An OGC SensorThings GIS Pipeline For Estimating Seismic Engineering Demand Parameters

Abstract. Estimating the losses in the immediate aftermath of an earthquake is a key component of seismic response. Seismic rapid-loss estimates provide first responders with a prediction of where and what to prepare for. Improving the precision of quick loss estimates requires an estimate of how a buildings in the affected zone may have reacted to an event. Structural response prediction models are a novel approach to estimating building response from the observed displacement of instrumented buildings. Current SRPMs are built on relatively small databases but offer potential for expansion. There exists no robust building-specific database which could facilitate the construction of these models. As a reaction to this gap, this study applies, abstractly and concretely, the OGC SensorThings data model to building seismograph records. The harmonized records form part of a proposed abstract and concrete Structural Response Prediction Model to make estimates of building-response on other un-instrumented buildings. The utility of a abstracted observation data-model and pipeline is shown, with the potential for unifying existing data-sources. The work shall show that the OGC SensorThings integrates generally well, with some limitations, with the requirements of seismic observation record keeping.

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Publication Details

Journal
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Published
2025-07-12
DOI
https://doi.org/10.5194/isprs-annals-x-g-2025-787-2025
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
0.00

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article

An OGC SensorThings GIS Pipeline For Estimating Seismic Engineering Demand Parameters

Peter van Oosterom, Azarakhsh Rafiee, Justin Schembri
ISPRS annals of the photogrammetry, remote sensing and spatial information sciences
Reservoir Engineering and Simulation Methods
article

An OGC SensorThings GIS Pipeline For Estimating Seismic Engineering Demand Parameters

Peter van Oosterom, Azarakhsh Rafiee, Justin Schembri
article en

Abstract

Abstract. Estimating the losses in the immediate aftermath of an earthquake is a key component of seismic response. Seismic rapid-loss estimates provide first responders with a prediction of where and what to prepare for. Improving the precision of quick loss estimates requires an estimate of how a buildings in the affected zone may have reacted to an event. Structural response prediction models are a novel approach to estimating building response from the observed displacement of instrumented buildings. Current SRPMs are built on relatively small databases but offer potential for expansion. There exists no robust building-specific database which could facilitate the construction of these models. As a reaction to this gap, this study applies, abstractly and concretely, the OGC SensorThings data model to building seismograph records. The harmonized records form part of a proposed abstract and concrete Structural Response Prediction Model to make estimates of building-response on other un-instrumented buildings. The utility of a abstracted observation data-model and pipeline is shown, with the potential for unifying existing data-sources. The work shall show that the OGC SensorThings integrates generally well, with some limitations, with the requirements of seismic observation record keeping.

ISPRS annals of the photogrammetry, remote sensing and spatial information sciencesVol. X-G-2025
Delft University of Technology (NL)
European Commission, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 79%
Reservoir Engineering and Simulation Methods
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