Abstract
Urban sprawl heavily affects coastal areas worldwide, posing threats to the environment and resulting in unsustainable urban growth patterns. This is particularly true in the Mediterranean Region, where coastal and especially insular territories constitute distinct cases of fragile ecosystems, affected by long-lasting mass tourism development trends. This research proposes a methodology for monitoring urban sprawl in coastal areas. High-resolution data for built-up areas are used in this respect, provided by the Global Human Settlement Layer (GHSL). Spatial data are processed using GIS technology; and FRAGSTATS software is used to calculate spatial metrics that quantify density, clustering, geometrical complexity and dispersion of the built environment. The proposed methodology is applied to a case study in Crete, a remarkable example of Mediterranean island community, heavily affected by mass tourism development. Urban growth trends in the period 1975–2014 are explored in this respect; and urban sprawl patterns are analyzed at a disaggregated level along the northern coastal zone, using recent GHSL data based on Sentinel-2 images (period 2017–2018). Using a combination of principal component analysis and cluster analysis, different typologies are identified and zones mostly affected by urban sprawl are highlighted.
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Acknowledgements
The present research work is part of the postdoctoral research co-financed through the Greek State and EU (European Social Fund) accomplished under the framework of the Program “Workforce development, Education and continuing education”, within the act “Financial assistance for Postdoc researchers – Cycle B”, (MIS 5033021), led by IKY (State Scholarships Foundation of Greece).
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Lagarias, A., Stratigea, A. (2021). High-Resolution Spatial Data Analysis for Monitoring Urban Sprawl in Coastal Zones: A Case Study in Crete Island. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12958. Springer, Cham. https://doi.org/10.1007/978-3-030-87016-4_6
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DOI: https://doi.org/10.1007/978-3-030-87016-4_6
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