An empirical study of relationships between urban lighting indicators and night-time light radiance
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Published:2023
Issue:5
Volume:33
Page:375-396
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ISSN:2336-4335
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Container-title:Neural Network World
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language:
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Short-container-title:NNW
Author:
Kekula František,Hrubeš Pavel
Abstract
Night-time light (NTL) radiance has a great potential in analyses of dynamic changes in patterns of human activities, and socio-economic and demographic factors. However, most of those analyses are focused on factors at global scales such as the population size, gross domestic product, electric power consumption, fossil fuel carbon dioxide emission etc. In this study we investigate the relationships between three urban lighting indicators and monthly averaged NTL radiance obtained from NASAs Black Marble monthly NTL composites for 4 study areas in the Czech Republic at local scale. The Pearson correlation analysis was used to identify a strength of the correlations between the indicators and radiance at near-nadir for two different snow conditions. The results from the correlation show that radiance has a strong positive correlation with the number of streetlighting points and their total nominal power, while for the average mast height there were observed moderate correlation coefficients. However, the areas with larger scales have higher correlation coefficients. Moreover, we found that the correlation coefficients are higher for snow-covered condition radiances. Generalized linear (GL) regression analysis was used to examine an association between the radiance and selected indicators. Owing to the excess zeros and overdispersion in the data, the zero-inflated regression performs better than the GL regression. Results from the regression analysis evince a statistically significant relationship between the radiance and selected indicators.
Publisher
Czech Technical University in Prague - Central Library
Subject
Artificial Intelligence,Hardware and Architecture,General Neuroscience,Software
Cited by
1 articles.
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