gms-preprocessing 0.19.1

GeoMultiSens - Scalable Multi-Sensor Analysis of 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)

• 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.

• OS compatibility: Linux

Status

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)

• correction of geometric errors (using AROSICS)

Level-2 processing:

• spatial homogenization

• spectral homogenization (using 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.

Usage via console interface

Homogenization jobs can also be created and started using the command line interface. Documentation can be found here.

Here is a small example:

# 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. 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:

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.

History / Changelog

You can find the protocol of recent changes in the gms_preprocessing package here.

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

Daniel Scheffler

eMail: [e-mail]

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.