Skip to content
Larry Edwards edited this page Dec 1, 2018 · 65 revisions

Desktop Exploration of Remote Terrain

Desktop Exploration of Remote Terrain (DERT) is a software tool for exploring large Digital Terrain Models (DTMs) in 3D. It aids in understanding topography and spatial relationships of terrain features, as well as performing simple analysis tasks relevant to the planetary science community.

DERT was developed by the Autonomous Systems and Robotics Area of the Intelligent Systems Division at NASA Ames Research Center. It leverages techniques implemented for science planning support applications provided to a number of NASA missions including Phoenix Mars Lander (PML) and Mars Science Laboratory (MSL).

DERT was funded by the Mars Reconnaissance Orbiter (MRO) mission and developed in collaboration with members of the MRO Context Camera (CTX) science team. DERT is licensed under the NASA Open Source Agreement (NOSA).

DERT constructs a virtual world from a DTM, attempting to stay true to dimension, light, and color. Using a mouse, the user may freely navigate throughout this world, viewing the terrain from any location. In addition to visualization, DERT provides:

  • Measurement tools for distance, slope, area, and volume
  • Artificial and solar light with positioning feature
  • Shadows
  • Multiple orthoimage overlays with adjustable transparency
  • Landmarks
  • Elevation profile
  • Cutting plane with terrain difference map
  • Through-the-lens view from a camera located on the terrain surface
  • Terrain height exaggeration

The term Digital Terrain Model refers to the combination of regularly sampled digital terrain elevation data, a Digital Elevation Model (DEM), with one or more co-registered orthogonally projected digital image overlays, or "ortho-images". Such models are typically generated photogrammetrically from orbital imagery, or directly from orbital lidar and radar altimetry data. Available data sets include those from NASA planetary missions such as Mars Reconnaissance Orbiter (MRO), Mars Global Surveyor (MGS), and Lunar Reconnaissance Orbiter (LRO), as well as those from the Landsat and Shuttle Radar Topography terrestrial missions.

To maintain the interactivity of the virtual world, DERT uses a multi-resolution file structure called a landscape. A landscape is a directory of co-registered layers, each of which contains a tiled pyramid created from the original DTM rasters. This pyramid consists of a quad-tree of tiles representing a raster file. Each branch of the quad-tree contains a tile covering one quarter of the area of its parent and at 4 times the detail. As the user navigates through the world, near tiles are replaced with those of higher resolution while far tiles are replaced with those of less detail. Tile edges are stitched together before rendering. LayerFactory, a companion application, is provided to create landscape layer pyramids from raster files.

Find out more about DERT here and see demonstrations here.

System Requirements

DERT was developed for Mac OS X and Linux platforms provided they meet the following requirements:

  • Mac OS X (El Capitan or later) or Linux Red Hat 6
  • 64 bit Java (1.8 or later)
  • At least 2G of RAM
  • OpenGL 2
  • 3 button mouse (see user guide for Mac trackpad instructions)

Installation

Prebuilt releases are available on the releases tab for this site. Additionally, versions that include the JPL SPICE kernels are available here. These releases are built with the Java 1.8 JDK so the corresponding JRE is required to run them. To install, download the the zip file for your platform and unzip it. You may place the resulting installation directory anywhere but keep its contents intact. See README.txt in this directory for more information.

Install the Geospatial Data Abstraction Library (GDAL) if you plan to build landscapes. This software is very useful for reading file metadata, file alignment, cropping and other data preparation tasks. You can find it here.

Documentation

A user guide is available here and also distributed with the release.

Usage

  • Mac: Double-click on the dert app icon or run the dert script found in the installation directory.
  • Linux: Run the dert script found in the installation directory.

To execute LayerFactory run the layerfactory script found in the installation directory. See the user guide for a description of parameters.

Preferences

There are a number of defaults defined in the dert.properties file. This file is used by both DERT and LayerFactory. Changes to this file require restarting the application. In the Linux distribution, the dert.properties file is located in the installation directory. In the Mac OSX distribution look in dert.app/Contents/Java in the installation directory.

Software Design

DERT is written in Java and uses several third party libraries for rendering, cartographic projection, file access, and lighting. These C libraries are wrapped with the Java Native Interface. See the software design for more information.

DTM Resources

DTMs from the Mars Reconnaissance Orbiter HiRISE instrument can be found here.

NASA Ames Stereo Pipeline (ASP), a suite of tools that can be used to build DTMs from stereo imagery, can be found here.

Additional MRO data sets as well as Lunar Reconnaissance Orbiter (LRO) data sets are at the NASA Planetary Data System Geosciences Node.

SRTM and Landsat data sets can be found at USGS EarthExplorer.

Examples

See examples of how to use DERT here.

Acknowledgements

Original Concept

  • Viz Team, Intelligent Robotics Group, NASA Ames Research Center

Funding

  • Mars Reconnaissance Orbiter Project (MRO)

Advice, Preliminary Testing, and Feedback

  • MRO Context Camera Science Team
  • NASA Intelligent Systems Antares Team
  • NASA Intelligent Systems MapMakers Team

Software Technique Funding

  • Applied Information Systems Research Program (AISRP)
  • Phoenix Mars Lander Project (PML)
  • Mars Reconnaissance Orbiter Project (MRO)
  • Mars Science Laboratory Project (MSL)
  • Lunar Atmosphere and Dust Environment Explorer Project (LADEE)

Software Support Libraries (Open Source)

  • Rendering: Ardor3D, JOGL - Ardor Labs, JogAmp link
  • Lighting: SPICE - NASA Navigation and Ancillary Information Facility (NAIF) link
  • Cartographic Projection: Proj.4 - Gerald Evenden link
  • GeoTIFF File Access: libTIFF - Sam Leffler link