstream risk first.

[PJDSC 2025] Explainable, street-level flood-risk mapping for Philippine cities.

Dependence-aware block-maxima inference for severity, persistence, and design-life levels.

Flood score integration for parcel-level flood risk assessment.

Experiments with LiDAR, IMU and machine learning for water level measurement.

Free tool to download EA surface water flood risk data as shapefiles for any UK postcode input

Ready-to-use MCP extensions for Gemini CLI and Claude Desktop - neighborhood intelligence, school ratings, flood risk, air quality, and more.

Citation-grounded NYC flood-exposure briefings: multi-agent civic AI on Granite 4.1 + Prithvi-EO + TerraMind, every claim cited to a public-record source.

AI-driven flood risk intelligence platform for Bihar — XGBoost breach prediction, real-time GIS monitoring, 7-day forecast simulation and resilience scoring

Municipality-Scale Flood Risk Mapping in Magdalena (30 municipios), Colombia — Sentinel-1 SAR + Ensemble ML + JRC water + CHIRPS climate + WorldPop exposure — GEE + Python (2015–2025)

GIS analysis of flood risk impact on road infrastructure in Lagos using OpenStreetMap and spatial modelling.