A JavaScript code developed in Google Earth Engine (GEE) Platform to Detect Flooded Area along with Affected Population

This GitHub repository contains the machine learning models described in Edoardo Nemnni, Joseph Bullock, Samir Belabbes, Lars Bromley Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery.

The official repo for ISPRS JP&RS 2024 "DAM-Net: Flood detection from SAR imagery using differential attention metric-based vision transformers"

This repository contains a Jupyter Notebook for automatic flood extent mapping using space-based information.

Analyzing NYC's Stormwater Flood Map - Extreme Flood Scenario

Seamless Flood Mapping Using Harmonized Landsat and Sentinel-2 Data

A Collection of Flood Hazard Layers for New York City.

A Collection of NASA ARSET Courses for Flood Mapping and Synthetic Aperture Radar (SAR)

This repository includes an automatic statistical-based flood mapping approach for ALOS2 Level 2.1 data. Additionally, this method of flood extraction utilizes Google Earth Engine's open data and processing capabilities.

In this repository, I share a class project in which I explored the Google Earth engine sentinel 1 SAR dataset potential to be used for flood mapping of the 2019 Gorgan flood.

Georgia Tech CS 7643 (Deep Learning) Final Project: Flood Mapping Semantic Segmentation using a U-Net Model with Feature Representations of Sentinel-1 and Sentinel-2 Data

Improving Seamless Flood Mapping with Cloudy Satellite Imagery via Water Occurrence and Terrain Data Fusion

Sentinel-1 SAR flood-frequency and LiCSBAS InSAR subsidence mapping for the Semarang–Demak coast (2020–2025), fused into a per-kelurahan coastal-flood vulnerability typology. SDG 11.5 / 13.1.

Intelligent Data Solution - Disaster Risk Reduction is a system to assist flood management in the state of Assam through data-driven ways. The repository contains codes to extract relevant datasets and the modelling approach used to calculate Risk Scores for each revenue circle in Assam.

Deep learning-based flood area segmentation using U-Net with ResNet50 encoder on satellite imagery.

Interactive flood-risk map for Delhi from satellite data — the July 2023 Yamuna flood, risk zones, roads & people at risk

SAR-based flood mapping workflow for the 2017 Coastal El Niño flood event in northern Peru using Sentinel-1 and Google Earth Engine.

Rapid flood extent mapping & exposure assessment using SAR & machine learning in Küçük Menderes Basin, Türkiye (Natural Hazards, 2026)

A remote-sensing based application using Google Earth Engine for flood mapping and impact assessment.

Google Earth Engine scripts and notes for remote sensing, NDVI, flood extent, and rainfall trend analysis.