prs-eth/Popcorn
[RSE 2024] 🍿POPCORN: High-resolution Population Maps Derived from Sentinel-1 and Sentinel-2 🌍🛰️
This project helps urban planners, humanitarian organizations, and researchers create detailed, up-to-date population maps. It takes free satellite images from Sentinel-1 and Sentinel-2, along with a few regional population counts, to produce high-resolution maps showing population density and built-up areas. This is ideal for those needing current population data, especially in areas where traditional census data is outdated or unavailable.
Use this if you need to quickly generate detailed population distribution maps for urban planning, disaster response, or resource allocation, particularly in regions with limited traditional census data.
Not ideal if you require extremely granular, building-level population counts or if you primarily rely on existing, high-resolution commercial imagery for your mapping needs.
Stars
43
Forks
13
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Jan 22, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/prs-eth/Popcorn"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
DPIRD-DMA/OmniWaterMask
Python library for high-accuracy water segmentation in satellite and aerial imagery, combining...
xinluo2018/WatNetv2
A new WatNet version which further extends the data applicability from Sentinel-2 image to...
sei-latam/WETSAT_v2
Wetlands flooding extent and trends using SATellite data and Machine Learning v2.0
sidgan/ETCI-2021-Competition-on-Flood-Detection
Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and...
iarai/Landslide4Sense-2022
Data description and baseline code for LandSlide4Sense 2022 competition