Remote night-time lights sensing: Investigation and econometric application

Journal of Economic and Financial Sciences


 
 
Field Value
 
Title Remote night-time lights sensing: Investigation and econometric application
 
Creator Coetzee, Clive E. Kleynhans, Ewert P.J.
 
Subject night lights; light pollution; DMSP/OLS; VIIRS/DNB; International Space Station; urban human activity
Description Orientation: Some recent studies have been published that demonstrated the value of remote sensing night-time lights as descriptors and/or proxies for human activity.Research purpose: This article investigated the association between night-time light emissions and gross domestic product (GDP) estimates for South Africa.Motivation for the study: Satellite night-lights data seemed to be a useful proxy for economic activity at temporal and geographic scales for which traditional data are of poor quality, are unavailable or only available with a large time lag.Research approach/design and method: The article primarily used the remote sensing of night-time light emissions using satellite technologies. The methodology employed in this study involved estimating both a vector error correction modelling (VECM) and autoregressive distributed lag (ARDL) models that map light growth into a proxy for GDP growth.Main findings: Both the VECM and ARDL models confirmed a long-term co-integrating relationship between GDP (per capita) and night-time lights (total light intensity), a statistically significant short-term error correction term could, however, not be established through the VECM, but indeed through the ARDL model.Practical/managerial implications: The results of the study suggested that satellite remote sensing technologies held much promise and opportunities in terms of the field of Economics and Development.Contribution/value-add: This study contributes to our understanding of the spatial and temporal behaviour and trends in economic activity. It also suggested the use of satellite remote sensing technologies as part of official statistical frameworks and methodologies.
 
Publisher AOSIS
 
Contributor World Trade Organization (WTO) National Research Foundation (NRF)
Date 2021-03-17
 
Type info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion —
Format text/html application/epub+zip text/xml application/pdf
Identifier 10.4102/jef.v14i1.613
 
Source Journal of Economic and Financial Sciences; Vol 14, No 1 (2021); 12 pages 2312-2803 1995-7076
 
Language eng
 
Relation https://jefjournal.org.za/index.php/jef/article/view/613/1197 https://jefjournal.org.za/index.php/jef/article/view/613/1196 https://jefjournal.org.za/index.php/jef/article/view/613/1198 https://jefjournal.org.za/index.php/jef/article/view/613/1195
 
Rights Copyright (c) 2021 Clive E. Coetzee, Ewert P.J. Kleynhans https://creativecommons.org/licenses/by/4.0