flood-detection

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

Code Repo for Earth Observation for Disaster Mapping: Benchmarks, Methods, Challenges and Future Perspectives

This is a Semester Project which aim is to implement a Deep Learning model in order to detect Flood Events from Satellite Images

Flood detection from images using deep learning. Deep learning library KERAS was employed and MobileNet architecture was fine-tuned for image classification task.

Advanced Telegram news submission bot with SecurityManager, flood detection, content filtering, photo support, scheduled publishing, and inline moderation. Freelance order, commercial work

Real-time defensive network tool with integrated packet scanner and GUI for detecting flood attacks, ARP spoofing, and DHCP floods, featuring multi-platform firewall support.

Web App for automated change detection in multi temporal satellite images for natural hazard classification.

BILAHUJAN — AI-powered flood detection | V Hack 2026 @ USM

Climate Disaster Warning System is a deep learning-based project for detecting wildfires, floods, and sea-level rise using satellite and ground data. It leverages ResNet, Vision Transformer (ViT), and GRACE datasets to support early warning systems and climate research.

Codebase for MS thesis @ Colorado State University. Processing pipeline and analysis code for measuring flood disaster impacts using MODIS satellite imagery, climate data, and EM-DAT disaster records.

AquaGuard is a native iOS application designed to protect communities during flood disasters. It provides real-time alerts, safety guides, and a crowdsourced reporting system to coordinate rescue efforts effectively.

Multimodal flood segmentation: Gated Fusion Network fusing Sentinel-1 SAR + Sentinel-2 optical via a learned attention gate. 0.74 mIoU overall, 0.61 under heavy cloud cover.

Deployment and explainability analysis of NASA-IBM's Prithvi-EO-2.0 for flood segmentation, evaluated on Sen1Floods11 against an NDWI baseline.

Offline flood and typhoon preparedness controller for Arduino Mega 2560 Pro: ultrasonic water level, BME280 pressure trend, TRI scoring, staged alerts, low-voltage relay cutoff.

Generates a merged raster mosaic for the entire AMD0 boundary, overcoming DEA sandbox disk and memory limitations.

Deep-learning + GIS pipeline detecting flood-driving drainage encroachment from 5 cm aerial imagery — U-Net semantic segmentation, multi-temporal change detection (Accra, Ghana)

A Multi-Model Ensemble Framework for Flood Detection and Early Warning in Bihar using BiLSTM, SAR Imagery, Weather Data, and Machine Learning.

Flood Vision - A deep learning–based computer vision system for flood mapping and damage assessment using aerial imagery.