.. image:: https://img.shields.io/badge/license-MIT-green :target: https://github.com/andersonreisoares/stmetrics/master/LICENSE :alt: License
.. image:: https://travis-ci.org/andersonreisoares/stmetrics.svg?branch=master :target: https://travis-ci.org/andersonreisoares/stmetrics
.. image:: https://codecov.io/gh/andersonreisoares/stmetrics/branch/master/graph/badge.svg?token=Y4WGJR12GF :target: https://codecov.io/gh/andersonreisoares/stmetrics
.. image:: https://readthedocs.org/projects/stmetrics/badge/?version=latest :target: https://stmetrics.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status
Produce reliable land use and land cover maps to support the deployment and operation of public policies is a necessity, especially when environmental management and economic development are considered. To increase the accuracy of these maps, satellite image time-series have been used, as they allow the understanding of land cover dynamics through the time.
The stmetrics, is a python package that provides the extraction of state-of-the-art time-series features. These features can be used for remote sensing time-series image classification and analysis.
See Installation <./docs/source/installation.rst>
_.
See https://stmetrics.readthedocs.io/en/latest/
Windows users, please check the installation procedures in our documentation!
See Example Notebook <./docs/source/examples/TimeMetrics.ipynb>
_.
Copyright (C) 2019 INPE.
STMETRICS is free software; you can redistribute it and/or modify it under the terms of the MIT License; see LICENSE file for more details.