Multi-Temporal Built-Up Grids of Brazilian Cities: How Trends and Dynamic Modelling Could Help on Resilience Challenges?

Author:

Rufino IanaORCID,Djordjević SlobodanORCID,Costa de Brito HigorORCID,Alves Priscila Barros RamalhoORCID

Abstract

The northeastern Brazilian region has been vulnerable to hydrometeorological extremes, especially droughts, for centuries. A combination of natural climate variability (most of the area is semi-arid) and water governance problems increases extreme events’ impacts, especially in urban areas. Spatial analysis and visualisation of possible land-use change (LUC) zones and trends (urban growth vectors) can be useful for planning actions or decision-making policies for sustainable development. The Global Human Settlement Layer (GHSL) produces global spatial information, evidence-based analytics, and knowledge describing Earth’s human presence. In this work, the GHSL built-up grids for selected Brazilian cities were used to generate urban models using GIS (geographic information system) technologies and cellular automata for spatial pattern simulations of urban growth. In this work, six Brazilian cities were selected to generate urban models using GIS technologies and cellular automata for spatial pattern simulations of urban sprawl. The main goal was to provide predictive scenarios for water management (including simulations) and urban planning in a region highly susceptible to extreme hazards, such as floods and droughts. The northeastern Brazilian cities’ analysis raises more significant challenges because of the lack of land-use change field data. Findings and conclusions show the potential of dynamic modelling to predict scenarios and support water sensitive urban planning, increasing cities’ coping capacity for extreme hazards.

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development

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