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Author Rybnikova, N.A.; Portnov, B.A. url  doi
  Title Using light-at-night (LAN) satellite data for identifying clusters of economic activities in Europe Type Journal Article
  Year 2015 Publication Letters in Spatial and Resource Sciences Abbreviated Journal Lett. Spatial & Resource Sci.  
  Volume 8 Issue 3 Pages 307–334  
  Keywords Remote Sensing; Economic activities; Clusters; Satellite photometry; Light-at-night; Europe; Nomenclature of Territorial Units for Statistics; C13; C38; O52; Economics  
  Abstract Enterprises organized in clusters are often efficient in stimulating urban development, productivity and profit outflows. Identifying the clusters of economic activities thus becomes an important step in devising regional development policies, aimed at the formation of clusters of economic activities in geographic areas in which this objective is desirable. However, a major problem with the identification of such clusters stems from limited reporting by individual countries and administrative entities on the regional distribution of specific economic activities, especially for small regional subdivisions. In this study, we test a possibility that missing data on geographic concentrations of economic activities in the European NUTS3 regions can be reconstructed using light-at-night satellite measurements, and that such reconstructed data can then be used for cluster identification. The matter is that light-at-night, captured by satellite sensors, is characterized by different intensity, depending on its source—production facilities, services, etc. As a result, light-at-night can become a marker of different types of economic activities, a hypothesis that the present study confirms. In particular, as the present analysis indicates, average light-at-night intensities emitted from NUTS3 regions help to explain up to 94 % variance in the areal density of several types of economic activities, performing especially well for professional, scientific and technical services (R^2=0.742−0.939), public administration (R^2=0.642−0.934), as well as for arts, entertainment and recreation (R^2=0.718−0.934). As a result, clusters of these economic activities can be identified using light-at-night data, thus helping to supplement missing information and assist regional analysis.  
  Address Department of Natural Resources and Environmental Management, Faculty of Management, University of Haifa, 31805, Mt. Carmel, Israel;  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes Approved no  
  Call Number IDA @ john @ Serial 1148  
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