Christian Strobl

Dr. Christian Strobl


Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

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29 October 2013 in Remote Sensing
Verified
Journal Article
Open access
PDF file
SMSandro Martinis
Sandro Martinis
ATAndré Twele
André Twele
CSChristian Strobl
Christian Strobl
JKJens Kersten
Jens Kersten
ESEnrico Stein
Enrico Stein
A two-component fully automated flood monitoring system is described and evaluated. This is a result of combining two individual flood services that are currently under development at DLR’s (German Aerospace Center) Center for Satellite based Crisis Information (ZKI) to rapidly support disaster management activities. A first-phase monitoring component of the system systematically detects potential flood events on a continental scale using daily-acquired medium spatial resolution optical data from the Moderate Resolution Imaging Spectroradiometer (MODIS). A threshold set controls the activation of the second-phase crisis component of the system, which derives flood information at higher spatial detail using a Synthetic Aperture Radar (SAR) based satellite mission (TerraSAR-X). The proposed activation procedure finds use in the identification of flood situations in different spatial resolutions and in the time-critical and on demand programming of SAR satellite acquisitions at an early stage of an evolving flood situation. The automated processing chains of the MODIS (MFS) and the TerraSAR-X Flood Service (TFS) include data pre-processing, the computation and adaptation of global auxiliary data, thematic classification, and the subsequent dissemination of flood maps using an interactive web-client. The system is operationally demonstrated and evaluated via the monitoring two recent flood events in Russia 2013 and Albania/Montenegro 2013.

15 January 2010
Verified
Book Chapter
Closed access
PDF file
URUlrich Raape
Ulrich Raape
STSven Teßmann
Sven Teßmann
AWAndreas Wytzisk
Andreas Wytzisk
TSTilmann Steinmetz
Tilmann Steinmetz
MWMonika Wnuk
Monika Wnuk
SJSimon Jirka
Simon Jirka

1 January 2011
Verified
Book Chapter
Open access
PDF file
RVRanga R. Vatsavai
Ranga R. Vatsavai
TBThomas E. Burk
Thomas E. Burk
SLSteve Lime
Steve Lime
MHMarco Hugentobler
Marco Hugentobler
ANAndreas Neumann
Andreas Neumann
CSChristian Strobl
Christian Strobl
The components making upan Open Source GIS are explained in this chapter. A map server (Sect. 30.1 ) can broadly be defined as a software platform for dynamically generating spatially referenced digital map products. The University of Minnesota MapServer (UMN Map Server) is one such system. Its basic features are visualization, overlay, and query. Section 30.2 names and explains many of the geospatial open source libraries, such as GDAL and OGR. The other libraries are FDO, JTS, GEOS, JCS, MetaCRS, and GPSBabel. The application examples include derived GIS-software and data format conversions. Quantum GIS, its origin and its applications explained in detail in Sect. 30.3 . The features include a rich GUI, attribute tables, vector symbols, labeling, editing functions, projections, georeferencing, GPS support, analysis, and Web Map Server functionality. Future developments will address mobile applications, 3-D, and multithreading. The origins of PostgreSQL are outlined and PostGIS discussed in detail in Sect. 30.4 . It extends PostgreSQL by implementing the Simple Feature standard. Section 30.5 details the most important open source licenses such as the GPL, the LGPL, the MIT License, and the BSD License, as well as the role of the Creative Commons.

29 April 2015 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Verified
Journal Article
Open access
PDF file
EFE.-M. Fuchs
E.-M. Fuchs
ESE. Stein
E. Stein
GSGuenter Strunz
Guenter Strunz
CSChristian Strobl
Christian Strobl
CFCorinne Frey
Corinne Frey
Keywords: Fires, Hot Spot Detection, Burnt Area Mapping, Prediction/Early Warning, Time Series, Decision Support Service This paper introduces fire monitoring works of two different projects, namely TIMELINE (TIMe Series Processing of Medium Resolution Earth Observation Data assessing Long –Term Dynamics In our Natural Environment) and PHAROS (Project on a Multi-Hazard Open Platform for Satellite Based Downstream Services). It describes the evolution from algorithm development from in applied research to the implementation in user driven applications and systems. Concerning TIMELINE, the focus of the work lies on hot spot detection. A detailed description of the choice of a suitable algorithm (round robin approach) will be given. Moreover, strengths and weaknesses of the AVHRR sensor for hot spot detection, a literature review, the study areas and the selected approach will be highlighted. The evaluation showed that the contextual algorithm performed best, and will therefore be used for final implementation. Concerning the PHAROS project, the key aspect is on the use of satellite-based information to provide valuable support to all phases of disaster management. The project focuses on developing a pre-operational sustainable service platform that integrates space-based EO (Earth Observation), terrestrial sensors and communication and navigation assets to enhance the availability of services and products following a multi-hazard approach.

22 June 2015
Verified
Conference Paper
Open access
CSChristian Strobl
Christian Strobl
ESEnrico Stein
Enrico Stein
PPPatrick Aravena Pelizari
Patrick Aravena Pelizari
URUlrich Raape
Ulrich Raape
PTPadsuren Tungalagsaikhan
Padsuren Tungalagsaikhan
TRThomas Ruppert
Thomas Ruppert
The project PHAROS (Project on a Multi-Hazard Open Platform for Satellite Based Downstream Services) designs and implements a multi-hazard open service platform which integrates space-based earth observation, satellite communications and navigation (Galileo/GNSS) assets to provide sustainable (pre-operational) services for a wide variety of users in multi-application domains, such as prediction/early detection of emergencies, population alerting, environmental monitoring and crisis management. While the service platform is designed to be multi-hazard, the specific developments for the pre-operational system and pilot demonstration will be focused on the forest fire scenario. The platform will integrate data from EO satellites and in-situ sensors process it and provide the results to a series of key services for disaster management in its different phases. One of the main concerns is to provide fire hot spots as an input for the PHAROS Simulation Service. These fire hot spots (thermal anomalies) are derived automatically and in near real time (NRT) from MODIS data. The MODIS data are available in a high (1d) temporal and in a medium (250m – 1000m) spatial resolution. For the detection of high temperature events (HTE) the MOD14 algorithm is used. The algorithm is based on the shift of the radiances/reflectance to shorter wavelengths (middle infrared) with an increasing surface temperature. MOD14 is well documented and tested in operational services and guarantees comparability and reproducibility as well as a standardized international acknowledged product. The thermal information is collected at 1000 m spatial resolution twice daily by each sensor (Terra and Aqua) providing up to four thermal observations daily. The MODIS images used for fire detection are acquired from two direct broadcast receiving stations from DLR located in Oberpfaffenhofen and Neustrelitz (Germany). This Poster will give an overview of the processing chain from the reception, the processing and derivation of the fire hot spots to the dissemination in the Pharos system.