Mr. Nico Zimmer Profile

Nico Zimmer

Research Engineer at Jeppesen GmbH

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Proceedings Article | 13 October 2008 Paper

Aviation obstacle auto-extraction using remote sensing information

W. Lugsch, D. Ravenscroft, N. Zimmer, J. Schiefele

Proceedings Volume 7110, 71101C (2008) https://doi.org/10.1117/12.799791

KEYWORDS: Satellites, Feature extraction, Remote sensing, Satellite imaging, Image processing, Earth observing sensors, Databases, Image segmentation, Radar, Airborne remote sensing

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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.

Proceedings Article | 29 October 2007 Paper

Synthetic generation of airport familiarization using geo information systems

P. Wipplinger, J. Schiefele, N. Zimmer

Proceedings Volume 6749, 67491X (2007) https://doi.org/10.1117/12.737068

KEYWORDS: Video, Geographic information systems, Data modeling, Satellite imaging, Earth observing sensors, Satellites, 3D modeling, Remote sensing, Buildings, Cameras

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An Airport Qualification may be required for a pilot to receive qualification for the execution of an approach or departure from a terrain, weather, or procedure challenging airport. The FAA identified these challenging airports and calls them "Special Pilot Qualification Airports". This Qualification may be accomplished through a familiarization using airport images or through a familiarization flight with an authorized person. Currently, Jeppesen offers Airport Familiarization Charts. These charts depict approach procedure photos to a runway from the pilot's perspective and aerial views of the airport. Before the approach, Pilots make use of these photos to get familiarized with the airport, the runway layout, the approach and terrain. Jeppesen qualification charts cover all FAA identified airports and other challenging airports. A first prototype for generating "Synthetic Airport Familiarization" pictures and videos has been researched, developed, implemented and validated. Flight Information Data as well as Remote Sensing Data and their derived data was processed and visualized through Geo Information System (GIS). This paper describes a new possibility to generate airport familiarization images using Remote Sensing Data, terrain data, airport vector data, obstacles and approach procedure data through GIS. The objective is to replace analogues photos with synthetic pictures and also to generate new Airport Familiarization Videos. Finally, an overview of the potential feature extensibility of the Synthetic Airport Familiarization System is presented.

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