Submission of proposals
U.S. Army Topographic Engineering Center (TEC)
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| U.S. Army Topographic Engineering Center (TEC)
A00-179 TITLE: Abstraction and Removal of Feature Data to Generate Bare Earth Models from LIght Detection and Ranging (LIDAR) Technologies TECHNOLOGY AREAS: Battlespace OBJECTIVE: To develop improved methodologies and techniques to identify, classify, and remove urban structures, transportation networks, power and communication towers, and vegetation features from high resolution DEMs generated from LIght Detection And Ranging (LIDAR) technologies. DESCRIPTION: LIDAR-topographic-mapping systems have considerable promise for producing high-resolution digital elevation models. The integration of satellite-communications and GPS-navigation systems are critical parts of LIDAR-mapping systems. Many of the available LIDAR sensors can collect ground points at sub-meter spacing which can be processed into a high resolution DEM with a vertical accuracy of 15 cm or less. Many cultural and vegetation features are included at these resolutions and accuracies. There is considerable interest within the Army regarding the utility of high-resolution digital elevation data. The availability of such data has the potential for significant enhancements to the responsiveness, flexibility, and performance of numerous systems and operations PHASE I: The contractor shall evaluate the various component technologies that need to be combined to accurately identify delineate, and separate for removal or export both cultural and vegetation features from high resolution DEMs produced from LIDAR sensors. The various technologies that need to be considered include: 1) establishing terrain editing tools to effectively combine varying resolution DEMs, 2) develop processing filters and utilities to effectively compare and contrast both cultural and vegetation features within the terrain models, 3) and explore the use of airborne imagery to assist in the removal of cultural and vegetation features in developing a bare earth terrain model. The researchers evaluations should preferably include hands-on valuations from multiple LIDAR data sets during the phase I development. PHASE II: Will accumulate the processing capabilities that are defined in Phase I into a prototype system. The prototype system will further develop and apply these emerging processing capabilities to support a broad range of civil engineering and military applications. The utilization of the LIDAR data for these applications will result in the production of end products suitable for execution of civil engineering tasks to providing timely information for military operations. PHASE III: This SBIR would result in a technology with broad applications in the civil community, where LIDAR based mapping is advancing rapidly. This SBIR addresses the research issues associated with the next generation of LIDAR based mapping. It would be of particular interest to local and state governments, as well as the emergency management/disaster relief and environmental communities. REFERENCES: K. Mclintosh, A. Krupnik and T. Schenk, "Registration of airborne laser data to surfaces generated by photogrammetric means", Workshop on "Mapping surface structure and topography by airborne and spaceborne lasers", La Jolla, CA, November 9-11, 1999. D-C. Lee, B. Csatho, and S. Filin, "Analysis of accuracy of airborne laser scanning over urban areas", Workshop on "Mapping surface structure and topography by airborne and spaceborne lasers", La Jolla, CA, November 9-11, 1999. P. Gamba and B. Houshmand, "Integration of high resolution imagery with LIDAR and IFSAR data for urban analysis application", Workshop on "Mapping surface structure and topography by airborne and spaceborne lasers", La Jolla, CA, November 9-11, 1999. C. Toth and D. Grejner-Brzezinska, "Integrating LIDAR with direct digital imagery", Workshop on "Mapping surface structure and topography by airborne and spaceborne lasers", La Jolla, CA, November 9-11, 1999. Eckmullner et al. "Vegetation types, buildings and roads from laser scanner data within a forest enterprise", Workshop on "Mapping surface structure and topography by airborne and spaceborne lasers", La Jolla, CA, November 9-11, 1999. J. Jaafar, G. Priestnall and P. M. Mather, "The effect of grid resolution of Lidar DSMs on the categorizing of residential and industrial areas", Workshop on "Mapping surface structure and topography by airborne and spaceborne lasers", La Jolla, CA, November 9-11, 1999. Z. Wang, and T. Schenk, "Building extraction and reconstruction from Lidar data", Workshop on "Mapping surface structure and topography by airborne and spaceborne lasers", La Jolla, CA, November 9-11, 1999. Carter, Bill. University of Florida, "Airborne Laser Swath Mapping: Digital Terrain Modeling of Marsh Areas", Fifth International Conference on Remeote Sensing for Marine and Coastal Environments, October 1998. Duffy, Mark. National Park Service, "Processing , Integration , and Application of LIDAR Survey Elevation Data in a Local GIS", Coastal GeoTools 1999. Gutierrez, Oskar. University of Texas at Austin, "Airborne Laser Swath Mapping of Galveston Island and Bolivar Peninsula", Fifth International Conference on Remeote Sensing for Marine and Coastal Environments, October 1998. Jansen, Mark. NOAA Coastal Services Center, "Using Airborne Laser Topographic Data to Examine North and South Carloiina Beach Dynamics", Coastal GeoTools, 1999. Wright, Wayne. NASA Wallops Island, "High Resolution Airborne Topographic Mapping LIDAR - Description and Preliminary Results" KEYWORDS: High Resolution and Bare Earth DEM, LIDAR, Feature Removal A00-180 TITLE: Fusing Terrain and Sensor Data During Spectral Feature Extraction TECHNOLOGY AREAS: Battlespace DOD ACQUISITION PROGRAM SUPPORTING THIS PROGRAM: Program Manager, Combat Terrain Information Systems OBJECTIVE: Improve spectral feature extraction by directly fusing terrain and sensor data to increase the depth of the imagery stack. Reduce supervision efforts that train, stratify, label, and adjust spectral feature extraction. Improve rapid mapping, modeling and simulation systems or programs by reducing the cost and time requirements from spectral feature extraction supervision efforts. DESCRIPTION: Spectral feature extraction mathematically sorts separated spatial distributions of brightness values within many stacked imagery bands. Current supervision efforts require inordinate involvement by terrain and spectral analysts to train, stratify, label, and adjust spectral feature extraction. Directly fusing appropriate terrain representations along with data from separate sensors to form a deeper imagery stack should reduce the other already developed but more costly spectral feature extraction supervision efforts. PHASE I: Explore the technical feasibility of directly fusing separate data sources during spectral feature extraction. Find innovative and creative methods of directly fusing terrain representations and data from separate sensors. Develop terrain and sensor data representations, find methods to directly fuse these separate data sources, and apply spectral feature extraction methods and systems to this fused data for rapidly generating or updating the terrestrial environment data of military mobility and concealment models or weapon systems. PHASE II: Use the phase one concepts and technology to directly fuse terrain representations and data from separate sensors during spectral feature extraction for rapid mapping of terrestrial environments. Reduce supervision efforts to train, stratify, label, and adjust spectral feature extraction from directly fusing terrain and sensor data. Show improvements to military mapping, modeling and simulation systems or programs. PHASE III: Add these discovered methods and technology into commercial or government modeling and information systems like the Army Combat Terrain Information Systems that use terrestrial environment data from spectral feature extraction. Extend these methods towards generating terrestrial environment feature data for construction or environmental (pollution, flooding, hurricanes, earthquakes, others) civilian applications. REFERENCES: Roger Brown, Photogrammetric GIS Technology: Feature Mapping on Digital Stereo Imagery, GIS/LIS'91 Proceedings, November 1991. Roger Brown, Combined Terrain and Spectral Reasoning Methods, 1998 ESRI User Conference Proceedings CDROM, (http://www.esri.com/library/userconf/proc98/PROCEED/TO400/PAP387/P387.HTM , http://www.tec.army.mil/news/p387.htm , http://www.browns-place.net/stomp/p387.htm ), July 1998. Charles F. Hutchinson, Techniques for Combining LandSat and Ancillary Data for Digital Classification Improvement, Photogrammetric Engineering and Remote Sensing, January 1982. Bobby Junkins, A Geobased Information System Providing Applications based on LandSat MSS Data, Digital Topographic Terrain Data, and Selected Collateral Data, March 1983, NASA Earth Resources Laboratory Report #219. Thomas M. Lillesand, Ralph W. Kiefer, Remote Sensing and Image Interpretation, 1979, John Wiley & Sons Incorporated. KEYWORDS: Terrain Sensor Imagery Spectral Feature Extraction Army - Download 1.22 Mb. Share with your friends:
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