Hesperides Rupes
What Hesperides Rupes is
Hesperides Rupes is a rupes — a scarp or cliff — on Mercury, 374 km across, centred at 3.0° S, 170.4° E in the Tolstoj quadrangle. It is the 48th largest named feature on Mercury and the 22nd largest of its class there.
Where the name comes from
Spanish; a global research vessel, used since 1991 for studies of geology, geophysics, hydrography, physical and chemical oceanography, marine biology as well as for logistical support to the Spanish Antarctic bases. The International Astronomical Union approved the name in 2023, under the theme it applies to every rupes on Mercury. Of the 66 features of this class catalogued on Mercury, the naming categories run England (11), United States (6), The Netherlands (Dutch) (4), France (4).
What it would take to settle Hesperides Rupes
Mercury scores 46 as a world. That number is the same for every square metre of it — but sunlight, water, radiation and the ground under your feet are not. This is the same question asked at 3.0° S, 170.4° E.
What this spot has going for it is sunlight — 100% of the sunlight the sunniest latitude on Mercury gets. What works against it is water — outside the ice-bearing latitudes.
Computed from Hesperides Rupes's catalogued latitude, longitude and feature class — 68% of the model's weight had a basis here, and 3 axes were dropped as not applicable to Mercury (radiation geometry, earth link, known ground). Gravity, pressure, delta-v and distance from the Sun are the same everywhere on Mercury and are already counted in the world's own index, not again here.
What this cannot see: elevation. Slope, local shadowing and the polar “peaks of eternal light” — ridge tops near the poles of a barely tilted world that catch sun almost continuously while a crater floor kilometres away never does — need a terrain model this does not have. Where a real mission targets a pole, that is usually why.
What is next to it
The largest rupes features on Mercury
All 66 rupes on Mercury — mapped together, with the naming theme and the size distribution.