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

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

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.

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

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.

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.

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.

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

NASA-IBM Prithvi-EO-2.0 fine-tuned on Sen1Floods11 for satellite flood segmentation, with Grad-CAM explainability. Live Gradio demo on HF Spaces.

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.

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

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

Embedding-based flood detection using AlphaEarth satellite embeddings, GeoTIFF flood datasets, and machine learning for scalable geospatial flood classification.