me XXXIX-B8, 2012
e. At the scenarios C and
to ground station. The
obile ground station must
ither in the airplane or by
sed data are directly sent
y ground antennas. In the
d processing stations well
ct downlink of data from
nal transfer times of the
Ns case, a maximum data
sumed.
le airborne rapid mapping
tionary receiving stations
D).
? operation, the crews, the
osts, etc. related to the
nainly independent of the
owing, the costs based on
lake the costs comparable
calculations are based on
erman Aerospace Center,
the costs included are the
e maintenance and other
S of operation per year.
close to Munich as home
area in Hamburg as target
sitions. Further, costs for
| be listed which results in
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
Costs Remark
Aircraft 18k€ 12 flight hours, 3 days,
includes amortisation
Fees 3k€ Flight clearance, airport
fees, etc.
Personnel 3k€ Travel costs, wages,
costs etc.
24k€
Table 4. Costs for airborne monitoring of three coverages in
Hamburg including crews and operators.
4.3 Price calculation
The provider of an airborne rapid mapping service acquires
high resolution georeferenced image data in real time. The
service can be activated by international or national
organizations, e.g. by the International Charter, and should
therefore be comparable to commercial high resolution satellite
scenes in terms of costs, delivery times, etc.
Based on the example Hamburg, three satellite scenes with
highest resolution e.g. Worldview, Quickbird with high priority
cost around 20 to 30k€, i.e. for this example the operational
costs are comparable. More generalized, the airborne
operational costs for providing georeferenced image scenes are
approximately 10€/km?. For economic feasibility, the final
prices for airborne image scenes will be higher to cover the
investment costs (Tab. 4). Thus, the final price will depend
mainly on the desired reaction time and the targeted regions in
terms of the different scenarios A to D.
5. CONCLUSIONS
Different low-cost camera systems for real-time disaster
monitoring are presented and the major differences between
them are clarified. The 3K and 3K-- camera system mounted on
a turboprop-engined aircraft enables the police and other rescue
forces to have a detailed and up-to-date overview of disaster
areas. The CHICAGO camera system has slightly less coverage
but is able to monitor events and other hot spots for a longer
period of time. The processing system, which is closely
connected to the cameras aboard the aircraft, has the advantage
of having direct access to the uncompressed and fully-detailed
images. These large images are handled efficiently with the
help of GPU-accelerated processing and modern image
processing algorithms. The orthorectification and the traffic-
data extraction are fast enough to allow a continuous image
acquisition with a high quality index. Depending on the
mission goals high-resolution orthorectified images and/or
current traffic data can be sent to the ground in real time.
Possible operational scenarios are discussed and differ mainly
in the costs depending on the desired reaction time. The assets
and drawbacks of operational airborne emergency mapping are
discussed in comparison to satellite image acquisition.
In the future, it is planned to design a highly integrated, light-
weight sensor in order to equip other smaller aircrafts with
similar monitoring systems. Moreover, other object recognition
methods are going to be implemented to extend the system's
field of applications, e.g. crowd analysis.
37
6. REFERENCES
Coppinger, R., 2010. Fuel cell motor-glider basis for endurance
UAV. In: Flight International 177 (5233): 25
IGI 2011. Ingenieur Gesellschaft für Interfaces mbH,
http://www.igi.eu (22.12.2011)
Kozempel, K., & Reulke, R., 2009. Camera Orientation Based
on Matching Road Networks. In: Image and Vision Computing
New Zealand, IVCNZ '09. 24th International Conference, 237 —
242,
Kurz, F., 2009. Accuracy assessment of the DLR 3K camera
system. In: DGPF Tagungsband, 18. Jahrestagung 2009.
Kurz, F., Rosenbaum, D., Leitloff, J., Meynberg, O. & Reinartz,
P., 2011. Real-time camera system for disaster and traffic
monitoring. In: Proceedings of International Conference on
SMPR 2011. International Conference on Sensors and Models
in Photogrammetry and Remote Sensing, 18.-19. Mai 2011,
Teheran, Iran.
Kurz, F., Tiirmer, S., Meynberg, O., Rosenbaum, D., Runge, H,,
Reinartz, P. 2012. Low-cost camera system for real-time
applications. In: PFG 2012/2. pp. 157-176.
Leitloff, J., Hinz, S. & Stilla, U., 2010. Vehicle Detection in
Very High Resolution Satellite Images of City Areas. In: IEEE
Transactions on Geoscience and Remote Sensing 48 (7): 2795—
2806.
Rosenbaum, D., Kurz, F., Thomas, U., Suri, S. & Reinartz, P.,
2008. Towards automatic near real-time traffic monitoring with
an airborne wide angle camera system. In: European Transport
Research Review, 1(1):11-12.
Rosenbaum, D, Leitloff, J., Kurz, F., Meynberg, O. & Reize,
T., 2010. Real-Time Image Processing for Road Traffic Data
Extraction from Aerial Images. In: Technical Commission VII
Symposium 2010 - June 2010, Vienna, Austria
Sirmacek, B. & Reinartz, P., 2011. Automatic crowd density
and motion analysis in airborne image sequences based on a
probabilistic framework. In: Proceedings of the 2nd IEEE ICCV
Workshop on Analysis and Retrieval and Tracked Events and
Motion in Imagery Streams (ARTEMIS'11), Nov. 2011,
Barcelona, Spain.
Zhu, K., d'Angelo, P. & Butenuth, M., 2010: Comparison of
Dense Stereo using CUDA. In: / 1" European Conference on
Computer Vision (ECCV) - Crete, Greece.
