Spatialisation of GDP based on NPP-VIIRS night lighting and urban utilization

DOI

10.2991/978-94-6463-419-8_22How to use a DOI?

Keywords

Specialization of GDP; Geospatial information; Energy consumption; Population density; Grayscale image element values

Abstract

Spatialisation of Gross Domestic Product combines GDP data with geospatial information can be used to visualize economic differences between regions. It allows for objective evaluation of economic disparities and can aid in identifying areas for targeted development. Besides, a city's economic level can be indicated by its energy consumption and population density, both of which are positively correlated with nighttime lighting data. Thus, the study builds a regression model of GDP and NPP-VIIRS nighttime light radiation value taking Beijing as an example, as the economic development of districts and counties in Beijing varies significantly. The lighting data from 2013–2020 was obtained from the database and processed to obtain the grayscale image element values. Ordinary Least Squares was used to model the regression of grey scale image element values with GDP for each year. The model fitting results indicated a positive linear correlation between GDP and nighttime lighting data. The correlation between GDP and nighttime lighting increased gradually from 2013 to 2020. During this period, the area of light and light intensity in Beijing increased simultaneously at night. From a spatial perspective, the intensity of nighttime lighting was higher in the central city than in the suburbs. This observation was consistent with the actual GDP level of Beijing. After pixel-by-pixel correction, the mean error was controlled between 1.02 to 1.15. Thus the level of economic development of the city can be predicted by the spatialisation of GDP used by the NPP-VIIRS night lights and the city. Besides, the study corrected special data points through error analysis, improving the accuracy of the application of the night light data and the ability to handle abnormal data.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Censhan Gao
AU  - Junhan Li
AU  - Tengyue Wu
AU  - Runjie Wang
AU  - Jie Wang
AU  - Haolin Chen
AU  - Yutong Jiang
PY  - 2024
DA  - 2024/05/07
TI  - Spatialisation of GDP based on NPP-VIIRS night lighting and urban utilization
BT  - Proceedings of the 3rd International Academic Conference on Blockchain, Information Technology and Smart Finance (ICBIS 2024)
PB  - Atlantis Press
SP  - 173
EP  - 179
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-419-8_22
DO  - 10.2991/978-94-6463-419-8_22
ID  - Gao2024
ER  -