3D city model for monitoring flash flood risks in Salalah, Oman

Kalbani, Khalid Al

doi:10.26833/ijeg.857971

Cited by 11 publications

(8 citation statements)

References 25 publications

(24 reference statements)

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“…The use of the GIS-based model in the present study facilitates the collection, understanding, and assessment of spatial and physical features that influence the vulnerability of places. Moreover, the digital model can be easily implemented with parametric ones aiming at structuring thematic platforms for managing technical data and planning [71], monitoring of effects of natural phenomena [72,73], and setting up a digitalized environment for risk communication and promotion of mitigative solutions [69,74], encouraging collaborative strategies [75].…”

Section: Discussionmentioning

confidence: 99%

Mapping the Multi-Vulnerabilities of Outdoor Places to Enhance the Resilience of Historic Urban Districts: The Case of the Apulian Region Exposed to Slow and Rapid-Onset Disasters

Cantatore,

Esposito,

Sonnessa

2023

Sustainability

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Recent critical events brought attention to the increasing exposure of urban environments to both slow and rapid onset disasters, which arise from both anthropogenic and natural causes. These events have particularly severe effects on historic centres, which are characterized by high levels of vulnerability and valuable assets exposed to risk. To minimize the impact on tangible and intangible cultural heritage values, especially in outdoor public areas such as squares and streets, it is crucial to establish coherent mitigative and adaptive solutions for different types of hazards. This research presents a methodology aimed at defining levels of multi-vulnerabilities in historic districts in the Apulia Region (Italy), considering the recurrent hazards to which the latter is prone. It uses a multi-step process based on structured and non-structured methodologies and tools for single risks, examined in combination, to determine the main properties characterizing the vulnerability assessment. The dataset was analyzed in a GIS environment to evaluate the selected Apulian case study (Molfetta) in Multi-Asynchronous Hazard scenarios, showing the compounded levels of criticalities for open areas and streets. This information is intended to support authority and emergency managers in identifying priority interventions and increasing the resilience of the outdoor public places.

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Section: Discussionmentioning

confidence: 99%

Mapping the Multi-Vulnerabilities of Outdoor Places to Enhance the Resilience of Historic Urban Districts: The Case of the Apulian Region Exposed to Slow and Rapid-Onset Disasters

Cantatore,

Esposito,

Sonnessa

2023

Sustainability

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“…River networks and basin boundaries can be determined via ArcGIS and Basin toolbox, which are GIS software. GIS is used to solve many water engineering problems and to prepare base data such as digital elevation model data [17,22,[24][25][26][27][28][29][30][31].…”

Section: Methodsmentioning

confidence: 99%

Modeling of annual maximum flows with geographic data components and artificial neural networks

Çubukçu

Demir

Sevimli

2023

International Journal of Engineering and Geosciences

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Disasters such as floods and floods are also encountered on the days when the highest flow is recorded, according to the Annual Maximum Flow (AMF) statistics. The Annual Maximum Flow is the highest flow rate ever recorded in a water year. Wherever this flow happens, it usually results in flooding. Snow melts and unexpected precipitation associated with temperature fluctuations are the two most important factors that create flooding. The deluge that follows kills people and destroys property in communities and agricultural lands. As a result, it's critical to predict the flow that causes flooding and take appropriate precautions to limit the damage. The prediction of the probability of the flood event in advance is very important for the safety of life and property of large masses and agricultural lands. Early warning systems, disaster management plans and minimizing these losses are among the important goals of the country's administration. In this study, It is used in five Current Observation Stations (COS) located in Yeşilırmak Basin in Turkey. By using 8 input data including geographical location, altitude and area information of these stations, AMF data were tried to be estimated for each COS. A total of 240 input data was used in the study. The data period covers the years 1964-2012. Unfortunately, AMF values cannot be monitored for all 5 stations used after 2012.Therefore, the data period was stopped in 2012. In this study, Multilayer Artificial Neural Networks (MANN), Generalized Artificial Neural Networks (GANN), Radial Based Artificial Neural Networks (RBANN) and Multiple Linear Regulation (MLR) methods were used. Input data sets were made into 4 packets and these packages were used respectively in both training and testing stages. Root mean square error (RMSE), mean absolute error (MAE) and correlation coefficient (R) were used as the comparison criteria. The results are as follow; MANN (8 Input) (RMSE = 119.118, MAE = 93.213, R = 0.808), and RBANN (2 Input) (RMSE = 111.559, MAE = 81.114, R = 0.900). These results show that AMF can be predicted with artificial intelligence techniques and can be used as an alternative method.

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“…Kalbani & Rahman [18] investigated issues and challenges arising from the usage of 3D city models for monitoring of flood risks in Oman based on the "City Geography Markup Language" (CityGML) standard. The aim of the study was to reduce time and effort of decision-makers by using a 3D city model to deal with flood risk management.…”

Section: Introductionmentioning

confidence: 99%

Development of a virtual reality application for the Old Harran School

ERNST,

AKDAĞ,

POLAT

et al. 2024

International Journal of Engineering and Geosciences

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The objective of this project that is described in this paper was to introduce the little-known Harran School of the medieval Islamic period to a broader audience using virtual reality technologies. 3D models of the medieval Inner Castle in the Harran archaeological site and one of its saloons obtained by photogrammetric methods were transferred to the game engine Unity. To this main saloon, 3D models of artifacts found during excavation works on this site that were used in medieval and earlies times were added. Additional objects, illumination and paintings of great Islamic scholars were appended to create a museum setting in the saloon. Currently, this virtual museum can be experienced by PC-based head-mounted devices. This project has been implemented under the Umbrella Group of Harran School at Harran University. While different implementations of virtual museums are available in Turkey with this project, a museum deploying virtual reality technology has been realized for the first time.

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3D city model for monitoring flash flood risks in Salalah, Oman

Cited by 11 publications

References 25 publications

Mapping the Multi-Vulnerabilities of Outdoor Places to Enhance the Resilience of Historic Urban Districts: The Case of the Apulian Region Exposed to Slow and Rapid-Onset Disasters

Mapping the Multi-Vulnerabilities of Outdoor Places to Enhance the Resilience of Historic Urban Districts: The Case of the Apulian Region Exposed to Slow and Rapid-Onset Disasters

Modeling of annual maximum flows with geographic data components and artificial neural networks

Development of a virtual reality application for the Old Harran School

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