A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Automated estimation of building height through image processing
Seismic risk is one of the main problems in highly urbanized countries with a considerable seismic hazard like Italy. To assess seismic risk of the built heritage, it is necessary to deepen the knowledge of its components, vulnerability in particular. Vulnerability can be evaluated through mechanical methods, which require detailed information on parameters that may affect the seismic response. The implementation of such methods often results in time-consuming and expensive investigations, thus making the risk assessment analysis very cumbersome. In order to make this process easier and faster, remote sensing algorithms can be taken into consideration. In this work, satellite images of areas of interest are automatically extracted via open source online maps, as well as some preliminary information about the buildings detected in the pictures. Afterwards, a filter is set in order to visualize only targeted building typologies (e.g., residential buildings), and street view images are obtained for each selected building. The images are then processed through feature extraction techniques, in order to predict the number of stories of the buildings. The remote and automated retrieval of this feature, along with other meaningful parameters, could allow the association of a specific vulnerability level for each building, thus making onsite surveys unnecessary, with a remarkable reduction in time and costs.
Automated estimation of building height through image processing
Seismic risk is one of the main problems in highly urbanized countries with a considerable seismic hazard like Italy. To assess seismic risk of the built heritage, it is necessary to deepen the knowledge of its components, vulnerability in particular. Vulnerability can be evaluated through mechanical methods, which require detailed information on parameters that may affect the seismic response. The implementation of such methods often results in time-consuming and expensive investigations, thus making the risk assessment analysis very cumbersome. In order to make this process easier and faster, remote sensing algorithms can be taken into consideration. In this work, satellite images of areas of interest are automatically extracted via open source online maps, as well as some preliminary information about the buildings detected in the pictures. Afterwards, a filter is set in order to visualize only targeted building typologies (e.g., residential buildings), and street view images are obtained for each selected building. The images are then processed through feature extraction techniques, in order to predict the number of stories of the buildings. The remote and automated retrieval of this feature, along with other meaningful parameters, could allow the association of a specific vulnerability level for each building, thus making onsite surveys unnecessary, with a remarkable reduction in time and costs.
Automated estimation of building height through image processing
Carpanese Pietro (author) / Dona Marco (author) / da Porto Francesca (author) / Manolis Papadrakakis, Michalis Fragiadakis / Carpanese, Pietro / Dona, Marco / DA PORTO, Francesca
2021-01-01
Conference paper
Electronic Resource
English
DDC:
720
Building height estimation using Google Earth
| Online Contents | 2016
UPDATING BUILDING MAPS BASED ON OBJECT EXTRACTION AND BUILDING HEIGHT ESTIMATION
| DOAJ | 2012
Performance of Building Height Estimation Using High-Resolution PolInSAR Images
| Online Contents | 2014
Satellite images analysis for shadow detection and building height estimation
| Online Contents | 2016