iarai/Landslide4Sense-2022
Data description and baseline code for LandSlide4Sense 2022 competition
This project helps disaster management specialists and environmental scientists automatically identify landslides using satellite imagery. It takes multi-spectral data, slope data, and digital elevation models as input. The output is a precise map showing the exact location and extent of landslides, which is crucial for quick response and risk assessment.
137 stars. No commits in the last 6 months.
Use this if you need to accurately detect landslides across diverse global regions using satellite images, especially for research or developing new detection algorithms.
Not ideal if you need a real-time operational system for immediate on-the-ground landslide warnings, as this is a benchmark and competition dataset for algorithm development.
Stars
137
Forks
31
Language
Python
License
MIT
Category
Last pushed
Jun 21, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/iarai/Landslide4Sense-2022"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
DPIRD-DMA/OmniWaterMask
Python library for high-accuracy water segmentation in satellite and aerial imagery, combining...
prs-eth/Popcorn
[RSE 2024] 🍿POPCORN: High-resolution Population Maps Derived from Sentinel-1 and Sentinel-2 🌍🛰️
xinluo2018/WatNetv2
A new WatNet version which further extends the data applicability from Sentinel-2 image to...
sidgan/ETCI-2021-Competition-on-Flood-Detection
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and...
sei-latam/WETSAT_v2
Wetlands flooding extent and trends using SATellite data and Machine Learning v2.0