Land use and cover change modelling and scenarios in the Upper Uruguay Basin (Brazil)

Marcos Wellausen Dias de Freitas, Pablo Muñoz, João Roberto dos Santos and Diógenes Salas Alves

Ecological Modelling, 2018, vol. 384, issue C, 128-144

Abstract: The objective of this work was to implement a spatial dynamics model to simulate land use and cover change (LUCC) in the period between 1986, 2002 and 2008 and to generate future scenarios until 2030 in an area characterized by multiple, competitive and complex LUCC processes. The model structure follows the majority of the existing LUCC models, being composed by six consecutive procedures: (a) calculation of transition demands, (b) definition and mapping of LUCC processes, (c) generation of transition probabilities maps, (d) spatial allocation of transitions, (e) calibration and validation of the simulation results, (f) generation of scenarios. The present model which is called LanDSCAM differs from other LUCC models reported in the literature in that: (a) LanDSCAM provision for the aggregation of multiple land use and cover transitions, simplifying LUCC modelling of study areas with multiple and complex land use and cover transitions; (b) a mandatory application of user-defined regions for transition demands calculation, transitions spatial allocation and model calibration, (c) introduction of specific procedures for spatial allocation of transitions divided on a deterministic cellular automata and a stochastic patch generation functions. The use of a theoretical approach for systems dynamics modelling allowed an overview on the different models of development by society. The LUCC model developed in this study provided contributions to the generation of simulations and scenarios in situations related to multiple, competitive and complex LUCC processes.

Keywords: Land use and cover change; Spatial dynamics model; Cellular automata model; Scenarios (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:384:y:2018:i:c:p:128-144

DOI: 10.1016/j.ecolmodel.2018.06.009

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