Mapping accessibility for earthquake hazard response in the historic urban centre of Bucharest

Merciu, Cristina; Ianoş, Ioan; Merciu, George-Laurenţiu; Jones, Roy; Pomeroy, George M.

doi:10.5194/nhess-18-2011-2018

Cited by 15 publications

(5 citation statements)

References 43 publications

(55 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this field, the application of spatial syntax is prevalent, mainly used for analyzing spatial topological structures [34][35][36][37]. Scholars using GIS for Spatial Morphology research are also numerous, focusing on spatial patterns and features [38][39][40][41]. Some scholars use GIS to assess the landscape sensitivity of historical districts, as seen in the works of Fang et al [42] and Yang and Shen [43].…”

Section: Study On the Preservation And Utilization Of Historic Districtsmentioning

confidence: 99%

Quantitative Research of Street Interface Morphology in Urban Historic Districts:A Case Study of West Street Historic District,Quanzhou

Huang,

Kang,

Zhao

2024

Preprint

View full text Add to dashboard Cite

Historic districts intertwine various elements of historical heritage, cultural significance, social relations and daily activities, and have significant research value. Through a review of previous literature, it can be observed that research on the conservation and renewal of historic districts often focuses on the overall planning and development of macro-level district. Recognizing the scarcity of quantitative studies on spatial morphology at the meso level, this paper introduces a quantitative methodology applicable to historic streets. Utilizing Quanzhou City's West Street Historical and Cultural Neighborhood as a case study, it employs Aspect Ratio (D/H), Interface Density, and Build-To-Line Rate to describe and summarize street interface morphology, presenting transformative strategies for future protection and renewal. West Street's characteristics include: (1) horizontally, influenced by the Tang Dynasty's concept of "lining houses to form streets," it has a high Build-To-Line Rate and density, providing enclosure, limitation, and spatial continuity; (2) vertically, it displays diverse interface morphology with a moderate Aspect Ratio and rhythmic changes, maintaining visitor interest. The study validates the feasibility of this quantitative method and provides valuable insights for the conservation and renewal of historic districts.

show abstract

Section: Study On the Preservation And Utilization Of Historic Districtsmentioning

confidence: 99%

Quantitative Research of Street Interface Morphology in Urban Historic Districts:A Case Study of West Street Historic District,Quanzhou

Huang,

Kang,

Zhao

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The Light Gradient Boosting (LGBM) model's prediction performance can be observed in Figure [22], where the orange line represents the predicted values and the blue line represents the actual values. The model's evaluation metrics can be obtained from Table [7], which shows an MAE of 0.2466, MSE of 0.1343, RMSE of 0.3513, R2 of 0.1491, RMSLE of 0.0555, MAPE of 0.0483, and TT of 0.1330 s. The accuracy of the model can also be assessed by examining Figure [23],…”

Section: Decision Tree Modelmentioning

confidence: 99%

Prediction of earthquake magnitude and seismic vulnerability mapping using artificial intelligence techniques: a case study of Turkey

Biswas

Kumar

Bera

2023

Preprint

View full text Add to dashboard Cite

Earthquake threats can result in fatalities, property destruction, and other cascading effects. Since it is nearly impossible to prevent earthquakes, anticipating the location of future earthquakes and figuring out their likelihood could be very helpful in reducing the seismic threat. In this work, seismic hazard prediction is executed to forecast adverse results using a range of potential artificial intelligence (AI) techniques, including ML and ANN. In the case study, we have looked at Turkey, which was recently and badly damaged by two earthquakes in February 2023. To predict earthquake magnitude, this study used a variety of regression algorithms, including Decision Tree Regressor, Extra-Trees Regressor, Random Forest Regressor, Bayesian Ridge Regressor, and advanced gradient boosting decision tree (GBDT) algorithms such as XGBoost, LightGBM, and CatBoost, as well as three artificial neural networks (ANN). The predicted magnitude and risk zone of an earthquake are mapped using a geographic information system (GIS), and the maps performed well in terms of prediction. The generated maps is showing the expected earthquake risk based on historical data using the statistical computations. The ANN models perform exceptionally well, with R2 scores of 0.99 and 0.98 for training and case study data, respectively, and low values for MSE, MAE, and RMSE. ML models have demonstrated an exceptional ability to properly generalize from a single dataset, which implies they can accurately anticipates results for new and untested data. The results would be helpful to many local emergency preparedness and infrastructure planning organizations.

show abstract

“…Almost half of the respondents mentioned the action of conservation and the consolidation of some patrimonial assets from the historical center of Bucharest as being necessary. These tourists' recommendations are related to the fact that there are several heritage buildings facing seismic risk in the study area [50,51], some of which are in a precarious state of conservation.…”

Section: Significance Of Findingsmentioning

confidence: 99%

Economic Valuation of Cultural Heritage Using the Travel Cost Method: The Historical Centre of the Municipality of Bucharest as a Case Study

2021

Self Cite

View full text Add to dashboard Cite

Because heritage buildings represent a special category of goods due to characteristics such as uniqueness and irreversibility, they are associated with multiple possibilities of use. This article aims to present a complex analysis of the values associated with using heritage buildings in the historical center of Bucharest and their correlation with corresponding conservation measures using the travel cost method. The authors used two computation methods: the zonal travel cost and the individual travel cost methods. The application of Bravais–Pearson’s coefficient of linear correlation confirmed that the demand for a cultural heritage site is inversely related to the travel costs and distance. The results reflect that the demand also depends on other factors, such as the satisfaction level of the tourist experience and tourists’ income and motivations. The study highlights the usefulness of the travel cost method, which facilitates analyzing the relationship between the significant value of using historical monuments and the extremely important conservation process in the current context, marked by socioeconomic dynamics that determine many reuses of cultural heritage.

show abstract

Mapping accessibility for earthquake hazard response in the historic urban centre of Bucharest

Cited by 15 publications

References 43 publications

Quantitative Research of Street Interface Morphology in Urban Historic Districts:A Case Study of West Street Historic District,Quanzhou

Quantitative Research of Street Interface Morphology in Urban Historic Districts:A Case Study of West Street Historic District,Quanzhou

Prediction of earthquake magnitude and seismic vulnerability mapping using artificial intelligence techniques: a case study of Turkey

Economic Valuation of Cultural Heritage Using the Travel Cost Method: The Historical Centre of the Municipality of Bucharest as a Case Study

Contact Info

Product

Resources

About