Sponsored by
Sort By
Holds a list of open source Python packages interesting to Hydrologists.
lang: Python
stars: 505
last activity:
R client for interacting with the USA National Phenology Network data web services.
lang: R
stars: 21
last activity:
Automatic tree crown delineation based on the Detectron2 implementation of Mask R-CNN.
lang: Python
stars: 194
last activity:
A Sector-Coupled Open Optimization Model of the European Transmission System.
lang: Python
stars: 432
last activity:
A highly-configurable, open source electricity resource capacity expansion model that incorporates several state-of-the-art practices in electricity system planning to offer improved decision support for a changing electricity landscape.
lang: Julia
stars: 313
last activity:
Makes it easier to use hydrological models without having intimate knowledge about how to install and run the models.
lang: Python
stars: 37
last activity:
Xarray extension for unstructured climate and global weather data analysis and visualization.
lang: Python
stars: 193
last activity:
A Python library aims to empower wind resource analysts and establish a common industry standard toolset.
lang: Python
stars: 57
last activity:
Uses mixed integer linear programming techniques to provide a flexible interface for building and solving conservation planning problems.
lang: R
stars: 127
last activity:
Provide map data which revolutionises disaster management, reduces risks, and contributes to achievement of the Sustainable Development Goals.
lang: HTML
stars: 68
last activity:
An easy to use open source tool for power system modeling, analysis and optimization with a high degree of automation.
lang: Python
stars: 985
last activity:
An open source project and Python package that introduces labels in the form of dimensions, coordinates, and attributes on top of raw NumPy-like arrays, which allows for more intuitive, more concise, and less error-prone user experience.
lang: Python
stars: 3.9K
last activity:
A npm module for accessing the green web API, and estimating the carbon emissions from using digital services.
lang: JavaScript
stars: 456
last activity:
An integrated web-based workbench for taxonomists and biodiversity scientists.
lang: Ruby
stars: 104
last activity:
A community learning resource for Python-based computing in the geosciences.
lang: Jupyter Notebook
stars: 66
last activity: