Remote sensing technology in mapping socio-economic divergence of Europe
Keywordscoastal region, coastalization, regional divergence, polarization, nocturnal illumination, remote sensing
AbstractMarine and ocean coasts traditionally act as natural growth poles for the humankind. Recent studies conducted by scholars from both natural and social sciences suggest that coastal zones accumulate population, agglomerate industries, attract entrepreneurs, and pull investments. The coastalization effect remains to be one of the defining factors of regional development around the globe and is projected to strengthen within a quarter of a century. Deepening socio-economic inequality and polarization between countries and regions despite of efforts taken with the convergence policies puts the ‘marine factor’ on research agenda. The study holds a comparative evaluation of the coastalization processes across the regions of Europe using the remote sensing technology and the statistical multivariate analysis for testing the correlation level of the results obtained. The research is based on a dataset for 413 regions of Europe featuring indicators for population density and Gross Regional Product (GRP) in Purchasing Power Parity (PPP) per sq.km. The regions are grouped into clusters depending on their socio-economic indicators and the intensity of nocturnal illumination. Results suggest that coastal and inland region types evenly distribute between clusters, with an average of 40% coastal. Observations over nocturnal illumination clearly indicate an extensive anthropogenic impact on European coasts, both northern and southern. However, their overall luminosity is inferior to inland territories. The study concludes with four patterns derived from a combined methodology of socio-economic indicators and remote sensing.
Banzhaf, E., Grescho, V., Kindler, A. (2009). Monitoring Urban to Peri‐Urban Development with Integrated Remote Sensing and GIS Information: A Leipzig, Germany Case Study. International Journal of Remote Sensing, 30(7), 1675-1696.
Barbier, E.B. et al. (2008). Coastal Ecosystem-Based Management with Nonlinear Ecological Functions and Values. Science, 319, 321-323. DOI: http://dx.doi.org/10.1126/Science.1150349
Baztan, J., Chouinard, O., Jorgensen, B., Tett, P., Vanderlinden, J.-P., Vasseur, L. (2015). Coastal Zones: Solutions for the 21st Century. 1st Edition. Amsterdam: Elsevier.
Bennett, M.M., Smith, L.C. (2017a). Advances in Using Multitemporal Night-Time Lights Satellite Imagery to Detect, Estimate, and Monitor Socioeconomic Dynamics. Remote Sensing of Environment, 192, 176-197.
Bennett, M.M., Smith, L.C. (2017b). Using Multitemporal Night-Time Lights Data to Compare Regional Development in Russia and China, 1992–2012. International Journal of Remote Sensing, 38(21), 5962-5991.
Burke, L. et al. (2001). Pilot Analysis of Global Ecosystems: Coastal Ecosystems. Washington: World Resources Institute.
Cauwels, P., Pestalozzi, N., Sornette, D. (2014). Dynamics and Spatial Distribution of Global Nighttime Lights. EPJ Data Science, 3(2). URL: Http://www.epjdatascience.com/content/3/1/2
Cetin, M., Musaoglu, N., Tanik, A. (2008). Multitemporal Assessment of Land-Use Change in a Rapidly Urbanizing Coastal Region in Turkey Using Remote Sensing. Environmental Engineering Science, 25(6), 917-928.
Chen, X., Nordhaus, W.D. (2011). Using Luminosity Data as a Proxy for Economic Statistics. Proceeedings of the National Academy of Sciences, 108(21), 8589-8594.
Cohen, J.E., Small. C., Mellinger, A., Gallup, J., Sachs, J., Vitousek, P.M., Mooney, H.A. (1997). Estimates of Coastal Populations. Science. New Series, 278(5341), 1211-1212.
Cracknell, P. (1999). Remote Sensing Techniques in Estuaries and Coastal Zones an Update. International Journal of Remote Sensing, 20(3), 485-496.
Crossland, C.J., Kremer, H.H., Lindeboom, H.J., Marshall Crossland, J.I., Le Tissier, M.D.A. (2005). Coastal Fluxes in the Anthropocene: The Land-Ocean Interactions in the Coastal Zone Project of the International Geosphere-Biosphere Programme. Berlin: Springer.
El-Sabh, M., Demers, S., Lafontaine, D. (1998). Coastal Management and Sustainable Development: From Stockholm to Rimouski. Ocean and Coastal Management, 39, 1-24.
Elvidge, C.D., Baugh, K.E., Anderson, S.J., Sutton, P.C., Ghosh, T. (2012). The Night Light Development Index (NLDI): A Spatially Explicit Measure of Human Development from Satellite Data. Social Geography, 7, 23-35.
Elvidge, C.D., Imhoff, M.L., Baugh, K.E., Hobson, V.R., Nelson, I., Safran, J., Tuttle, B.T. (2001). Night-Time Lights of the World: 1994-1995. ISPRS Journal of Photogrammetry and Remote Sensing, 56(2), 81-99.
Fedorov, G.M., Mikhaylov, A.S., Kuznetsova, T.Yu. (2017). The Influence of the Sea on the Development of the Economy and the Resettlement of the Baltic Region Countries. Baltic Region, 9(2), 4-18.
Ghosh, T., Anderson, S., Powell, R.L., Sutton, P.C., Elvidge, C.D. (2009). Estimation of Mexico’s Informal Economy and Remittances Using Nighttime Imagery. Remote Sensing, 1, 418-444.
Hinrichsen, D. (1996). Coasts in Crisis. Issues in Science and Technology, 12(4), 39-47.
Kurt, S. (2016). Analysis of Temporal Change Taking Place at the Coastline and Coastal Area of the South Coast of the Marmara Sea. Gaziantep University Journal of Social Sciences, 15(3), 899-924.
Makhnovsky, D. (2014). The Coastal Regions of Europe: Economic Development at the Turn of the 20th Century. Baltic Region, 4(22), 59-78.
Mellander, C., Lobo, J., Stolarick, K., Matheson, Z. (2015). Night-Time Light Data: A Good Proxy Measure for Economic Activity? Plos ONE, 10(10). DOI: http://dx.doi.org/10.1371/Journal.Pone.0139779
Pak, A., Majd, F. (2011). Integrated Coastal Management Plan in Free Trade Zones, A Case Study. Ocean and Coastal Management, 54, 129-136.
Rybnikova, N.A., Portnov, B.A. (2014). Mapping Geographical Concentrations of Economic Activities in Europe Using Light at Night (LAN) Satellite Data. International Journal of Remote Sensing, 35(22), 7706-7725.
Rybnikova, N.A., Portnov, B.A. (2016). Estimating Geographic Concentrations of Quaternary Industries in Europe Using Artificial Light-At-Night (ALAN) Data. International Journal of Digital Earth, 10(9), 861-878.
Ryznar, R.M., Wagner, T.W. (2001). Using Remotely Sensed Imagery to Detect Urban Change: Viewing Detroit from Space. Journal of the American Planning Association, 67(3), 327-336.
Salvador, R., Simões, A., Soares, C.G. (2015). Features of the European Maritime Clusters. 55th Congress of the European Regional Science Association: World Renaissance: Changing Roles For People and Places, 25-28 August 2015, Lisbon, Portugal.
Valev, E.B. (2009). The Problems Of Development and Interaction of Seaside Territories in Europe. Regionalnie Isslegovania, 1(22), 11-23.
Vallega, A. (1998). Agenda 21 of Ocean Geography. In: A. Vallega Et Al. (Eds.), Geography, Oceans and Coasts Towards Sustainable Development (pp. 17-116). Angeli, Milano.
Vitousek, P.M., Mooney, H.A., Lubchenco, J., Melillo, J.M. (1997). Human Domination of Earth’s Ecosystems. Science, 277(5325), 494-499.
Zeng, C., Zhou, Y., Wang, S., Yan, F., Zhao, Q. (2011). Population Spatialization in China Based on Night-Time Imagery and Land Use Data. International Journal of Remote Sensing, 32(24), 9599-9620.
Zhang, Q., Seto, K.C. (2013). Can Night-Time Light Data Identify Typologies Of Urbanization? A Global Assessment of Successes And Failures. Remote Sensing, 5(7), 3476-3494.
Zhao, N., Hsu, F.-C., Cao, G., Samson E.L. (2017). Improving Accuracy of Economic Estimations with VIIRS DNB Image Products. International Journal of Remote Sensing, 38(21), 5899-5918.
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