Optimizing the environmental design and management of public green spaces: Analyzing urban infrastructure and long-term user experience with a focus on streetlight density in the city of Las Vegas, NV
IF 14.7 1区 计算机科学Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xiwei Shen, Jie Kong, Yang Song, Xinyi Wang, Grant Mosey
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引用次数: 0
Abstract
In Las Vegas and many other desert cities, the unique climatic conditions, marked by high daytime temperatures, naturally encourage residents to seek outdoor recreational activities during the cooler evening hours. However, the approach to streetlight management has been less than optimal, leading to inadequate illumination in public parks after dark. This lack of proper lighting compromises not only the safety but also the enjoyment opportunity of these spaces during the night, a time when they could offer a much-needed respite during summer heat. Recent scholarship has highlighted the deterrence of park usage due to poor design of the street lighting, pointing to a broader issue in urban planning that requires attention to adapt infrastructures to local climates for the benefit of public health and well-being. This study seeks to contribute to the existing scholarship on park lighting by utilizing diverse data sources and creating longitudinal measures to examine how population behaviors in urban parks vary over time in different locations. It seeks to explore the impact of park users’ demographics, particularly variations across race and income levels, and the density of street lighting on the nighttime usage of public green spaces by using the time fixed effect method. It aims to understand how demographic diversity among park users and the physical environment, specifically street lighting density, influences patterns of nighttime activities in public parks. Using this analysis, we develop an improved predictive model for determining the density of street lighting in public green spaces by comparing multiple types of machine learning models. This model will consider the demographic diversity of users and the observed patterns of nighttime usage, with the goal of enhancing accessibility, safety, and utilization of these spaces during nighttime hours. The significance of this research contributes to the broader objective of creating resilient, healthy, and inclusive cities that cater to the well-being of their residents.
期刊介绍:
Information Fusion serves as a central platform for showcasing advancements in multi-sensor, multi-source, multi-process information fusion, fostering collaboration among diverse disciplines driving its progress. It is the leading outlet for sharing research and development in this field, focusing on architectures, algorithms, and applications. Papers dealing with fundamental theoretical analyses as well as those demonstrating their application to real-world problems will be welcome.