mmuneeburahman/Natural-Disaster-Damage-Assessment-Deep-Learning
This repo contains datasets, papers and other information related to Destruction Detection in Satellite Imagery.
This project helps disaster response organizations and urban planners quickly assess damage after natural disasters. By analyzing satellite or aerial imagery, it identifies destroyed or damaged buildings. This allows for rapid evaluation of affected areas, guiding resource allocation and recovery efforts for emergency responders and government agencies.
No commits in the last 6 months.
Use this if you need to understand the extent of building destruction in an area after a disaster using satellite or UAV images.
Not ideal if you are looking for tools to process non-imaging data like social media posts or ground-level photos for damage assessment.
Stars
23
Forks
2
Language
—
License
—
Category
Last pushed
Oct 22, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/mmuneeburahman/Natural-Disaster-Damage-Assessment-Deep-Learning"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
satellite-image-deep-learning/techniques
Techniques for deep learning with satellite & aerial imagery
DPIRD-DMA/OmniCloudMask
OmniCloudMask is a Python library for fast, accurate cloud and cloud shadow segmentation in...
developmentseed/label-maker
Data Preparation for Satellite Machine Learning
NRCan/geo-deep-learning
Deep learning applied to georeferenced datasets
satellite-image-deep-learning/software
Software for working with satellite & aerial imagery ML datasets