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IJGI
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Advanced Methodology for Developing an Inventory Database of Human-Made Structures...
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Advanced Methodology for Developing an Inventory Database of Human-Made Structures in Urban Areas for Assessment of Risk and Vulnerability

A special issue of ISPRS International Journal of Geo-Information (ISSN 2220-9964).

Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 16098

Special Issue Editors

Dr. Hiroyuki Miura

E-Mail Website
Guest Editor
Graduate School of Advanced Science and Engineering, Hiroshima University, Higashi-Hiroshima 739-8527, Japan
Interests: earthquake engineering; geospatial analysis for damage assessment; remote sensing for disaster response; DEM analysis for geomorphology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Masashi Matsuoka

E-Mail Website
Guest Editor
Department of Architecture and Building Engineering, Tokyo Institute of Technology, Yokohama 226-8502, Japan
Interests: earthquake engineering; geomorphology; GIS and application of remote sensing technology to disaster management
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Yoshihisa Maruyama

E-Mail Website
Guest Editor
Department of Urban Environment Systems, Chiba University, 1-33 Yayoi-cho, Inage-ku, Chiba, Chiba 263-8522, Japan
Interests: real-time earthquake engineering; urban disaster mitigation; lifeline engineering

Special Issue Information

Dear Colleagues,

Assessment of risk and vulnerability of human-made structures, such as buildings and infrastructures, is an important issue when it comes to taking countermeasures against natural disasters. GIS-based risk and vulnerability analysis can be powerful tools to comprehend the extent and amount of damage expected in scenarios, to support effective disaster mitigation strategies, and to assist early recovery and reconstruction activities.

An inventory database for human-made structures would be crucial for such assessments. GIS inventories have been officially developed by local and national governments in most urban areas. Open-source databases such as OpenStreetMap are now also available online. The existing databases, however, need to be updated to follow recent developments in urban areas in a timely manner if significant discrepancy between the database and the real world is found. Additionally, detailed information, which is required for risk and vulnerability assessment, such as the typical materials of the structure, structural systems, use, and construction year, is not contained in the database. The development of methodologies to effectively construct or update the inventory database and efficiently provide or estimate the attributes for risk assessment are important tasks that must be completed to prepare for coming disasters.

In order to concentrate the knowledge and experiences accumulated thus far, we would like to invite you to submit articles on your recent work. The topics of interest include but are not limited to the following keywords.

Dr. Hiroyuki Miura
Prof. Dr. Masashi Matsuoka
Prof. Dr. Yoshihisa Maruyama
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. ISPRS International Journal of Geo-Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Risk and vulnerability analysis
  • Damage and loss estimation for scenarios
  • Inventory data development for buildings and infrastructures
  • Remote sensing for data generation
  • AI computing for spatial attribute
  • Disaster mitigation planning
  • Spatial data analysis for recovery/reconstruction process
  • Critical infrastructure protection against disasters
  • GIS-based decision support systems for risk analysis, emergency management, scenario simulations
  • Resilience enhancement strategies

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Published Papers (4 papers)

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Research

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38 pages, 18333 KiB  
Article
Towards a Sensitivity Analysis in Seismic Risk with Probabilistic Building Exposure Models: An Application in Valparaíso, Chile Using Ancillary Open-Source Data and Parametric Ground Motions
by Juan Camilo Gómez Zapata, Raquel Zafrir, Massimiliano Pittore and Yvonne Merino
ISPRS Int. J. Geo-Inf. 2022, 11(2), 113; https://doi.org/10.3390/ijgi11020113 - 6 Feb 2022
Cited by 6 | Viewed by 3371
Abstract
Efforts have been made in the past to enhance building exposure models on a regional scale with increasing spatial resolutions by integrating different data sources. This work follows a similar path and focuses on the downscaling of the existing SARA exposure model that [...] Read more.
Efforts have been made in the past to enhance building exposure models on a regional scale with increasing spatial resolutions by integrating different data sources. This work follows a similar path and focuses on the downscaling of the existing SARA exposure model that was proposed for the residential building stock of the communes of Valparaíso and Viña del Mar (Chile). Although this model allowed great progress in harmonising building classes and characterising their differential physical vulnerabilities, it is now outdated, and in any case, it is spatially aggregated over large administrative units. Hence, to more accurately consider the impact of future earthquakes on these cities, it is necessary to employ more reliable exposure models. For such a purpose, we propose updating this existing model through a Bayesian approach by integrating ancillary data that has been made increasingly available from Volunteering Geo-Information (VGI) activities. Its spatial representation is also optimised in higher resolution aggregation units that avoid the inconvenience of having incomplete building-by-building footprints. A worst-case earthquake scenario is presented to calculate direct economic losses and highlight the degree of uncertainty imposed by exposure models in comparison with other parameters used to generate the seismic ground motions within a sensitivity analysis. This example study shows the great potential of using increasingly available VGI to update worldwide building exposure models as well as its importance in scenario-based seismic risk assessment. Full article
(This article belongs to the Special Issue Advanced Methodology for Developing an Inventory Database of Human-Made Structures in Urban Areas for Assessment of Risk and Vulnerability)
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22 pages, 16666 KiB  
Article
Development of Building Inventory Data in Ulaanbaatar, Mongolia for Seismic Loss Estimation
by Zorigt Tumurbaatar, Hiroyuki Miura and Tsoggerel Tsamba
ISPRS Int. J. Geo-Inf. 2022, 11(1), 26; https://doi.org/10.3390/ijgi11010026 - 30 Dec 2021
Cited by 2 | Viewed by 4863
Abstract
During the last two decades, the rapid urbanization movement has increased the concentration of population and buildings in Ulaanbaatar city (UB), Mongolia. There are several active faults around UB. The estimated maximum magnitude of 7 in the Emeelt fault has been expected to [...] Read more.
During the last two decades, the rapid urbanization movement has increased the concentration of population and buildings in Ulaanbaatar city (UB), Mongolia. There are several active faults around UB. The estimated maximum magnitude of 7 in the Emeelt fault has been expected to significantly impact the UB region because the fault is only 20 km from the city. To consider the disaster mitigation planning for such large earthquakes, assessments of ground shaking intensities and building damage for the scenarios are crucial. In this study, we develop the building inventory data in UB, including structural types, construction year, height, and construction cost in order to assess the buildings’ vulnerability (repair cost) due to a scenario earthquake. The construction costs are estimated based on the procedure of the Mongolian construction code from the coefficients of cost per floor area for each structural type, and coefficients for heating system, floor areas, and buildings’ locations. Finally, the scenario’s economic loss of the damaged buildings is evaluated using the developed building inventory, global vulnerability curves of GAR-13, and estimated spectral accelerations. Full article
(This article belongs to the Special Issue Advanced Methodology for Developing an Inventory Database of Human-Made Structures in Urban Areas for Assessment of Risk and Vulnerability)
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15 pages, 1822 KiB  
Article
Simultaneous Extraction of Road and Centerline from Aerial Images Using a Deep Convolutional Neural Network
by Tamara Alshaikhli, Wen Liu and Yoshihisa Maruyama
ISPRS Int. J. Geo-Inf. 2021, 10(3), 147; https://doi.org/10.3390/ijgi10030147 - 8 Mar 2021
Cited by 7 | Viewed by 2332
Abstract
The extraction of roads and centerlines from aerial imagery is considered an important topic because it contributes to different fields, such as urban planning, transportation engineering, and disaster mitigation. Many researchers have studied this topic as a two-separated task that affects the quality [...] Read more.
The extraction of roads and centerlines from aerial imagery is considered an important topic because it contributes to different fields, such as urban planning, transportation engineering, and disaster mitigation. Many researchers have studied this topic as a two-separated task that affects the quality of extracted roads and centerlines because of the correlation between these two tasks. Accurate road extraction enhances accurate centerline extraction if these two tasks are processed simultaneously. This study proposes a multitask learning scheme using a gated deep convolutional neural network (DCNN) to extract roads and centerlines simultaneously. The DCNN is composed of one encoder and two decoders implemented on the U-Net backbone. The decoders are assigned to extract roads and centerlines from low-resolution feature maps. Before extraction, the images are processed within an encoder to extract the spatial information from a complex, high-resolution image. The encoder consists of the residual blocks (Res-Block) connected to a bridge represented by a Res-Block, and the bridge connects the two identical decoders, which consists of stacking convolutional layers (Conv.layer). Attention gates (AGs) are added to our model to enhance the selection process for the true pixels that represent road or centerline classes. Our model is trained on a dataset of high-resolution aerial images, which is open to the public. The model succeeds in efficiently extracting roads and centerlines compared with other multitask learning models. Full article
(This article belongs to the Special Issue Advanced Methodology for Developing an Inventory Database of Human-Made Structures in Urban Areas for Assessment of Risk and Vulnerability)
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Review

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38 pages, 16325 KiB  
Review
What Would Happen If the M 7.3 (1721) and M 7.4 (1780) Historical Earthquakes of Tabriz City (NW Iran) Occurred Again in 2021?
by Mohammad Ghasemi, Sadra Karimzadeh, Masashi Matsuoka and Bakhtiar Feizizadeh
ISPRS Int. J. Geo-Inf. 2021, 10(10), 657; https://doi.org/10.3390/ijgi10100657 - 30 Sep 2021
Cited by 5 | Viewed by 4542
Abstract
Tabriz is located in the northwest of Iran. Two huge earthquakes with magnitudes of 7.4 and 7.3 occurred there in 1780 and 1721. These earthquakes caused considerable damage and casualties in Tabriz. Using the method of scenario building, we aim to investigate what [...] Read more.
Tabriz is located in the northwest of Iran. Two huge earthquakes with magnitudes of 7.4 and 7.3 occurred there in 1780 and 1721. These earthquakes caused considerable damage and casualties in Tabriz. Using the method of scenario building, we aim to investigate what would happen if such earthquakes occurred in 2021. This scenario building was carried out using deterministic and GIS-oriented techniques to find the levels of damage and casualties that would occur. This procedure included two steps. In the first step, a database of factors affecting the destructive power of earthquakes was prepared. In the next step, hierarchical analysis was used to weigh the data, and then the weighted data were combined with an earthquake intensity map. The obtained results were used to predict the earthquake intensity in Tabriz. According to our results, the earthquake with a magnitude of 7.3 that occurred in 1721 caused huge destruction in the north of Tabriz, as this earthquake occurred inside the site. However, this earthquake caused minimal damage to the south of the city owing to the geological situation of this area of Tabriz. The earthquake with a magnitude of 7.3 that occurred in 1780 caused less damage because of its distance from the site. In the third step of this analysis, the vulnerability of buildings and the population were examined. According to the estimates, District 4 would experience the highest damage rate in the earthquake of 1721, with 15,477 buildings destroyed, while this area would have a lower damage rate in the earthquake that occurred in 1780. The total casualties in Tabriz would number 152,092 and 505 people in the earthquakes of 1721 and 1780, respectively. Full article
(This article belongs to the Special Issue Advanced Methodology for Developing an Inventory Database of Human-Made Structures in Urban Areas for Assessment of Risk and Vulnerability)
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