Using NASA’s night light data analyzing poverty index Bangladesh

Abstract

In the never-ending quest to reach Sustainable Development Goal 1 (SDG 1), which is to end poverty, new and different ways of doing things are needed, especially in places where collecting data the old way is hard. ”Analysis of Poverty Using NASA Black Marble NTL Data with the DHS Wealth Index of Bangladesh,” the title of this study, describes a new way to figure out how poor a country is by using NASA’s VNP46A4 dataset, which is an important part of the Black Marble suite. The VNP46A4 dataset gives annual averages from 2017 to 2018 based on NTL radiance corrected for atmospheric and lunar factors, containing 28 layers of useful information. Initial analysis using VNP46A4 and DHS data revealed inefficiencies and accuracy issues. Therefore, we propose a new approach: utilizing datasets for the year 2022, including OSM, Google Static Maps, and NASA’s VNP46A3, which provides monthly data that we have merged into yearly aggregates, to achieve higher accuracy. This method focuses on specific data layers, h26v06 and h27v06, within the VNP46A4 dataset covering Bangladesh. By integrating the unique nighttime brightness data of Bangladesh through merging and clipping, and combining it with other significant datasets, this study aims to present a comprehensive overview of the country’s socioeconomic status. Using NASA’s nighttime light data intelligently, this approach seeks to provide policymakers, development agencies, and academics with a transformative tool, leveraging advanced technology and extensive datasets to enable informed decisions and targeted assistance for struggling communities.