Abstract

In previous studies using night-time light (NTL) image in analyzing light pollution, most of the researchers focused on national or regional scale analysis. While in this article we focus on the perception of light pollution's influence to the environment of human settlement. We propose an analysis method mainly utilizing NTL images and a city's point of interest (POI) data to assess the light pollution from the aspect of its impact on the environment of city residents. The method quickly provides light pollution analysis at a fine spatial scale. We also address the POI data in a novel aggregating algorithm to better construct the area of interest, which can conquer the limitation of spatial resolution of NTL data in some extent. By doing the assessment in two Chinese medium-size cities, light pollution sources, the pollution level for each residence are found and analyzed. Furthermore, several light pollution patterns are discovered and interpreted. The result of the experiment demonstrates our assessment method provides a fast way to analyze light pollution patterns and can show the detailed light pollution situation in a city.

Highlights

  • L IGHT pollution is caused by alteration of natural light levels in the night environment produced by the introduction of artificial light, a problem that is increasingly debated [1]

  • We proposed an assessment model to simulate the influence from one single point of light pollution source to residents

  • Considering that the amount of point of interest (POI) varies greatly with category, we proposed a potential polluting index (PPI), which aims to measure the potential of pollution sources to cause light pollution rPOI

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Summary

Introduction

L IGHT pollution is caused by alteration of natural light levels in the night environment produced by the introduction of artificial light, a problem that is increasingly debated [1]. The impact of the light pollution on public health through either direct or indirect effects is of utmost concern, the potential adverse health outcomes include cancers, cardiovascular disease, obesity, adverse pregnancy outcomes, and metabolic diseases. Manuscript received March 14, 2021; revised April 11, 2021; accepted July 10, 2021. Date of publication July 14, 2021; date of current version August 9, 2021.

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