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A Cellular Automata Urban Growth Model for Water Resources Strategic Planning

Author(s): Dionysios Nikolopoulos; Konstantina Risva; Christos Makropoulos

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Keywords: Urban growth; Cellular Automata; Monte Carlo calibration; Urban surfaces identification

Abstract: The alarming rate of urbanization poses immediate problems to water resources management, mainly, but not limited to water supply, flood risk management, wastewater treatment and water quality control. Ideally, strategic planning of water systems should be fully aware of the prospects of future urban growth in order to maintain high reliability of services provided and satisfy customers in the long term. Typically, urban growth is handled in a static manner via the development of future scenarios based on previous urban planning studies. Generally, these scenarios focus solely on population increase and ignore the spatial allocation dynamics. Modern urban water strategic thinking needs to incorporate robust tools and methodologies in management practices, able to predict and quantify the outcome possibility of future urban growth. To cope with the aforementioned challenge, this study proposes a novel cellular automata urban growth model as well as, a supplementary remote sensing methodology to preprocess input data.

DOI:

Year: 2018

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