Night Lights

In recent years, the application of satellites and big data to the economic field has been expanding rapidly. In particular, it has become clear that the intensity of night light acquired by satellites is correlated with social and economic indicators such as gross domestic product, employment, population, and education in each country. In this paper, I first describe the method of calculating the night light intensity in Japan by prefecture and city. Next, in order to understand the versatility of the night light data, I examine the relationship between the intensity of night light at the city level and various socio-economic indicators and data published by public offices, using Japan as a case study. Based on the results of the various analyses, it is assumed that night light can be used as a proxy variable for these various indicators. Finally, I describe the possibility of using night light to perform a rapid analysis on the stagnation of economic activity under sudden social events.

NEXT

back ground

The data acquired by satellites are large scale and high frequency. It is possible to obtain the data at any time and use it in all situations from research to daily life. The use of this technology is underway. For example, the amount of precipitation, wind speed, and sea Remote sensing data such as water temperature and soil moisture content. based on crop selection, agricultural productivity, urban development, and Building types, roads, pollution, flooding, beach quality, fishing This is the first time that I have seen such a study. Among them, the data has attracted much attention as highly versatile data, and The data of night lights are shown in this report.

chapter1

Initially, we analyze the relationship between the data published by the government and the night light in Japan. Secondly, economic activity under sudden social events such as the coronal catastrophe The purpose of this paper is to describe the analysis and the possibility of estimating the stagnation of the movement using the night light.

Relationship between store density and night light intensity in each municipality

Retail stores, restaurants, commercial offices, department stores, and large supermarkets are open at night, which has a significant effect on the intensity of light at night, so the correlation coefficient is expected to be high when performing the correlation analysis. At this time, to minimize the difference by the area of the municipality, we used the density of stores rather than the number of stores.


Relationship between unemployed and suicide

For unemployment and homelessness, the total number of homeless people = 2401.8* unemployment rate -1131.39, given by R^2: 0.974139 and P-value: < 0.0001, which is very true. Similarly, for men, the number of people living homeless = 2236.87* unemployment rate -1071.88, given by R^2: 0.971681 and P-value: < 0.0001. On the other hand, for women, given the number of homeless people = 63.9464* unemployment rate + 15.32, R^2: 0.871758, P-value: 0.0020988, the fit is high, but it hardly changes when the unemployment rate (number of unemployed people) goes up.

TOP