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Advisor(s)
Abstract(s)
In this chapter, a hybrid approach integrating cellular automata (CA), fuzzy logic,
logistic regression, and Markov chains for modelling and prediction of land-use and
land-cover (LULC) change at the local scale, using geographic information with
fine spatial resolution is presented. A spatial logistic regression model was applied
to determine the transition rules that were used by a conventional CA model. The
overall dimension of LULC change was estimated using a Markov chain model. The
proposed CA-based model (termed CAMLucc) in combination with physical variables
and land-use planning data was applied to simulate LULC change in Portimão,
Portugal between 1947 and 2010 and to predict its future spatial patterns for 2020
and 2025. The main results of this research show that Portimão has been facing
massive growth in artificial surfaces, particularly near the main urban settlements
and along the coastal area, and reveal an early and intensive urban sprawl over time.
Description
Keywords
Land-Use Land-Cover Coastal Area Modelling and prediction
Pedagogical Context
Citation
Faria de Deus, R., Tenedório, J. A., & Rocha, J. (2021). Modelling land-use and land-cover changes: a hybrid approach to a Coastal Area. In: J. A. Tenedório, R. Estanqueiro, & C. D. Henriques (Eds.), Methods and Applications of Geospatial Technology in Sustainable Urbanism (pp. 57-102). IGI Global. http://doi:10.4018/978-1-7998-2249-3.ch003
Publisher
IGI Global