## 1 Introduction  
Road lighting plays an important role in human life, and many types of light sources, such as the low-pressure sodium lamp (LPS), the high pressure mercury lamp (HPM) [1], the high pressure sodium lamp (HPS) [2], the metal halide lamp (MH) [3], and the light emitting diode (LED) [4], have been used in road lighting. The illuminance of road lighting is of great importance in helping people evaluate efficiency, safety [5; 6; 7], health [8], and economics issues [9] related to the urban environment. At present, the main approaches of measuring road lighting are illuminance/luminance meters and imaging photometers [10]. The measurement of road lighting is logistically difficult. The measured part of the road should be closed during measurements, which requires cooperation from the local authority. Existing guidance (e.g., British Standards Institution 2016 [11] and CIE 115:2010 [12]) requires approximately 30 measurements to be recorded at equally spaced positions between luminaires, which is a significant undertaking. Extrapolation of the light measurements from the measured section of the road to other parts of the road may not be valid for a number of reasons, such as variations in the distribution of luminaires, the light losses of light sources, and occlusion caused by trees. These issues can cause differences in illuminance distributions in different parts of a road. Existing approaches therefore cannot guarantee a simple measurement of a whole road, without significant resource allocation towards comprehensive measurements of the lighting. Lighting has a great influence on human beings in many aspects. Prior studies reported that the artificial lighting at night (ALAN) have an impact on human productivity, social activity, accident prevention, health, and safety [13]. Suitable ambient lighting may increase the activities of pedestrians and cyclists at night [14]. There is a strongly held public perception that street lighting contributes directly to the safety [15; 16]. Lighting has both positive and negative effects on human health [17]. ALAN is also related to aesthetics, energy, and economic issues. Lighting has been playing important roles in beautifying cities [18], leading to economic benefits. However, energy consumption is also great [19], and several energy performance indicators [20] are proposed for evaluation. The benefits and costs of ALAN should be balanced. Moreover, ALAN may also have an ecology impact and cause light pollution [21]. Most of these related impacts cannot be precisely and clearly evaluated due to a lack of big lighting data. In terms of the lighting itself, lighting data can provide a range of lighting performance information, with which we can establish a smarter lighting system in the city. With illuminance data, it is possible to evaluate the illuminance levels, uniformity [22], lighting efficiency [23], mesopic luminance [24; 25], and melanopic illuminance [26] performance. Most road lighting provides luminances between 0.5 to 2 cd/m\({}^{2}\)[27; 28] and tends to fall in the mesopic vision of luminance range from 0.005 to 5 cd/m\({}^{2}\)[24]. Illuminance/luminance is measured using the spectral sensitivity curve in photopic vision [29], which is the photopic adaptation luminance. A transform to the mesopic luminance provides a more accurate measure of the lighting perceived by an observer at night. The circadian/ melanopic illuminance [30; 31] is a concept derived from non-visual biological effects relating to health problems. Several models, the [PERSON] model [32], the [PERSON] model [30], and the [PERSON] work [31], the latter two of which are established considering neuro mechanisms, have been proposed to measure circadian/ melanopic illuminance. There is discrepancy between these two works, and none has been formally acknowledged. In this study, we adopt equivalent melanopic lux based on the [PERSON] work in the calculation.