Metadata-Version: 2.1
Name: gms-preprocessing
Version: 0.18.12
Summary: GeoMultiSens - Scalable Multi-Sensor Analysis of Remote Sensing Data
Home-page: https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing
Author: Daniel Scheffler
Author-email: daniel.scheffler@gfz-potsdam.de
License: GPL-3.0-or-later
Description: =========================================================================================
        gms_preprocessing - Spatial and spectral homogenization of satellite remote sensing data.
        =========================================================================================
        
        The goal of the gms_preprocessing Python library is to provide a fully automatic
        pre-precessing pipeline for spatial and spectral fusion (i.e., homogenization)
        of multispectral satellite image data. Currently it offers compatibility to
        Landsat-5, Landsat-7, Landsat-8, Sentinel-2A and Sentinel-2B.
        
        * Free software: GNU General Public License v3 or later (GPLv3+) (`license details <https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/blob/master/LICENSE>`_)
        * Documentation: https://geomultisens.gitext-pages.gfz-potsdam.de/gms_preprocessing/doc/
        * Code history: Release notes for the current and earlier versions of gms_preprocessing can be found `here <./HISTORY.rst>`_.
        * OS compatibility: Linux
        
        
        Status
        ------
        
        .. .. image:: https://img.shields.io/travis/geomultisens/gms_preprocessing.svg
                :target: https://travis-ci.org/geomultisens/gms_preprocessing
        
        .. .. image:: https://readthedocs.org/projects/gms_preprocessing/badge/?version=latest
                :target: https://gms_preprocessing.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
        .. .. image:: https://pyup.io/repos/github/geomultisens/gms_preprocessing/shield.svg
             :target: https://pyup.io/repos/github/geomultisens/gms_preprocessing/
             :alt: Updates
        
        .. image:: https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/badges/master/pipeline.svg
                :target: https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/commits/master
        .. image:: https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/badges/master/coverage.svg
                :target: https://geomultisens.gitext-pages.gfz-potsdam.de/gms_preprocessing/coverage/
        .. image:: https://img.shields.io/pypi/v/gms_preprocessing.svg
                :target: https://pypi.python.org/pypi/gms_preprocessing
        .. image:: https://img.shields.io/conda/vn/conda-forge/gms_preprocessing.svg
                :target: https://anaconda.org/conda-forge/gms_preprocessing
        .. image:: https://img.shields.io/pypi/l/gms_preprocessing.svg
                :target: https://gitext.gfz-potsdam.de/danschef/gms_preprocessing/blob/master/LICENSE
        .. image:: https://img.shields.io/pypi/pyversions/gms_preprocessing.svg
                :target: https://img.shields.io/pypi/pyversions/gms_preprocessing.svg
        
        See also the latest coverage_ report and the nosetests_ HTML report.
        
        Features
        --------
        
        Level-1 processing:
        ^^^^^^^^^^^^^^^^^^^
        
        * data import and  metadata homogenization (compatibility: Landsat-5/7/8, Sentinel-2A/2B)
        * equalization of acquisition- and illumination geometry
        * atmospheric correction (using `SICOR <https://gitext.gfz-potsdam.de/EnMAP/sicor>`_)
        * correction of geometric errors (using `AROSICS <https://gitext.gfz-potsdam.de/danschef/arosics>`_)
        
        Level-2 processing:
        ^^^^^^^^^^^^^^^^^^^
        
        * spatial homogenization
        * spectral homogenization (using `SpecHomo <https://gitext.gfz-potsdam.de/geomultisens/spechomo>`_)
        * estimation of accuracy layers
        
        => application oriented analysis dataset
        
        
        Getting started
        ---------------
        
        Usage via WebApp
        ^^^^^^^^^^^^^^^^
        
        The recommended way to use gms_preprocessing is to setup the WebApp (see the
        gms-vis_ repository) providing a UI for GeoMultiSens. Using this UI, existing
        satellite data can be explored, filtered and selected for processing. New data
        homogenization jobs (using gms_preprocessing) can be defined and started. All
        configuration parameters of gms_preprocessing are accessible in the UI.
        
        
        .. image:: https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/raw/master/docs/images/webapp_screenshot_900x497.png
            :width: 900 px
            :height: 497 px
            :scale: 100 %
            :alt: WebApp Screenshot
        
        
        Usage via console interface
        ^^^^^^^^^^^^^^^^^^^^^^^^^^^
        
        Homogenization jobs can also be created and started using the command line
        interface. Documentation can be found `here <https://geomultisens.gitext-pages.gfz-potsdam.de/gms_preprocessing/doc/usage.html#gms-preprocessing-command-line-interface>`__.
        
        Here is a small example:
        
        .. code:: bash
        
            # start the job with the ID 123456 and override default configuration with the given one.
            >>> run_gms.py jobid 123456 --json_config /path/to/my/config.json
        
        There is a default configuration file, called `options_default.json <https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/blob/master/gms_preprocessing/options/options_default.json>`_.
        This file contains the documentation for all the available configuration
        parameters.
        
        
        Usage via Python API
        ^^^^^^^^^^^^^^^^^^^^
        
        There is also a Python API that allows to setup and start homogenization jobs
        by a Python function call.
        
        This is an example:
        
        .. code:: python
        
            from gms_preprocessing import ProcessController
        
            configuration = dict(
                db_host='localhost',
                CPUs=20
                )
        
            PC = ProcessController(job_ID=123456, **configuration)
            PC.run_all_processors()
        
        Possible configuration arguments can be found `here <https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/blob/master/gms_preprocessing/options/options_schema.py>`__.
        
        
        History / Changelog
        -------------------
        
        You can find the protocol of recent changes in the gms_preprocessing package
        `here <https://gitext.gfz-potsdam.de/geomultisens/gms_preprocessing/-/blob/master/HISTORY.rst>`__.
        
        
        License
        -------
        
        gms_preprocessing - Spatial and spectral homogenization of satellite remote sensing data.
        
        Copyright 2020 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, Potsdam, Germany
        
        This program is free software: you can redistribute it and/or modify
        it under the terms of the GNU General Public License as published by
        the Free Software Foundation, either version 3 of the License, or
        (at your option) any later version. This program is distributed in the hope
        that it will be useful, but WITHOUT ANY WARRANTY; without even the implied
        warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
        GNU General Public License for more details. You should have received a copy
        of the GNU General Public License along with this program.
        If not, see <http://www.gnu.org/licenses/>.
        
        
        Contact
        -------
        
        .. line-block::
        
            Daniel Scheffler
            eMail: daniel.scheffler@gfz-potsdam.de
        
            Helmholtz Centre Potsdam GFZ German Research Centre for Geoscienes
            Section 1.4 Remote Sensing
            Telegrafenberg
            14473 Potsdam
            Germany
        
        
        Credits
        -------
        
        The development of the gms_preprocessing package was funded by the German Federal Ministry of Education and Research
        (BMBF, project grant code: 01 IS 14 010 A-C).
        
        The package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
        
        Landsat-5/7/8 satellite data and SRTM/ASTER digital elevation models have been provided by the US Geological
        Survey. Sentinel-2 data have been provided by ESA.
        
        .. _Cookiecutter: https://github.com/audreyr/cookiecutter
        .. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
        .. _coverage: https://geomultisens.gitext-pages.gfz-potsdam.de/gms_preprocessing/coverage/
        .. _nosetests: https://geomultisens.gitext-pages.gfz-potsdam.de/gms_preprocessing/nosetests_reports/nosetests.html
        .. _conda: https://conda.io/docs/
        .. _redis-server: https://www.rosehosting.com/blog/how-to-install-configure-and-use-redis-on-ubuntu-16-04/
        .. _gms-vis: https://gitext.gfz-potsdam.de/geomultisens/gms-vis
        
Keywords: gms_preprocessing
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Provides-Extra: doc
Provides-Extra: test
Provides-Extra: lint
Provides-Extra: dev
