Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 1 of 1
Full-Text Articles in Entire DC Network
Predicting Gross Metropolitan Product Worldwide Using Statistical Learning Models, Socio-Economic, And Satellite Imagery Data, Simin Joshaghani
Predicting Gross Metropolitan Product Worldwide Using Statistical Learning Models, Socio-Economic, And Satellite Imagery Data, Simin Joshaghani
Boise State University Theses and Dissertations
Gross metropolitan product (GMP) is one the most critical indicators for determining a metropolitan area’s economic performance. While GMP data currently exists for major cities in the US and OECD countries, the rest of the world is a blind spot. This study aims at estimating the GMP of 1289 cities in non-US and OECD countries, where no official city-level statistics are produced. We perform this estimation through multiple machine learning models, using night-time lights satellite imagery, and other publicly available data. We analyze eight spatial databases and four cross-sectional datasets and derive a feature vector of covariates through various techniques, …