Potential of Night-Time Lights to Measure Regional Inequality

Kinga Ivan,József Benedek,Iulian-Horia Holobâcă,Ibolya Török

doi:10.3390/rs12010033

Abstract

Night-time lights satellite images provide a new opportunity to measure regional inequality in real-time by developing the Night Light Development Index (NLDI). The NLDI was extracted using the Gini coefficient approach based on population and night light spatial distribution in Romania. Night-time light data were calculated using a grid with a 0.15 km2 area, based on Defense Meteorological Satellite Program (DMSP) /Operational Linescan System (OLS satellite imagery for the 1992–2013 period and based on the National Polar-orbiting Partnership–Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) satellite imagery for the 2014–2018 period. Two population density grids were created at the level of equal cells (0.15 km2) using ArcGIS and PostgreSQL software, and census data from 1992 and 2011. Subsequently, based on this data and using the Gini index approach, the Night Light Development Index (NLDI) was calculated within the MATLAB software. The NLDI was obtained for 42 administrative counties (nomenclature of territorial units for statistics level 3 (NUTS-3 units)) for the 1992–2018 period. The statistical relationship between the NLDI and the socio-economic, demographic, and geographic variables highlighted a strong indirect relationship with local tax income and gross domestic product (GDP) per capita. The polynomial model proved to be better in estimating income based on the NLDI and R2 coefficients showed a significant improvement in total variation explained compared to the linear regression model. The NLDI calculated on the basis of night-time lights satellite images proved to be a good proxy for measuring regional inequalities. Therefore, it can play a crucial role in monitoring the progress made in the implementation of Sustainable Development Goal 10 (reduced inequalities).

Highlights

At the United Nations (UN) Sustainable Development Summit held in September 2015, the leaders of 193 UN member states expressed their adherence to the 17 Sustainable Development Goals (SDGs) of the 2030 Agenda which, as a global action plan, aims at reducing poverty, fighting inequalities and injustice, and protecting the environment by 2030 [1]
We demonstrated in our study that Earth observation solutions could play an important role
We demonstrated in our study that Earth observation solutions could play an important role in in monitoring progress in the direction of SDG 10

Summary

Introduction

At the United Nations (UN) Sustainable Development Summit held in September 2015, the leaders of 193 UN member states expressed their adherence to the 17 Sustainable Development Goals (SDGs) of the 2030 Agenda which, as a global action plan, aims at reducing poverty, fighting inequalities and injustice, and protecting the environment by 2030 [1]. SDG 10 aims at reducing inequalities, which include, among other actions, empirical evidence production and monitoring the evolution of inequalities within and among countries. The monitoring of the latter is not difficult for most countries where national accounts and national statistical offices have been established [33]

Objectives

Methods

Conclusion