Thomas Terzibaschian

Mr. Thomas Terzibaschian

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Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 February 2022 in Journal of Imaging
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Journal Article
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CFChristian Fischer
Christian Fischer
WHWinfried Halle
Winfried Halle
TSThomas Säuberlich
Thomas Säuberlich
OFOlaf Frauenberger
Olaf Frauenberger
MHMaik Hartmann
Maik Hartmann
TTThomas Terzibaschian
Thomas Terzibaschian
Space-borne infrared remote sensing specifically for the detection and characterization of fires has a long history in the DLR Institute of Optical Sensor Systems. In the year 2001, the first DLR experimental satellite, Bi-spectral Infrared Detection (BIRD), was launched after an intensive test period with cooled IR sensor systems on airborne systems. The main basis for the development of the FireBIRD mission with the two satellites, Technology Erprobungsträger No 1 (TET-1) and Bi-spectral-Infrared Optical System (BIROS), was the already space-proven sensor and satellite technology with successfully tested algorithms for fire detection and quantification in the form of the so-called fire radiation power (FRP). This paper summarizes the development principles for the IR sensor system of FireBIRD and the most critical design elements of the TET-1 and BIROS satellites, especially concerning the attitude control system—all very essential tools for high-resolution infrared fire monitoring. Key innovative tools necessary to increase the agility of small IR satellites are discussed.

1 December 2019 in Journal of Space Safety Engineering
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Journal Article
Open access
MHMaren Hülsmann
Maren Hülsmann
RKRalph Kahle
Ralph Kahle
MSManfred Schneller
Manfred Schneller
SASaika Aida
Saika Aida
MHManuel Hahn
Manuel Hahn
WHWinfried Halle
Winfried Halle

7 March 2020
Verified
Book Chapter
Open access
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WHWinfried Halle
Winfried Halle
CFChristian Fischer
Christian Fischer
TTThomas Terzibaschian
Thomas Terzibaschian
AZAdina Zell
Adina Zell
RRRalf Reulke
Ralf Reulke
The release of greenhouse gases and aerosols from fires has a large influence on global climate: on average, fires are responsible for up to 30% of anthropogenic \(CO_2\) emissions. The German Aerospace Center (DLR) is operating the “FireBIRD” constellation, which consists of the two satellite missions TET-1 (Technology Test Platform), and BIROS (Bispectral Infrared Optical System) It is dedicated to scientific investigation of the issues involved as well as to early fire detection from space. The satellite and detector approach is based on proven DLR technology achieved during the BIRD (Bispectral Infrad Detection) Mission, which was launched in 2001 and was primarily used for observation of fires and volcanic activity until 2004.The Payload of TET-1 and BIROS has spectral channels in visible (VIS), near infrared (NIR), mid wave (MIR) and a thermal infrared (TIR) channel. The paper is focused on the processing for TET- and BIROS- Fire- BIRD image data. In the FireBird standard processing chain level 1b and 2a data-products are generated automatically for all users after the data reception on ground. The so called fire-radiative-power (FRP) is one of the most important climate relevant parameters witch is estimated by using the bi-spectral method. Two characteristics of the FireBIRD sensors are unique: first, the high radiometric dynamic sensitivity for quantitative evaluation of normal temperatures and high temperature events (HTE) in the same scene. Second, the evaluation of the effective fire area in square meters independent of the recorded number of fire cluster sizes, which is given as the number of pixels per cluster. For certain users, such as firefighters, it is necessary to obtain fire data products (location and temperature) quickly and with minimal delay after detection. In such applications, data processing must take place directly on board the satellite without using a complex processing chain. The paper describes also an alternative fire-detection algorithm witch uses artificial neural networks (deep learning) and will compare it with the standard Level-2 FireBIRD processing.

1 June 2004 in IFAC Proceedings Volumes
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Journal Article
Closed access
OMOlaf Maibaum
Olaf Maibaum
TTThomas Terzibaschian
Thomas Terzibaschian

1 January 2008
Verified
Book Chapter
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OMOlaf Maibaum
Olaf Maibaum
SMSergio Montenegro
Sergio Montenegro
TTThomas Terzibaschian
Thomas Terzibaschian

28 November 2009
Verified
Book Chapter
Closed access
PDF file
ZYZizung Yoon
Zizung Yoon
TTThomas Terzibaschian
Thomas Terzibaschian
CRChristian Raschke
Christian Raschke
OMOlaf Maibaum
Olaf Maibaum