Releases: earthlab/cross-sensor-cal
Version 1
EarthLabSpectral v0.1 Release
We are thrilled to announce the initial release of EarthLabSpectral v0.1, a comprehensive toolkit designed for the calibration and resampling of multispectral and hyperspectral satellite imagery. This release marks a significant milestone in our journey to provide the Earth observation community with robust, open-source tools for remote sensing data analysis.
Key Features:
Cross-Sensor Spectral Calibration: Seamlessly calibrate spectral data across different satellite sensors, enhancing the compatibility and comparability of datasets.
Advanced Resampling Techniques: Utilize state-of-the-art resampling algorithms to match satellite imagery across varying spectral resolutions.
Support for Major Satellite Data Formats: Whether you're working with Landsat, Sentinel, or other satellite platforms, EarthLabSpectral offers extensive format support.
Intuitive Data Analysis Workflow: From loading and processing data to visualizing results, our toolkit is designed to streamline your analysis workflow.
What's New in v0.1:
Initial implementation of Gaussian resampling for spectral data.
Support for reading and writing ENVI-format spectral datasets.
Integration with popular Python libraries like GeoPandas, Rasterio, and Matplotlib for spatial analysis and visualization.
A selection of example notebooks to get you started with common remote sensing tasks.
Getting Started:
To begin using EarthLabSpectral, please refer to our documentation and example vignettes. Installation instructions and detailed API documentation are available to help you integrate EarthLabSpectral into your projects.
Contributing:
EarthLabSpectral is a community-driven project, and contributions are warmly welcomed. Whether you're interested in adding new features, improving documentation, or reporting bugs, please visit our GitHub repository to get involved.
Acknowledgments:
This project is made possible by the contributions of Ty Tuff, Erick Verleye, and the broader EarthLab community. We extend our heartfelt thanks to everyone who has provided feedback, submitted patches, and supported EarthLabSpectral's development.
Stay Updated:
For the latest updates, follow our project on GitHub and join our community discussion channels. We're excited to see how you use EarthLabSpectral in your remote sensing research and applications!