4.6 Article

100 Years of Land-Use and Land-Cover Data: What Has Been the Effect of Spatial Planning in Coastal Land-Use and Land-Cover Change?

Journal

SUSTAINABILITY
Volume 15, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/su15097636

Keywords

land-use and land-cover change; land-use and land-cover change model; land-use plans; Municipal Master Plan; planning permits; sustainable development; urban sprawl

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This article proposes a reproducible method for assessing the effect of past planning practices and simulating future land-use and land-cover changes. By systematically comparing observed changes with planning rules, a database was constructed to quantify the actual effect of planning rules and identify other determinants of land-use evolution. The findings can help to simulate possible scenarios and guide future planning policies.
The Sustainable Development Goals require us to rethink spatial planning policies' effectiveness. This article proposes a reproducible method for assessing the effect of past planning practices and simulating future land-use and land-cover (LULC) changes with a Cellular Automata model. The originality of our approach is to systematically compare observed changes in LULC with the planning rules in force over almost a century of evolution. A quasi-exhaustive database was constructed at a very fine spatial resolution for the municipality of Portimao (Southern Portugal), including the location and changes of LULC categories, and the planning rules of the corresponding time period on nine dates between 1947 and 2018. The quantified measurement of the actual effect of planning rules enables us to identify other determinants of the evolution. Findings reveal that the policies established by the local government-which aimed to foster well-planned comprehensive urban areas-were not as effective as intended. The quantified discrepancies between planning recommendations and observed evolution help to simulate which LULC scenarios could be designed to reach the expected result in future planning policies. Our assessment method could be applied in other urban and tourist regions where land artificialization exerts strong pressure on the environment.

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