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Leslie Keely edited this page Aug 15, 2016 · 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 simulates the DTM as a virtual world, 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 viewpoint. 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
  • Terrain 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 DERT's interactivity, DTMs must be converted into a multi-resolution file structure called a landscape. A landscape is a directory of co-registered layers, each of which contains a tiled raster pyramid. 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. LayerFactory, a companion application, is provided to create landscape layer pyramids.

DERT creates its virtual world from a landscape. 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.

See videos of DERT here.

###System Requirements

DERT is available for Mac OS X and Linux platforms provided they meet the following requirements:

  • Mac OS X (10.7 or later) or Linux Red Hat 6
  • 64 bit Java (1.7 or later)
  • At least 2G of RAM
  • OpenGL 2
  • 3 button mouse (see user guide for Mac trackpad instructions)

###Installation

Download the latest release for your operating system here and unzip the file. You may place the resulting installation directory anywhere but keep its contents intact. The path to DERT should not contain any spaces. Edit the dert script file to set the Java path and/or change the memory allocation.

DERT may be installed in a central location for multiple users. Put the installation directory in the user's path.

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 with Java 1.7 or later: 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.

###Memory Allocation

The maximum memory allocation for DERT is 2 GB and LayerFactory is set to 8 GB. Java will try to allocate this much virtual memory. The maximum memory can be modified by changing MAX_MEM in the dert and layerfactory scripts.

To change the Mac app, right-click on dert.app, select "Show Package Contents" from the context menu. Open the Contents directory and double-click on Info.plist to edit. Open JVMOptions and change the -Xmx memory option. Save.

###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)

Home

Download

Overview

User Guide

Demos

Examples

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