Open source web based lunar ejecta thickness and layering calculator application

Introduction: Ejecta layering is an important characteristic of the airless lunar surface, and ejecta emplacement contributes much in the surface modification and regolith evolution [1, 2]. Next lunar missions, especially under the Artemis project [3], and the CP-22 mission with the PROSPECT payload onboard [4] will have various interactions with the regolith. including sampling and geotechnical processing, thus information on the structure of the regolith is useful both for scientific, In Situ Resource Utilization (ISRU) and safety aspects. Especially small craters have been poorly covered and understood in these aspects [5] as well as for next landing site candidates [6]. I present a new method of ejecta thickness estimation and introduce the test version of a web based application, which calculates the thickness, volume and stratigraphy of the ejecta for a chosen location on the lunar surface and estimates their source craters.

Data processing and visualization: Based on several measurements on the general topographic radial profile of ejecta plus bedrock uplift around differently sized craters, i used LOLA Digital Elevation model with spatial resolution of 60 m/px (for crates with diameter < 2 km) and WAC Digital Elevation Model with spatial resolution of 100 m/px (for craters with diameter > 2 km) to define a mathematical formula to model the observed crater ejecta topography. 

Figure 1. Digital Elevation Model (first column) and optical images (LRO Narrow Angle Camera Mosaic and Wide Angle Camera Mosaic, second column) from examples of different crater size categories and the ejecta profiles (third column) of the three craters form each categories (blue lines) and the modelled ejecta thickness (red lines).

Having an ejecta estimation formula, in the next stage i have developed the online application, where clients can query information about the ejecta thickness for the selected point in the lunar surface. 

Figure 2. Used techniques and frameworks for the application.

For the calculation and visualization purposes two types of data storage are necessary. The position and size information about lunar craters are the key of the calculations: i used the Robbins crater database [7], that contains more than 1.2 million craters larger than 1km. PosGIS extension of PostgreSQL [8] was implemented to store these data. Navigation and localization on the lunar surface is important for the proper site selection: Geoserver [9] is designed to store spatial datasets, i added the IAU planetary CRS extension for the appropriate coordinate handling of the LROC WAC global mosaic with 100 m/px resolution.

I used JavaScript based Leaflet.js [10] for the site selection: the client has to click on the displayed lunar surface and jQuery [11] gives the coordinates of the chosen point to the Python based Flask [12] application. This application connects to the PostGIS database and extract the thickness data with an sql selection. After the calculation the backend converts the data to JSON (for displaying) and CSV (for downloading) and transfer back to the browser with MIME (Multipurpose Internet Mail Extensions).

Figure 3. Visualization of the source craters and their ejecta thickness at the selected location (centre) displayed in the Leaflet map. 

The Leaflet window displays the result: the craters that provides ejecta to the selected point with opacity related to the thickness. Blue popups also appear at the center of the craters and contain information about position, distance from the selected point, diameter and provided ejecta.

Future development: I am planning the further development of this application with some other important features. Age estimation (fist relative, then absolute where possible) of the source craters is the next stage. After the age information will be available, i can create layer sequence stratigraphy for the selected location. In the near future i will release this open source application to the planetary scientist community.   

 

Acknowledgement

This work was supported by the LUNGISTRAT project of ESA (4000146132), formerly the Ministry of National Economy and Trade, recently the Ministry of National Economic.

 

References

[1] Takano et al. 2020. Experimental study on thermal properties of high porosity particles for understanding physical properties of Phobos surface. In: JpGU-AGU Joint Meeting, PPS08-P01.

[2] Kobayashi et al. 2023. Laboratory measurements show temperature-dependent permittivity of lunar regolith simulants. Earth Planets and Space 75:1, 8.

[3] Moriarty and Petro 2024. Journal of Geophysical Research: Planets, Volume 129, Issue 4, article id. e2023JE008266.

[4] Heather et al. 2024. The ESA PROSPECT Payload for CP22: Science Activities and Operations Planning. 55th LPSC, No. 3040, id.1085

[5] Kereszturi and Steinmann 2019. Terra-mare comparison of small young craters on the Moon. Icarus 322, 54-68.

[6] Leone et al. 2023. Sverdrup-Henson crater: a candidate location for the first lunar South Pole settlement. iScience 9;26(10):107853.

[7] Robbins 2018. A New Global Database of Lunar Impact Craters >1–2 km: 1. Crater Locations and Sizes, Comparisons With Published Databases, and Global Analysis. . Journal of Geophysical Research: Planets, Volume 124, Issue 4. 871-892.

[8] PostgreSQL, https://www.postgresql.org/

[9] Geoserver, https://geoserver.org/

[10] Leaflet.js, https://leafletjs.com/

[11] jQuery, https://jquery.com/

[12] Flask, https://flask.palletsprojects.com/en/stable/