Simulation and Prediction of Urban Land Use Change Considering Multiple Classes and Transitions by Means of Random Change Allocation Algorithms

Author(s)

Marques-Carvalho, Romulo ; de Almeida, Claudia Maria ; Escobar-Silva, Elton Vicente ; Alves, Rayanna Barroso de Oliveira ; Lacerda, Camila Souza dos Anjos

• Document type: Journal article
• Source: REMOTE SENSING; v. 15, n. 1, p. 29-pg., 2023-01-01.

Abstract

The great majority of the world population resides nowadays in urban areas. Understanding their physical and social structure, and especially their urban land use pattern dynamics throughout time, becomes crucial for successful, effective management of such areas. This study is committed to simulate and predict urban land use change in a pilot city belonging to the Sao Paulo Metropolitan Region, southeast of Brazil, by means of a cellular automata model associated with the Markov chain. This model is driven by data derived from orbital and airborne remotely sensed images and is parameterized by the Bayesian weights of evidence method. Several layers related to infrastructure and biophysical aspects of the pilot city, Sao Caetano do Sul, were used as evidence in the simulation process. Alternative non-stationary scenarios were generated for the short-run, and the results obtained from past simulations were statistically validated using a multiresolution "goodness-of-fit" metric relying on fuzzy logic. The best simulations reached fuzzy similarity indices around 0.25-0.58 for small neighborhood windows when an exponential decay approach was employed for the analysis, and approximately 0.65-0.95 when a constant decay and larger windows were considered. The adopted Bayesian inference method proved to be a good parameterization approach for simulating processes of urban land use change involving multiple classes and transitions. (AU)

• FAPESP's process: 20/09215-3 - Identification of pervious and impervious surface areas (ISA) using GEographic Object-Based Image Analysis (GEOBIA) and deep learning as input to drive a forecast model of urban growth
• Grantee: Cláudia Maria de Almeida
• Support Opportunities: Regular Research Grants
• FAPESP's process: 21/11435-4 - Scenario-based projections of future urban floods by means of a loose-coupling between a CA-based urban land use change model and a hydrodynamic model: a case study in São Caetano do Sul (SP)
• Grantee: Elton Vicente Escobar Silva
• Support Opportunities: Scholarships in Brazil - Doctorate