Remote night-time lights sensing: Investigation and econometric application

Abstract

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.

Measuring industrial lumber production using nighttime lights: A focus study on lumber mills in British Columbia, Canada

“…Regardless of temporal scale, some degree of association exists between lumber production and NTL as they proved to be co-integrated and have unidirectional Granger causality. Previous literature has found co-integrated relationships between NTL and population [ 10 ], GDP [ 63 ] and electricity consumption [ 64 ]. All these measures are positively related to commodity production [ 65 ] so a similar relationship is to be expected.…”