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

Andreas F. Gkontzis, S. Kotsiantis, G. Feretzakis, V. Verykios
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Abstract

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.
市民报告的城市挑战的时间动态:综合时间序列分析
在以数字化和城市化的迅猛发展为特征的时代,社区福祉的本质取决于城市管理的效率。随着城市的蓬勃发展和转型,制定精明的策略以驾驭复杂的城市生活变得越来越重要。本研究采用时间序列分析法,对希腊帕特雷市市民与基于坐标的问题映射平台的互动情况进行了仔细研究。研究探讨了所报告的城市问题的时间动态,特别侧重于通过季节性视角识别重复出现的模式。该分析采用季节分解技术,对时间序列数据进行剖析,以揭示原始大数据中可能被掩盖的报告问题和城市区域的趋势。它突出了一个明显的季节性模式,即夏季的浓度达到峰值。该研究将其方法扩展到了预测,提供了对城市问题随着时间推移的预期演变的见解。对未来几年的预测显示,总体城市问题和特定地区报告的城市问题都呈持续上升趋势,并伴有明显的季节性变化。这种对时间序列分析和季节性的全面探索为城市利益相关者提供了宝贵的见解,使他们能够对未来的城市挑战做出明智的决策和预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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