Technology
How we turn planetary data into exploration intelligence.
Scientific data → processing → terrain → analysis → planning → results.
Stage 01 / 06
Scientific data
Collect documented planetary imagery, elevation data and mission metadata from supported sources.
- Prefer official downloads and supported services: USGS Astrogeology, NASA PDS nodes, NASA Solar System Treks.
- Record the product, version, DOI, licence and retrieval date with every file.
- Never scrape restricted systems; cache downloads and respect rate limits.
On this website
USGS Mars 2020 TRN CTX DTM and orthoimage (CC0), Viking MDIM 2.1, MOLA, the Perseverance traverse and IAU names.
A / Capability area
Planetary Mapping
Transform elevation models, imagery and geospatial data into useful planetary maps.
Maps are where every question about a site begins. We build them in the body's own coordinate system, at the resolution the data actually has, with the source of every pixel one click away.
- Available
Rotating Mars globe from the Viking MDIM 2.1 mosaic with MOLA relief shading
Home page
- Available
Jezero terrain model with draped CTX orthoimagery, in 3-D and 2-D
Terrain Lab
- Prototype
Whole-Mars globe streaming imagery down to ~5 m/pixel
MOMAR
- Planned
Lunar maps from LOLA elevation and LROC imagery
B / Capability area
Terrain Intelligence
Derive terrain characteristics such as slope and elevation variation from suitable scientific datasets.
Terrain intelligence turns a grid of heights into answers: how steep, how rough, where the ground changes. We keep a strict line between what was measured, what was derived exactly, and what was estimated under assumptions.
- Available
Slope by Horn's method with latitude-correct cell sizes
Terrain Lab
- Available
Hazard mask: cells over, and close to, a selectable slope limit
Terrain Lab
- Prototype
Roughness and per-cell risk grids, including sampled 1 m HiRISE slopes
MOMAR
- Planned
Rock and obstacle detection from high-resolution imagery
Measured: elevation. Derived exactly: slope, hillshade, the hazard mask. Estimated under assumptions: risk scores and route costs. Illustrative only: MOMAR's 3-D rocks, fine relief and weather.
C / Capability area
Mission Planning
Explore candidate routes and mission regions while accounting for terrain risks and other available constraints.
A route is a hypothesis about a mission. We plan more than one, show what each optimizes for, and report the numbers that separate them — never a single unexplained score.
- Available
Shortest and lower-slope routes with statistics and an elevation profile
Terrain Lab
- Prototype
Multi-stop itineraries, return-to-base checks and time budgets
MOMAR
- Prototype
Science stops from mineral indicators and mapped geologic contacts
MOMAR
- Planned
Illumination and shadow analysis
- Planned
Communication-window constraints, where reliable data exists
Slope alone is not a safety model. Real mission planning also needs surface material, rock abundance, vehicle characteristics, lighting, communications, thermal conditions and the mission's own rules.
E / Capability area
Scientific Data Processing
Build reproducible pipelines for retrieving, validating, transforming, visualizing and analysing planetary datasets.
Trust in a result depends on being able to trace it. Every pipeline step writes what it read, what it did, and whether it succeeded — and a failed step is reported as missing, never filled with a guess.
- Available
Reproducible asset build with recorded provenance for this website
scripts/build-assets.mjs
- Prototype
Python pipeline (GDAL/rasterio) with a per-step real / fallback / unavailable status
MOMAR
- Prototype
In-browser range reads of cloud-hosted planetary GeoTIFFs
MOMAR
- Planned
Lunar pipeline for LOLA and LROC products
Four kinds of result, never mixed up.
Values taken from a documented dataset, with its stated accuracy.
e.g. elevation from the CTX DTM
Calculated exactly from measured data by a stated formula. Same input, same output.
e.g. slope by Horn's method
Optimal or computed under a model whose weights and limits are assumptions, shown with the result.
e.g. a lower-slope route under a 25° limit
Generated for visualization or scenario testing. Never presented as an observation.
e.g. MOMAR's illustrative 3-D rocks
Route planning: what the model includes
Routes are found with A* on the elevation grid, moving between the eight neighbours of each cell and never cutting a corner past an impassable cell. Cells steeper than the slope limit are impassable. The shortest route minimizes surface distance; the lower-slope route multiplies each step by 1 + 3 × (slope ÷ limit)². Both are optimal for their cost on this grid.
Statistics — length, climb, steepest and mean slope — are computed from the cells each route actually crosses. Nothing is filled in.
What slope alone does not capture
Slope is not a safety model. Real mission planning also needs:
- Rock abundance and individual obstacles smaller than the elevation posts
- Surface material: loose sand, dust, duricrust, regolith bearing strength
- Vehicle characteristics: wheel size, ground clearance, tilt and power limits
- Lighting and shadows, which change with time of day and season
- Communication windows to Earth or relay orbiters
- Thermal conditions and the mission's own operational rules