Determination of magnetopause and bow shock shape based on convolutional neural network modelling of MESSENGER data

<p><span id="E87">The magnetosphere of Mercury is relatively small and highly dynamic, mostly due to the weak planetary magnetic field. Varying solar wind conditions principally determine the location of both the </span><span id="E89">Hermean</span><span id="E91"> bow shock and magnetopause. In 2011 – 2015 MESSENGER spacecraft completed over 4000 orbits around Mercury, thus giving a data of more than 8000 crossings of bow shock and magnetopause of the planet, this makes it possible to study in detail the bow shock, the magnetopause and the </span><span id="E93">magnetosheath</span><span id="E95"> structures.</span></p> <p>In this work we determine crossings of the bow shock and the magnetopause of Mercury by applying machine learning methods to the MESSENGER magnetometer data. We attempt to identify the crossings during the whole duration of the orbital mission and model the average three-dimensional shapes of these boundaries. The results are compared with those previously obtained in other works.</p> <p><span id="E101">This work may be of interest for future Mercury research related to the </span><span id="E103">BepiColombo</span><span id="E105"> spacecraft mission, which will enter the orbit around the planet in December 2025.</span></p>

Venus: key to understanding the evolution of terrestrial planets

In this paper, originally submitted in answer to ESA’s “Voyage 2050” call to shape the agency’s space science missions in the 2035–2050 timeframe, we emphasize the importance of a Venus exploration programme for the wider goal of understanding the diversity and evolution of habitable planets. Comparing the interior, surface, and atmosphere evolution of Earth, Mars, and Venus is essential to understanding what processes determined habitability of our own planet and Earth-like planets everywhere. This is particularly true in an era where we expect thousands, and then millions, of terrestrial exoplanets to be discovered. Earth and Mars have already dedicated exploration programmes, but our understanding of Venus, particularly of its geology and its history, lags behind. Multiple exploration vehicles will be needed to characterize Venus’ richly varied interior, surface, atmosphere and magnetosphere environments. Between now and 2050 we recommend that ESA launch at least two M-class missions to Venus (in order of priority): a geophysics-focussed orbiter (the currently proposed M5 EnVision orbiter – [1] – or equivalent); and an in situ atmospheric mission (such as the M3 EVE balloon mission – [2]). An in situ and orbital mission could be combined in a single L-class mission, as was argued in responses to the call for L2/L3 themes [3–5]. After these two missions, further priorities include a surface lander demonstrating the high-temperature technologies needed for extended surface missions; and/or a further orbiter with follow-up high-resolution surface radar imaging, and atmospheric and/or ionospheric investigations.

HIGH-RESOLUTION TOPOGRAPHY OF MERCURY FROM MESSENGER ORBITAL STEREO IMAGING – THE SOUTHERN HEMISPHERE QUADRANGLES

We produce high-resolution (222 m/grid element) Digital Terrain Models (DTMs) for Mercury using stereo images from the MESSENGER orbital mission. We have developed a scheme to process large numbers, typically more than 6000, images by photogrammetric techniques, which include, multiple image matching, pyramid strategy, and bundle block adjustments. In this paper, we present models for map quadrangles of the southern hemisphere H11, H12, H13, and H14.

Activity Planning for a Lunar Orbital Mission

This article describes a challenging, real-world planning problem within the context of a NASA mission called LADEE (Lunar Atmospheric and Dust Environment Explorer). I present the approach taken to reduce the complexity of the activity-planning task in order to perform it effectively under the time pressures imposed by the mission requirements. One key aspect of this approach is the design of the activity planning process based on principles of problem decomposition and planning abstraction levels. The second key aspect is the mixed-initiative system developed for this task, called LASS (LADEE Activity Scheduling System). The primary challenge for LASS was representing and managing the science constraints that were tied to key points in the spacecraft’s orbit, given their dynamic nature due to the continually updated orbit determination solution.