A Collection of Flood Hazard Layers for New York City.
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Updated
Nov 21, 2023 - Jupyter Notebook
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
Mangrove Flood Risk Assessment 🌳🌊
NASA ACRES fellowship project mapping wildfire and flood risk in Kula and South Maui using satellite remote sensing.
Exploring the Building Elevation and Subgrade (BES) Dataset for New York City in Python
Capa de confianza calibrada (ECE/conformal/UQ) para pronósticos de inundación de modelos hidrológicos OSS — para municipios y protección civil
Flood susceptibility mapping workflow using geospatial data engineering and a decision making algorithm to identify and visualize flood-prone areas.
Agent-based model of spatial flood-defence cooperation: threshold public-goods game with environmental feedback, three strategies (UC/CC/D), and resilience-erosion dynamics on a lattice.
Interactive flood-risk simulation for urban Chennai — terrain-based drainage analysis with a real-time "what-if" rainfall scenario engine. DEM pipeline → simplified hydraulic proxy (HEC-RAS upgrade planned) → live web dashboard.
Ready-to-use MCP extensions for Gemini CLI and Claude Desktop - neighborhood intelligence, school ratings, flood risk, air quality, and more.
Malaysia-focused flood risk prediction and explainability research project using FastAPI, Streamlit, geospatial data, and machine learning.
Geospatial foundation model for flood susceptibility mapping
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)
Flood Prediction is a Databricks Solution Accelerator for spatial ML: public elevation, water, climate, and historical flood data → H3 features → scenario-trained models → an interactive underwriting map. Built for Public Sector and P&C Insurance demos. Retarget any city by changing a few bundle variables.
A plain-language flood risk lookup tool for Philadelphia residents
Flood-retention investment MVP that ranks where extra capacity can reduce downstream risk first.
Enterprise-grade Streamlit platform that turns inspection reports, photos, audio & floorplans into provenance-tracked repair cost estimates across 21 modules - cost, CapEx, permits, environmental risk, insurance, recalls, ROI & more. Real government data, deterministic calculations.
Repo for Oluwatobi's geospatial data analytics projects, blog posts and podcast
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