Redirigiendo al acceso original de articulo en 19 segundos...
Inicio  /  Applied Sciences  /  Vol: 11 Par: 12 (2021)  /  Artículo
ARTÍCULO
TITULO

Detecting Areas Vulnerable to Flooding Using Hydrological-Topographic Factors and Logistic Regression

Jae-Yeong Lee and Ji-Sung Kim    

Resumen

As a result of rapid urbanization and population movement, flooding in urban areas has become one of the most common types of natural disaster, causing huge losses of both life and property. To mitigate and prevent the damage caused by the recent increase in floods, a number of measures are required, such as installing flood prevention facilities, or specially managing areas vulnerable to flooding. In this study, we presented a technique for determining areas susceptible to flooding using hydrological-topographic characteristics for the purpose of managing flood vulnerable areas. To begin, we collected digital topographic maps and stormwater drainage system data regarding the study area. Using the collected data, surface, locational, and resistant factors were analyzed. In addition, the maximum 1-h rainfall data were collected as an inducing factor and assigned to all grids through spatial interpolation. Next, a logistic regression analysis was performed by inputting hydrological-topographic factors and historical inundation trace maps for each grid as independent and dependent variables, respectively, through which a model for calculating the flood vulnerability of the study area was established. The performance of the model was evaluated by analyzing the receiver operating characteristics (ROC) curve of flood vulnerability and inundation trace maps, and it was found to be improved when the rainfall that changes according to flood events was also considered. The method presented in this study can be used not only to reasonably and efficiently select target sites for flood prevention facilities, but also to pre-detect areas vulnerable to flooding by using real-time rainfall forecasting.

 Artículos similares

       
 
Lev V. Eppelbaum, Youri I. Katz and Zvi Ben-Avraham    
The Easternmost Mediterranean is a transition region from the ocean to the continent where the spreading and collision zones of the lithospheric plates join. The methodology of paleomagnetic mapping of the transition zones is based on combining geologica... ver más
Revista: Applied Sciences

 
William Villegas-Ch and Jaime Govea    
This article addresses the need for early emergency detection and safety monitoring in public spaces using deep learning techniques. The problem of discerning relevant sound events in urban environments is identified, which is essential to respond quickl... ver más

 
Romina Kraus    
Ballast water is recognised as successfully transporting non-native (potentially) invasive alien species and other harmful organisms (human pathogens and toxic phytoplankton) from one region to another. Global warming enables the successful adaptation of... ver más

 
Zihao Liu, Zhaolin Wu, Zhongyi Zheng, Xianda Yu, Xiaoxuan Bu and Wenjun Zhang    
In recent years, the increasing volume and complexity of ship traffic has raised the probability of collision accidents in ports, waterways, and coastal waters. Due to the relative rarity of collision accidents, near misses have been used in the research... ver más

 
Nakhyeon Seong, Jeongseon Kim and Sungsu Lim    
This paper presents a novel machine learning-based approach for detecting abnormal ship movements using CCTV videos. Our method utilizes graph-based algorithms to analyze ship trajectories and identify anomalies, with a focus on enhancing maritime safety... ver más