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Peña-García, A.; Sędziwy, A. |
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Title |
Optimizing Lighting of Rural Roads and Protected Areas with White Light: A Compromise among Light Pollution, Energy Savings, and Visibility |
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2019 |
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Leukos |
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Leukos |
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in press |
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15502724.2019.1574138 |
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Lighting; Energy; Skyglow; LED |
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The broad implementation of light emitting diode (LED) light sources in public lighting has become a revolution in recent years. Their low power consumption and good performance (extremely low onset time, long lifetime, high efficacy) make LEDs an optimal solution in most outdoor applications. In addition, the white light emitted by the vast majority of LEDs used in public lighting and their good color rendering improve well-being, comfort, and safety in cities, especially in commercial zones and urban centers. However, regulations on light pollution that have been developed in some countries in parallel to the introduction of LED lighting impose strong constraints to white light emission, which is present due to the higher Rayleigh scattering of short wavelengths. These regulations request filtering blue wavelengths in some protected areas and thus limit the projects to high- or low-pressure sodium sources or amber LEDs. In this work, the pros and cons of white and amber LED lighting in rural areas are analyzed and compared through simulations made on a typical rural lighting situation and considerations based on efficiency, visual performance, nonvisual effects, and light pollution. The most important conclusion is that Rayleigh scattering seems to prevail in the current considerations on light pollution, whereas other important aspects affecting safety and sustainability are are not considered. Accurate designs can decrease light pollution without constraints against white LEDs. The objective of this work is to provide evidence leading to consider light pollution from a more general perspective in the benefit of humans and the environment. |
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1550-2724 |
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GFZ @ kyba @ |
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2380 |
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Jiang, Z.; Zhai, W.; Meng, X.; Long, Y. |
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Title |
Identifying Shrinking Cities with NPP-VIIRS Nightlight Data in China |
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Journal Article |
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2020 |
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Journal of Urban Planning and Development |
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J. Urban Plann. Dev. |
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146 |
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4 |
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04020034 |
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Remote Sensing |
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Although there has been a rapid urbanization in China since the 1980s, the simultaneous urban shrinkage phenomenon has existed for a long time. The study of shrinking cities is particularly important for China as the current urban development has changed from physical expansion to built-up area improvement. After redefining what constitutes a city (what we term a natural city), we compared the adjusted nightlight intensity of National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) data between 2013 and 2016 to accurately identify shrinking cities throughout China. The results indicate that there are 2,862 redefined natural cities in China and that the total area reaches 53,275 km2, about 0.5% of the national territory. Based on this, we identified 798 shrinking cities with a total area of 13,839 km2. After analyzing the relative position of shrinking cities and internal shrinking pixels in the geometric space, the morphological characteristics of shrinking cities were systematically classified into six patterns. The majority of shrinking cities belong to scatter shrinkage, central shrinkage, and local shrinkage; only 5% are complete shrinkage; the rest are unilateral shrinkage and peripheral shrinkage. In addition, six shrinkage causes were quantitatively classified and summarized by referring to multiple-source urban data and municipal yearbooks. To enrich the methodological system for urban shrinkage, the research provides a reminder of the need to consider the other side of urbanization (i.e., dissolution of social networks) and proposes appropriate strategies and policies to address shrinkage issues. |
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0733-9488 |
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GFZ @ kyba @ |
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3065 |
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Shan, J.; Liu, Y.; Kong, X.; Liu, Y.; Wang, Y. |
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Identifying City Shrinkage in Population and City Activity in the Middle Reaches of the Yangtze River, China |
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Journal Article |
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2020 |
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Journal of Urban Planning and Development |
Abbreviated Journal |
J. Urban Plann. Dev. |
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146 |
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3 |
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04020027-1 - 04020027-11 |
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Remote Sensing |
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In the context of globalization, cities have undergone a polarization of growth and shrinkage. Urban shrinkage is typically measured by a decrease in population. However, city activity is usually ignored. Accordingly, this study measured city shrinkage in the middle reaches of the Yangtze River based on whether city activities and population shrank from 2000 to 2010. This study drew on the Cobb-Douglas production function using multiple big data [such as nighttime light (NTL) data, patent data, and land transaction data] to calculate a city activity index to examine city activity. The geographically weighted regression (GWR) model was applied to explore the influencing factors of city shrinkage. Results showed the following: (1) in the area of study, 14.87% of cities experienced population loss, considering the city activities, an increase in the latter accounted for 57.36% in depopulation cities; (2) urban shrinkage spatial pattern presented the feature of “overall growth, local shrinkage”; (3) in the urban shrinkage regression model, urban spatial expansion and the increase in secondary industry population were factors that aggravated urban shrinkage. The main influencing factors of city shrinkage in the regions are different and need to be studied in-depth and meticulously in combination with the local development situation. This study plays a vital role in characterizing city activities and identifying urban shrinkage while providing a reference for urban planning and policy setting. |
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0733-9488 |
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UP @ altintas1 @ |
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3180 |
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Zangeneh, P.; Hamledari, H.; McCabe, B. |
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Title |
Quantifying Remoteness for Risk and Resilience Assessment Using Nighttime Satellite Imagery |
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Journal Article |
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Year |
2020 |
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Journal of Computing in Civil Engineering |
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J. Comput. Civ. Eng. |
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34 |
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5 |
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04020026 |
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Remote Sensing |
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Remoteness has a crucial role in risk assessments of megaprojects, resilience assessments of communities and infrastructure, and a wide range of public policymaking. The existing measures of remoteness require an extensive amount of population census and of road and infrastructure network data, and often are limited to narrow scopes. This paper presents a methodology to quantify remoteness using nighttime satellite imagery. The light clusters of nighttime satellite imagery are direct yet unintended consequences of human settled populations and urbanization; therefore, the absence of illuminated clusters is considered as evidence of remoteness. The proposed nighttime remoteness index (NIRI) conceptualizes the remoteness based on the distribution of nighttime lights within radii of up to 1,000 km. A predictive model was created using machine learning techniques such as multivariate adaptive regression splines and support vector machines regressions to establish a reliable and accurate link between nighttime lights and the Accessibility/Remoteness Index of Australia (ARIA). The model was used to establish NIRI for the United States and Canada, and in different years. The index was compared with the Canadian remoteness indexes published by Statistics Canada. |
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0887-3801 |
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GFZ @ kyba @ |
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2937 |
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Liu, J.; Cai, J.; Lin, S.; Zhao, J. |
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Title |
Analysis of Factors Affecting a Driver’s Driving Speed Selection in Low Illumination |
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Journal Article |
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2020 |
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Journal of Advanced Transportation |
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Journal of Advanced Transportation |
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2020 |
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Article ID 2817801 |
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Public Safety |
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To better understand a driver’s driving speed selection behaviour in low illumination, a self-designed questionnaire was applied to investigate driving ability in low illumination, and the influencing factors of low-illumination driving speed selection behaviour were discussed from the driver’s perspective. The reliability and validity of 243 questionnaires were tested, and multiple linear regression was used to analyse the comprehensive influence of demographic variables, driving speed in a low-illumination environment with street lights and driving ability on speed selection behaviour in low illumination without street lights. Pearson’s correlation test showed that there was no correlation among age, education, accidents in the past 3 years, and speed selection behaviour in low illumination, but gender, driving experience, number of night-driving days per week, and average annual mileage were significantly correlated with speed selection behaviour. In a low-illumination environment, driving ability has a significant influence on a driver’s speed selection behaviour. Technical driving ability under low-illumination conditions of street lights has the greatest influence on speed selection behaviour on a road with a speed limit of 120 km/h (β = 0.51). Risk perception ability has a significant negative impact on speed selection behaviour on roads with speed limits of 80 km/h and 120 km/h (β = −0.25 and β = −0.34, respectively). Driving speed in night-driving environment with street lights also has a positive influence on speed selection behaviour in low illumination (β = 0.61; β = 0.28; β = 0.37). |
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0197-6729 |
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GFZ @ kyba @ |
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2913 |
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