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Using Satellite Data on Nighttime Lights Intensity to Estimate Contemporary Human Migration Distances
Lund University, Department of Human and Economic Geography, Lund SE-223 62, Sweden.
Lund University, Department of Human and Economic Geography, Lund SE-223 62, Sweden.
Lund University, Department of Human and Economic Geography, Lund SE-223 62, Sweden.
University West, Department of Engineering Science, Division of Mathematics, Computer and Surveying Engineering. University of Gothenburg, Department of Economy and Society, .
2017 (English)In: Annals of the American Association of Geographers, ISSN 2469-4452, E-ISSN 2469-4460, Vol. 107, no 3, p. 591-605Article in journal (Refereed) Published
Abstract [en]

For well over a century, migration researchers have recognized the lack of adequate distance measures to be a key obstacle for advancing understanding of internal migration. The problem arises from the convention of spatially defining migration as the crossing of administrative borders. Because administrative regions vary in size, shape, and settlement patterns, it is difficult to tell how far movers go, raising doubts about the generalizability of research in the field. This article shows that satellite data on nighttime lights can be used to infer accurate measures of migration distance. We first use the intensity of nighttime lights to locate mean population centers that closely correspond to mean population centers calculated from actual population data. Until now, locating mean population centers accurately has been problematic, as it has required highly disaggregated population data, which are lacking in many countries. The nighttime lights data, which are freely available on a yearly basis, solve this challenge. We then show that this information can be used to accurately estimate migration distances. © 2017 by American Association of Geographers.

Place, publisher, year, edition, pages
Taylor and Francis Ltd. , 2017. Vol. 107, no 3, p. 591-605
Keywords [en]
border region; internal migration; light intensity; nightglow; satellite data
National Category
Economic Geography Human Geography
Research subject
SOCIAL SCIENCE, Human and economic geography
Identifiers
URN: urn:nbn:se:hv:diva-11912DOI: 10.1080/24694452.2016.1270191ISI: 000400045300003Scopus ID: 2-s2.0-85014545640OAI: oai:DiVA.org:hv-11912DiVA, id: diva2:1166122
Note

Published online: 28 Feb 2017                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    

Available from: 2017-12-14 Created: 2017-12-14 Last updated: 2022-11-01Bibliographically approved

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