jgrss/cultionet
Image segmentation of cultivated land
This project helps agricultural analysts, environmental scientists, and land-use planners accurately map cultivated land. By inputting satellite image time series and hand-drawn crop field outlines, it produces detailed maps showing where cultivated areas are located. This allows professionals to understand land use patterns and monitor agricultural activity over time.
No commits in the last 6 months.
Use this if you need to precisely identify and map cultivated land from satellite imagery, especially using time-series data for improved accuracy.
Not ideal if you only have single-date satellite images or require mapping very small, irregular plots that are hard to define with polygons.
Stars
31
Forks
5
Language
Python
License
Apache-2.0
Category
Last pushed
Sep 23, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/jgrss/cultionet"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
maja601/EuroCrops
The official repository for the EuroCrops dataset.
dida-do/eurocropsml
EuroCropsML is a ready-to-use benchmark dataset for few-shot crop type classification using...
langnico/global-canopy-height-model
This repository contains the code used in the paper: A high-resolution canopy height model of...
clejae/europe_land_iacs_prep
Preprocessing and harmonization scripts for IACS/GSA data.
raoofnaushad/Land-Cover-Classification-using-Sentinel-2-Dataset
Application of deep learning on Satellite Imagery of Sentinel-2 satellite that move around the...