Moon Coverage Documentation

The moon-coverage python package is a toolbox to perform surface coverage analysis based on orbital trajectory configuration. Its main intent is to provide an easy way to compute observation opportunities of specific region of interest above the Galilean satellites for the ESA-JUICE mission but could be extended in the future to other space mission.

It is actively developed by the Laboratory of Planetology and Geodynamics (CNRS-UMR 6112) at the University of Nantes (France), under ESA-JUICE founding support.

Installation

The package is available on pypi and can be install directly with pip:

$ pip install moon-coverage

If you already installed moon-coverage and you want to upgrade it to the latest version, you need to add a --upgrade flag in the pip command above.

Kernel management and setup

The moon-coverage is a SPICE based application which requires a set of kernels to work. Usually these kernels are provided by the agency in charge of the space mission you are interested in. In the case of the ESA/JUICE mission, there kernels can be found in the ESA-SPICE Service public FTP inside the JUICE folder.

Knowing which kernel is required for your needs can be complicated, but usually, your kernel provider will also give you a meta-kernel that contains the list of all the kernels required for a specific configuration. In the case of JUICE, these meta-kernels are called CReMA.

New in version 0.9.0: If you work with ESA missions, you no longer need to manage and update your CReMAs manually. The tool will automatically query the ESA-SPICE bitbucket to get the latest version of the metakernels for you. If you need to use older versions, you now have the possibility to explicitly specify it at runtime.

Presentation of the tool in video

The moon-coverage tool was presented at the 5th Planetary Data Workshop in June 2021 and the video is publicly available on YouTube:

Note

The version of the tool used in this video is 0.8.0 and some function have slightly changed since then, but it should not affect the behavior of the tool significantly.

Table of Content

• Trajectory computations
  • Step 1 - Tour configuration setup
  • Step 2 - Select a Trajectory window
  • Trajectory SPICE helpers
  • Select an instrument
  • Filter the data
  • Step 3 - Display the trajectory on a map
  • Check if a trajectory intersects an ROI or collection of ROIs
  • Intersection between a trajectory and an ROI or a collection of ROIs
  • Represent the intersection of the trajectory and the ROIs on a Map
  • Find the target flybys
  • Represent the instrument field of view
  • TourConfig, Trajectory and Flyby API
• Maps
  • Map object
  • Custom map
• Region of Interest (ROI)
  • Ganymede and Callisto ROIs
  • ROI object
  • GeoJsonROI object
  • ROIsCollection object
  • [Sub]Category API
• Event files
  • Event file format
  • Parsing an event file
  • Events usage
  • Events filtering
• SPICE toolbox
  • SPICE Pool
  • SPICE references
  • SPICE time toolbox
  • SPICE aberration corrections
• SPICE kernel and metakernel parser
  • Text kernel parser and formatter
  • MetaKernel object
• ESA CReMA metakernels
  • JUICE CReMA Collection
  • Other ESA missions