Retro-diagnosis methodology for land consumption analysis towards sustainable future scenarios: Application to a mediterranean coastal area

Land consumption is a good indicator to directly diagnose present and future imbalances in territories, and indirectly, possible issues associated to the management of other resources. Therefore, after reaching the target of standardizing urban research that makes it possible to build healthier and greener cities, the real challenge for the future is to make the leap from urban scale to regional scale and deploy these policies in an integrated manner, in so-called "smart territories".In that context, this paper presents a model of multidisciplinary analysis through indicators based in land consumption and transformation rates. The model, called GIS-LiDAR retrospective analysis, is implemented through territorial information tools in order to simulate and diagnose possible future imbalances based on past and current trends. This innovative methodology will be applied in a Spanish Mediterranean coastal area called the Campo de Cartagena, a territory with issues related to low-density urban sprawl, intensive agriculture and mass tourism coastal urbanization. This territory of high economic activity and with important environmental protected areas like the Mar Menor lagoon as well as complex interrelated phenomena will be "retrohistorically" diagnosed from the perspective of land transformation over 60 years. The method, designed to advance future scenarios and help planners in decision-making, will show dangerous current trends leading to imbalances in this area so that future planning can be implemented with smart (sustainable) criteria. (C) 2018 Elsevier Ltd. All rights reserved.

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Garcia-Ayllon S. Retro-diagnosis methodology for land consumption analysis towards sustainable future scenarios: Application to a mediterranean coastal area. Elsevier B.V., 2018. https://doi.org/10.1016/j.jclepro.2018.02.160

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Resource type Article
Date of creation 2024-11-05
Date of last revision 2025-01-22
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Metadata identifier 5d5ab145-7963-56d1-97e8-6e14e1b90f76
Metadata language Spanish
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High-value dataset category Earth observation and environment
ISO 19115 topic category biota
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Name of the dataset creator Garcia-Ayllon, S.
Name of the dataset editor Elsevier B.V.
Other identifier DOI: 10.1016/j.jclepro.2018.02.160
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Email of the dataset creator salvador.ayllon@upct.es
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