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NEAR REAL TIME PROCESSING OF DSM FROM AIRBORNE DIGITAL CAMERA
SYSTEM FOR DISASTER MONITORING
F. Kurz*, V. Ebner, D. Rosenbaum, U. Thomas, P. Reinartz
German Aerospace Center (DLR), Remote Sensing Technology Institute, PO Box 1116, D-82230 Weßling, Germany -
franz. kurz@dlr. de
KEY WORDS: Digital Elevation Model, Airborne Optical Camera, Disaster Monitoring, Near Real Time Processing
Knowledge of accurate digital surface models (DSMs) is a valuable information for security authorities and organizations during
emergencies, disasters, or big events. In this context, the potential of the recently developed digital optical camera system (3K) to
non-metric off-the-shelf cameras (Canon EOS 1 Ds Mark II, 16 MPixel), which are aligned in an array with one camera looking in
nadir direction and two in oblique direction. The DSMs are calculated using a subpixel hierarchical matching based on interest
points followed by a region growing algorithm. Exterior orientation is given online by GPS/IMU data, whereas interior camera
parameters are provided in advance. The resulting DSM is calculated by forward intersection. For the validation, the point
accuracies in relation to the base-to-height ratio as well as the reached point density in relation to the calculation time were
calculated. Two flight campaigns with the 3K camera system were performed with varying frame rates over the centre of Munich on
30 th April and on 17 th June 2007. Point accuracies over flat terrain were validated with reference DEMs and correspond quite well to
simulated accuracies. The validation showed that smaller base-to-height ratios decrease the point accuracies but increase point
densities as images are more similar in particular over urban areas. Exemplarily possible applications for near real time DSMs in the
context of disaster monitoring are described, e.g. monitoring of land slides, 3D change detection over urban area, and monitoring of
infrastructure. Problematic in all cases is the long processing time, thus the matching algorithms must be modified or new techniques
must be applied. Some starting points for the reduction of processing times are discussed. In this context, the proposed matching
algorithms and results serve as reference for much faster implementations.
Near real time monitoring of natural disasters, mass events, and
large traffic disasters with airborne SAR and optical sensors
will be the focus of several projects in research and
development at the German Aerospace Center (DLR) in the
next years. For these applications, up-to-date ortho imagery in
combination with digital surface models (DSMs) derived in
near real time is a useful database for different user groups in
the disaster community. One advantage of near real time DSMs
is to provide 3D information to automatic image analysis tools,
e.g. in particular over urban areas 3D information is useful for
building change detection.
In this paper, we will focus on the generation of DSM with a
newly developed digital camera system at DLR: the 3K camera
system (3Kopf=3Head). This camera system broadens the
spectrum of applications and also of the processing algorithms
due to its ability for near real time processing onboard and due
to the high frame rate of 3Hz, e.g. increased overlap in flight
direction lead to more multi-ray points for DSM generation. In
chapter 3 the fully automatic processing flow is described in
more detail and in chapter 4 the camera system and the
algorithms are validated based on several data takes over
Munich. A collection of applications for near real time DSMs in
the context of disaster monitoring is presented in this paper,
which are in detail
Commission IV, WG IV/9
ABSTRACT:
derive DSMs automatically and in near real time will be evaluated. The 3K camera system with a frame rate of 3Hz consists of three
1. INTRODUCTION
• the monitoring of urban areas (3D change detection)
• the monitoring of infrastructure
1.1 Disaster monitoring
• the monitoring of land slides or avalanches
• the determination of building heights
Figure 1 Airborne monitoring and processing system
