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Proceedings Paper

Aviation obstacle auto-extraction using remote sensing information
Author(s): N. Zimmer; W. Lugsch; D. Ravenscroft; J. Schiefele
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Paper Abstract

An Obstacle, in the aviation context, may be any natural, man-made, fixed or movable object, permanent or temporary. Currently, the most common way to detect relevant aviation obstacles from an aircraft or helicopter for navigation purposes and collision avoidance is the use of merged infrared and synthetic information of obstacle data. Several algorithms have been established to utilize synthetic and infrared images to generate obstacle information. There might be a situation however where the system is error-prone and may not be able to consistently determine the current environment. This situation can be avoided when the system knows the true position of the obstacle. The quality characteristics of the obstacle data strongly depends on the quality of the source data such as maps and official publications. In some countries such as newly industrializing and developing countries, quality and quantity of obstacle information is not available. The aviation world has two specifications - RTCA DO-276A and ICAO ANNEX 15 Ch. 10 - which describe the requirements for aviation obstacles. It is essential to meet these requirements to be compliant with the specifications and to support systems based on these specifications, e.g. 3D obstacle warning systems where accurate coordinates based on WGS-84 is a necessity. Existing aerial and satellite or soon to exist high quality remote sensing data makes it feasible to think about automated aviation obstacle data origination. This paper will describe the feasibility to auto-extract aviation obstacles from remote sensing data considering limitations of image and extraction technologies. Quality parameters and possible resolution of auto-extracted obstacle data will be discussed and presented.

Paper Details

Date Published: 13 October 2008
PDF: 13 pages
Proc. SPIE 7110, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII, 71101C (13 October 2008); doi: 10.1117/12.799791
Show Author Affiliations
N. Zimmer, Jeppesen GmbH (Germany)
W. Lugsch, Jeppesen (United States)
D. Ravenscroft, Jeppesen (United States)
J. Schiefele, Jeppesen GmbH (Germany)


Published in SPIE Proceedings Vol. 7110:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII
Ulrich Michel; Daniel L. Civco; Manfred Ehlers; Hermann J. Kaufmann, Editor(s)

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