cultionet
Crop mapper
A deep learning library for image segmentation of cultivated land from satellite data
Image segmentation of cultivated land
27 stars
1 watching
5 forks
Language: Python
last commit: 4 months ago
Linked from 1 awesome list
agriculturecroplandcropsdeep-learningfieldsland-coverpytorchpytorch-lightningremote-sensingsatellite
protontypes/open-sustainable-technologyRelated projects:
| Repository | Description | Stars |
|---|---|---|
 jlandmann/glaciersat | Software package for analyzing satellite imagery of glaciers, providing monitoring tools and assessing observation uncertainties. | 8 |
 chjch/pylusat | An open-source Python toolkit providing a suite of geospatial analysis tools for land use suitability analysis | 14 |
 yannforget/pylandsat | A tool for accessing and preprocessing Landsat imagery from the Google Cloud dataset | 65 |
 jgcri/demeter | An open source Python package that disaggregates future land allocation projections from integrated models into detailed land use and land cover data | 26 |
 maja601/eurocrops | A comprehensive dataset collection combining EU countries' crop reporting data, harmonized with a standardized taxonomy for machine-readable analysis. | 177 |
 developmentseed/label-maker | Automatically annotates satellite images with OpenStreetMap data | 461 |
 dl4sits/breizhcrops | A platform for crop type identification using satellite time series data | 200 |
 orion-ai-lab/s4a | A dataset and software toolkit for deep learning-based crop classification and segmentation from Sentinel-2 satellite imagery | 90 |
 nasaharvest/cropharvest | A remote sensing dataset with associated benchmarks and tools for training machine learning models. | 175 |
 muesli/smartcrop | Automates image cropping to maintain aspect ratios | 1,820 |
 johntruckenbrodt/pyrosar | A framework for processing SAR satellite data from various sources | 514 |
 computational-plant-science/dirt | Automated high-throughput root phenotyping platform using image processing and machine learning algorithms. | 25 |
 jliemansifry/semantic-segmentation | Develops deep learning models to classify and annotate pixel-level details in satellite images | 21 |
 allenai/satlas | Provides high-quality AI-generated geospatial data by applying deep learning models to satellite imagery, enabling accurate and frequent mapping of the Earth's landmass. | 205 |
 evan-delancey/googleearthengine | Develops algorithms and integrates satellite data from Google Earth Engine to analyze land surface changes and track environmental patterns. | 11 |