Simulation

Venus Altimetry Data Sources

Comprehensive guide to public data sources for Venus terrain elevation, focusing on radar altimetry from key missions like Magellan.

venusterraindataaltimetry

Overview

Venus’s terrain data is primarily from radar altimetry due to its thick atmosphere blocking optical imaging. The Magellan mission (NASA, 1990-1994) provides the most comprehensive global topography dataset, covering ~98% of the surface at resolutions around 4-6 km/pixel horizontally, with vertical accuracy ~100-200m. This is augmented by earlier missions like Pioneer Venus (1978) for low-res altimetry, Venera 15/16 (Soviet, 1983) for northern hemisphere radar (~1-2 km resolution), and Earth-based radar from Arecibo Observatory. More recent missions like Akatsuki (JAXA, 2010-2025) focused on atmosphere, not terrain. Upcoming missions (e.g., VERITAS, EnVision) will provide higher-res data post-2030, but nothing new yet.

Data is archived in public repositories like NASA’s Planetary Data System (PDS), USGS Astrogeology (Astropedia), and specialized bundles. Formats include GeoTIFF (raster elevation grids), PDS IMG (binary images with labels), ASCII grids, and NetCDF for some derived products. Resolutions vary: global ~5km/pixel, regional stereo-derived up to ~200m/pixel.

Key archives for download:

Key Recommendation
For web-based terrain engines, start with USGS GeoTIFFs. They're georeferenced and support async tile loading via URLs or local files. All data is free/public domain. Download sizes range from MBs (low-res global) to GBs (high-res regional mosaics).

Major Data Sources

1. Magellan Global Topography Data Record (GTDR)

2. Magellan Stereo-Derived Topography

3. Magellan Colorized Topographic Mosaics

  • Description: Global mosaics combining topography with radar backscatter (reflectivity). Elevation color-coded (e.g., red=high, blue=low). Resolution: ~6.6 km/pixel. Useful for visualization in your /world/terrain shaders.
  • Formats: GeoTIFF (with color ramp), JPEG/PNG for previews.
  • Links/Download:
  • Notes: Derived from F-BIDR (Full-Resolution Basic Image Data Records). Can extract elevation channel.

4. Pioneer Venus Orbiter Altimetry

5. Venera 15/16 Radar Maps

  • Description: Radar imagery and derived topography for northern hemisphere (above 30°N). Resolution: ~1-2 km/pixel. Covers ~25% of Venus, focusing on plains and tectonics.
  • Formats: PDS IMG, GeoTIFF mosaics.
  • Links/Download:
  • Notes: Binary data needs label parsing (PDS format). Combine with Magellan for hybrid coverage.

6. Arecibo Earth-Based Radar Data

  • Description: Ground-based radar from Arecibo Observatory (1970s-2010s). Provides regional topography and roughness maps, resolution ~1-5 km. Covers equatorial regions, complementary to space missions.
  • Formats: FITS, ASCII grids.
  • Links/Download:
  • Notes: Sparse, but high vertical resolution (~10m in spots). Not global.

7. Other/Derived Datasets

Best Practices for Parsing in TypeScript/JavaScript

For browser-based 3D terrain engines (like those built with SvelteKit/Threlte), efficient async sector loading is critical. GeoTIFF is ideal—it’s georeferenced (lat/lon tied to pixels) and supports overviews/pyramids for level-of-detail. Avoid loading full global datasets (~GBs in memory); tile them or use cloud-optimized GeoTIFF (COG) where available.

Recommended Library: geotiff.js

  • Why: Pure JS, no dependencies, handles remote/local files, bilinear sampling. Works in browser/Node. GitHub: https://github.com/geotiffjs/geotiff.js/ (NPM: npm i geotiff).

  • Installation: npm install geotiff (TypeScript types available).

  • Basic Parsing Flow (example terrain loader implementation):

    import { fromUrl, fromFile } from 'geotiff'; // Or fromBlob for local

async function loadSector(url: string, latIndex: number, lonIndex: number): Promise<TerrainSector> {
  const tiff = await fromUrl(url); // Or fromFile('path/to/file.tif')
  const image = await tiff.getImage(); // Get first image (for single-band elevation)

  const width = image.getWidth(); // Samples per side
  const height = image.getHeight();
  const resolution = image.getResolution()[0]; // Meters/sample, or compute from bbox

  // Read raster data (Float32 elevation array)
  const [data] = await image.readRasters() as [Float32Array];

  // For sectors: Extract sub-array if needed (use readRasters with {window: [x,y,w,h]})
  // Bilinear sampling: Use image.readRasters({width:1, height:1, interleave:false, bbox:[lonMin,latMin,lonMax,latMax]})

  return { latIndex, lonIndex, data, resolution, size: width };
}

  • Sector Loading: For large files, use readRasters with window or bbox to fetch sub-regions (e.g., 1°x1° sectors). Cache with IndexedDB or localStorage for offline.

  • Coordinate Handling: Get tiepoints/model from image.getTiePoints(), image.getGDALMetadata(). Convert lat/lon to pixel: Use proj4.js for reprojection if not lat/lon projected.

  • Performance Tips:

    • Async/Throttle: Debounce sector loads to prevent cascade requests.
    • Fallback: Keep procedural generation for unloaded/sparse regions.
    • Compression: GeoTIFFs are often LZW/Deflate compressed—geotiff.js handles decompression automatically.
    • Three.js Integration: For WebGL terrain rendering, load elevation into heightmap textures: https://spatial-dev.guru/2024/11/30/creating-3d-terrain-maps-from-geotiff-files-with-three-js/
    • Error Handling: Check for NoData values in metadata, clamp extreme elevations.

  • Other Libs: If needed, tiff.js for non-geo TIFFs; GDAL.js (WASM) for advanced reprojection, but heavier.

Getting Started
Recommended first step: Download the USGS Magellan GTDR GeoTIFF and test parsing with geotiff.js. Verify elevation sampling against known Venus features like Maxwell Montes (~11km peak) to ensure coordinate transforms are working correctly.

References

Rappaport, N.J. et al.
Magellan Venus Global Topography Data Record
NASA Planetary Data System
(1994)
https://pds-geosciences.wustl.edu/missions/magellan/gxdr/