Use of High Quality UAV Based Data to Correct Satellite Derived DEMs

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-02-M-0254
Agency Tracking Number: N02-077-03
Amount: $70,000.00
Phase: Phase I
Program: SBIR
Awards Year: 2002
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
P.O. Box 6024, Sherman Oaks, CA, 91413
DUNS: 082191198
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 John Dugan
 Arete Fellow
 (703) 413-0290
 dugan@arete-dc.com
Business Contact
 Philip Selwyn
Title: Vice President
Phone: (703) 413-0290
Email: selwyn@arete-dc.com
Research Institution
N/A
Abstract
"The goal of this SBIR proposal is to develop and demonstrate a technique for improving the accuracy of DEMs generated from satellite imagery by using appropriate airborne imagery. It is anticipated that the positioning and pointing capabilities of futureUAVs will provide much more accurate geo-location of features on the ground than satellite systems and they, therefore, can provide the surrogate "ground truth" for correcting satellite data that has much larger area coverage. The algorithm will bedeveloped and exercised using IKONOS satellite-derived DEMs in combination with imagery data from the Arete Associates developed Airborne Remote Optical Spotlight System (AROSS), which a field-tested and robust EO system designed for research on tacticalUAV applications such as this one. In Phase 1, we will develop the algorithm for extracting highly accurate 3-D geodetic coordinates for multiple images collected from this UAV surrogate and develop the algorithm that uses these results to correct thesatellite data. In addition, we will evaluate the approach by applying the correction algorithm to an IKONOS imagery-derived DEM, using AROSS data and in situ ground truth collected during a recent experiment. Assuming success, phase 2 will developrobust software to automatically make these corrections of satellite data using UAV data, and perform a more complete evaluation of the accuracy on a much larger data set. Phase I will develop enha

* Information listed above is at the time of submission. *

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