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SISPPEO (Satellite Imagery & Signal Processing Packages for Earth Observation) project is dedicated to packages necessary for extracting synthetic information from satellite imagery data (e.g, Sentinel-2, -3, Landsat...) for earth observation (Water and Land).

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SISPPEO: Satellite Imagery & Signal Processing Package for Earth Observation

Conda (channel only) Conda Conda - License DOI

Content

  1. What is SISPPEO ?
  2. Requirements
  3. Installation
  4. Dependencies

What is SISPPEO ?

SISPPEO is an open source project and Python package (with a CLI) allowing one to extract synthetic information useful for Earth observation (Water and Land) from satellite optical imagery (e.g, Sentinel-2/MSI, Sentinel-3/OLCI, Landsat 8/OLI…).

Author: Arthur Coqué ([email protected])

Contributors: Guillaume Morin ([email protected]), Nathalie Reynaud ([email protected]), Thierry Tormos ([email protected]), Valentine Aubard ([email protected])

Requirements

You will need Python 3.8 to run SISPPEO. You can have multiple Python versions (2.x and 3.x) installed on the same system without any problems.

Installation

SISPPEO can be downloaded and installed using conda-forge:

$ conda install sisppeo -c conda-forge

You can also install it from source. To do so, you will first have to clone the GitHub repository:

$ git clone https://github.com/inrae/SISPPEO.git
$ cd sisppeo

Then, you will need to create a virtual environment (optional, but strongly advised) and install SISPPEO.

  • using conda (recommended):
$ conda env create -f conda/environment.yml
$ pip install .
  • using virtualenv and pip:
$ python3 -m venv venv
$ source venv/bin/activate

$ pip install -U .

Finally, you can use SISPPEO as a Python package (it's kind of like a toolbox) or through its CLI:

$ sippeo <your_cmd>

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SISPPEO (Satellite Imagery & Signal Processing Packages for Earth Observation) project is dedicated to packages necessary for extracting synthetic information from satellite imagery data (e.g, Sentinel-2, -3, Landsat...) for earth observation (Water and Land).

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