Digital elevation extraction from multiple MTI data sets.
- University of Arizona, Tucson, AZ
- NASA Goddard Space Flight Center, Greenbelt, MD
The Digital Elevation Model (DEM) extraction process traditionally uses a stereo pair of aerial photographs that are sequentially captured using an airborne metric camera. Standard DEM extraction techniques have been naturally extended to utilize satellite imagery. However, the particular characteristics of satellite imaging can cause difficulties in the DEM extraction process. The ephemeris of the spacecraft during the collects, with respect to the ground test site, is the most important factor in the elevation extraction process. When the angle of separation between the stereo images is small, the extraction process typically produces measurements with low accuracy. A large angle of separation can cause an excessive number of erroneous points in the output DEM. There is also a possibility of having occluded areas in the images when drastic topographic variation is present, making it impossible to calculate elevation in the blind spots. The use of three or more images registered to the same ground area can potentially reduce these problems and improve the accuracy of the extracted DEM. The pointing capability of the Multispectral Thermal Imager (MTI) allows for multiple collects of the same area to be taken from different perspectives. This functionality of MTI makes it a good candidate for the implementation of DEM extraction using multiple images for improved accuracy. This paper describes a project to evaluate this capability and the algorithms used to extract DEMs from multi-look MTI imagery.
- Research Organization:
- Sandia National Laboratories
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 946985
- Report Number(s):
- SAND2003-2296C
- Country of Publication:
- United States
- Language:
- English
Similar Records
Sub-pixel resolution with the Multispectral Thermal Imager (MTI).
MTI SCIENCE, DATA PRODUCT AND GROUND DATA PROCESSING OVERVIEW