Understanding Terrain and Scenery Data for Airport Simulation

Simulating diverse global airports demands precise terrain and scenery data to replicate real-world conditions. Terrain data captures the physical shape of the land—elevation, slopes, and surface characteristics—while scenery data adds the visible features: runways, taxiways, buildings, vegetation, lighting, and ground markings. Together, these datasets form the foundation of an immersive virtual airport environment, essential for pilot training, entertainment, and aviation education.

Types of Terrain Data

Terrain data comes in several forms, each serving a specific role in simulation:

  • Digital Elevation Models (DEMs): Grid-based representations of ground elevation. Common sources include SRTM (Shuttle Radar Topography Mission) at 30-meter resolution and ASTER GDEM at 15 meters. Higher-resolution LiDAR DEMs can achieve sub-meter accuracy but cover limited areas.
  • Orthoimagery: Georeferenced satellite or aerial photographs that provide realistic surface textures. Providers like USGS EarthExplorer offer Landsat imagery (15–30 m), while commercial sources deliver resolution down to 0.3 m.
  • Vector Data: Discrete features such as roads, buildings, water bodies, and vegetation polygons. OpenStreetMap is a prime global source for such data, often integrated into simulation scenery.

Components of Scenery Data

Scenery data builds the visual context around the airport. Key elements include:

  • Airport Layout: Precise runways, taxiways, aprons, and helipads—often sourced from ICAO or FAA databases.
  • Structures: Terminal buildings, hangars, control towers, and cargo facilities. These may be modeled from blueprints or photogrammetry.
  • Ground Markings and Lighting: Runway markings, approach lights, taxiway signage, and PAPI systems.
  • Vegetation and Land Coverage: Trees, grass, crops, and bare soil—essential for regional authenticity.

Sources of Accurate Data

Gathering reliable data is the critical first step. Below are trusted sources for terrain and scenery information:

  • SRTM (Shuttle Radar Topography Mission): Provides near-global elevation data with 30-meter resolution. Versions 2.1 and 3.0 are widely used in flight simulation.
  • ASTER GDEM: A product of METI and NASA, offering 15-meter resolution DEMs for most of the globe.
  • OpenStreetMap (OSM): A community-driven vector dataset encompassing roads, buildings, waterways, and land use. Many simulation tools directly import OSM data for autogen scenery.
  • Satellite Imagery: Landsat (free, 15–30 m), Sentinel-2 (free, 10 m), and commercial providers (Maxar, Airbus) for high-resolution ortho textures.
  • Official Airport Data: FAA Airport Data (5010) and ICAO Aerodrome Reference Codes provide runway dimensions, elevations, and facility details.
  • LiDAR Datasets: Available through national geological surveys (e.g., USGS 3DEP) for sub-meter elevation accuracy.

Data Processing and Conversion

Raw data must be processed to meet the specifications of your simulation platform. This involves several technical steps:

Reprojection and Georeferencing

Terrain and imagery from different sources use varying coordinate systems (e.g., WGS84, UTM). Tools like GDAL and QGIS reproject data into a common geographic coordinate system—typically WGS84 for flight simulation.

Mosaicking and Blending

Multiple DEM tiles or satellite images are merged into a seamless composite. Color balancing and feathering reduce visible seams at tile boundaries.

Resampling and Resolution Adjustment

Simulators have practical limits on texture resolution and polygon counts. Downsampling DEMs to match a platform’s effective detail distance (e.g., LOD thresholds) prevents performance degradation.

Format Conversion

Simulators use proprietary formats. For example, Microsoft Flight Simulator 2020 uses photo tiles (JPG/DDS) and elevation files in BGL format. X-Plane uses base mesh (DSF/OBJ) and terrain (DDS/PNG) files. Tools like World Editor (WED), Airport Design Editor (ADE), and Ortho4XP automate conversion for specific platforms.

Integrating Data into Simulation Platforms

Each major flight simulator has its own workflow for importing custom terrain and scenery.

Microsoft Flight Simulator (2020/2024)

MSFS uses a worldwide photogrammetric core but allows local replacements. Developers can create “Packages” containing elevation and imagery for specific areas using the SDK. The World Map Editor (WME) lets users define airport boundaries and add custom objects. External tools like Blender with the MSFS plugin enable 3D model import.

X-Plane (11/12)

X-Plane’s scenery system relies on base mesh (DSF) and overlays. Ortho4XP generates orthophoto tiles and corresponding DSF meshes from DEM and imagery. The Laminar Research Gateway allows community airport submissions. For manual editing, World Editor (WED) and SketchUp with X-Plane exporters are standard.

Prepar3D

Prepar3D uses the same BGL infrastructure as FSX. Airport Design Editor (ADE) handles airport layouts, while SBUILDER manages terrain elevation and photoreal ground. Custom 3D models are created in 3DS Max or Blender with the P3D SDK.

Steps for Creating Diverse Airport Environments

1. Research and Gather Data

Identify the target airport and its unique features. Collect source materials: DEMs from USGS or Copernicus, orthoimagery from Sentinel Hub, vector data from OpenStreetMap, and official airport diagrams from the FAA or Jeppesen. Note any special requirements such as seasonal vegetation or complex taxiway networks.

2. Process and Convert Data

Use GIS software (QGIS, Global Mapper) to hillshade DEMs, clip areas of interest, and merge multiple tiles. For imagery, apply atmospheric correction and color balance. Convert elevation data into the simulator’s required format (e.g., ASCII to DSF, or TIFF to BGL). Tools like GDAL scripts can automate batch conversion.

3. Design and Customize Scenery

Model airport-specific buildings and objects using 3D software, ensuring polygon counts are reasonable for real-time rendering. Add ground textures from real satellite imagery or custom painted markings. Place lighting arrays, windsocks, and navigation aids according to real-world positions. Leverage automated scenery generation tools (e.g., World Traffic for moving vehicles) to bring the airport to life.

4. Test and Refine

Load the scenery into the simulator and perform test runs. Check for elevation mismatches—aircraft sinking into runways or hovering above ground—and correct using elevation offset tools. Verify taxiway alignments and sign placement. Use top-down views (like Google Earth overlays) to ensure buildings match real footprints. Iterate based on visual discrepancies.

Challenges and Solutions

Creating accurate airport simulations involves several common obstacles:

  • Data Inconsistency: Elevation data may have voids or spikes. Solution: Use multiple DEM sources and fill gaps with interpolation (e.g., using GDAL’s fill nodata).
  • Imagery Color Imbalances: Seasonal or cloud-free mosaics can look unnatural. Solution: Apply histogram matching and manual color grading in photo editing software.
  • Performance vs. Detail Trade-offs: Ultra-high-resolution textures and complex 3D models cause slowdowns. Solution: Implement Level of Detail (LOD) variations and use efficient texture formats (DXT compression).
  • Runway and Taxiway Elevation: Airports often sit on level ground, but terrain data may show unnatural bumps. Solution: Flatten terrain using “exclusion rectangles” or mesh editing to enforce smooth surfaces.
  • Vegetation Placement: Automated tree generation can place trees on runways. Solution: Create exclusion zones in the scenery configuration.

Benefits of Accurate Simulation

Precise terrain and scenery data produce dramatic improvements in realism, with tangible benefits across user groups:

  • Pilot Training: Realistic airport environments help pilots practice approaches, taxiing, and ground operations in VFR/IFR conditions. Accurate elevation ensures true performance handling for takeoff and landing.
  • Hobbyists: Enthusiasts gain deep immersion—flying into airports that look and feel like their real counterparts, with appropriate landmarks and terrain contours.
  • Education: Aviation geography students study airport design, obstacle clearance, and terrain influences on flight paths.
  • Developer Portfolio: Providing diverse, high-quality airport scenery builds reputation within the simulation community and may lead to professional opportunities.

The field is rapidly evolving. Key trends to watch:

  • Real-Time Data Streaming: Servers delivering live weather, wind, and even real-time air traffic could also stream updated terrain correction data for dynamic airport conditions.
  • Procedural Generation with AI: Machine learning algorithms can autofill building facades, vegetation, and ground markings based on satellite imagery, reducing manual work.
  • Full Photogrammetry Integration: As simulators support higher fidelity, entire airports will be scanned via drone photogrammetry and directly imported as point clouds or mesh.
  • Open-Source Collaboration: Projects like the FlightGear scenery model and community portals (e.g., Flightsim.to) encourage shared, high-quality data.

By embracing these data sources and workflows, developers can create airport environments that are not only visually stunning but also functionally accurate—supporting everything from casual virtual flights to rigorous professional training. Accurate terrain and scenery data turn a simple game into a powerful simulation tool.