Redirigiendo al acceso original de articulo en 19 segundos...
ARTÍCULO
TITULO

Temporal Dynamics of Citizen-Reported Urban Challenges: A Comprehensive Time Series Analysis

Andreas F. Gkontzis    
Sotiris Kotsiantis    
Georgios Feretzakis and Vassilios S. Verykios    

Resumen

In an epoch characterized by the swift pace of digitalization and urbanization, the essence of community well-being hinges on the efficacy of urban management. As cities burgeon and transform, the need for astute strategies to navigate the complexities of urban life becomes increasingly paramount. This study employs time series analysis to scrutinize citizen interactions with the coordinate-based problem mapping platform in the Municipality of Patras in Greece. The research explores the temporal dynamics of reported urban issues, with a specific focus on identifying recurring patterns through the lens of seasonality. The analysis, employing the seasonal decomposition technique, dissects time series data to expose trends in reported issues and areas of the city that might be obscured in raw big data. It accentuates a distinct seasonal pattern, with concentrations peaking during the summer months. The study extends its approach to forecasting, providing insights into the anticipated evolution of urban issues over time. Projections for the coming years show a consistent upward trend in both overall city issues and those reported in specific areas, with distinct seasonal variations. This comprehensive exploration of time series analysis and seasonality provides valuable insights for city stakeholders, enabling informed decision-making and predictions regarding future urban challenges.

 Artículos similares

       
 
Haiqiang Yang and Zihan Li    
The objective imbalance between the taxi supply and demand exists in various areas of the city. Accurately predicting this imbalance helps taxi companies with dispatching, thereby increasing their profits and meeting the travel needs of residents. The ap... ver más

 
Jingtao Sun, Jin Qi, Zhen Yan, Yadong Li, Jie Liang and Sensen Wu    
The COVID-19 pandemic has had a profound impact on people?s lives, making accurate prediction of epidemic trends a central focus in COVID-19 research. This study innovatively utilizes a spatiotemporal heterogeneity analysis (GTNNWR) model to predict COVI... ver más

 
Lei Jin, Shaodan Chen and Mengfan Liu    
Drought, as a recurring extreme climatic event, inflicts diverse impacts on ecological systems, agricultural productivity, water resources, and socio-economic progress globally. Discerning the drought patterns within the evolving environmental landscape ... ver más
Revista: Water

 
Yang Liu and Qianqian Zhang    
Analyzing 165 data from five national control sites in Baiyangdian Lake, this study unveils its spatiotemporal pattern of water quality. Utilizing machine learning and multivariate statistical techniques, this study elucidates the effects of rainfall and... ver más
Revista: Water

 
Zhihui Tian, Ruoyi Zhang, Lili Wu, Yongji Wang, Jinjin Yang and Di Cao    
Climate change, population growth, and socio-economic transformations present multifaceted challenges to the water resource systems in the four major river basins of Henan Province. Consequently, to gain a comprehensive understanding of water security wi... ver más
Revista: Water