Catálogo de publicaciones - libros

Future land-use configurations provide valuable knowledge for policy makers and economic agents, especially under expected environmental changes such as decreasing rainfall or increasing temperatures. This chapter proposes an optimisation approach for modelling land-use change in which landscapes (land uses) are generated through the use of an evolutionary algorithm called . It is designed for a multiobjective function that aims at the minimisation of soil erosion and the maximisation of carbon sequestration, under a set of local restrictions. has been applied to a Mediterranean landscape, located in southern Portugal. The algorithm design and the results obtained show the feasibility of the generated landscapes, the appropriateness of the evolutionary methods to model land-use changes and the spatial characteristics of the landscape solutions that emerge when physical drivers have a major influence on their evolution.

Employment deconcentration has become a major issue on the policy and planning agenda in many metropolitan areas throughout the western world. In recent years, growing evidence indicates that in many developed countries, the deconcentration of employment - particularly of retail centres and offices - has become a key planning issue. This chapter uses the forecasting and simulation model in order to investigate some of the projected changes in land use, land value and sociodemographic characteristics of metropolitan areas undergoing employment deconcentration. The process of model application in the Tel Aviv metropolitan context is described. Two land-use scenarios of very different scales are simulated: a macro-level scenario relating to the imposition of an ‘urban growth boundary’ and a micro-level scenario simulating the effects of a shopping mall construction in different parts of the metropolitan area. The results are discussed in terms of the potential and constraints of microsimulation for analyzing metropolitan growth processes.

In contrast to typical urban regions dominated by a core city located in the region’s centre and a suburban fringe, the Austrian Rhine Valley, selected as the study area, can be described as a peri-urban region with some medium-sized centres and various rural villages, all developing in different ways. Thus, a simulation approach has to be applied that allows for different settlement growth and densification velocities in order to reach model results which come close to real land-use transitions. The urban growth model presented here is based on a multi-agent system which simulates location decisions of households and company start-ups within a cellular landscape driven by regional and local attractiveness patterns. The model has been applied to generate control runs for the past decade and validated by comparing its results with observed land-use changes at municipality level and at raster cell level. Scenario runs for the future have been conducted assuming suspended zoning regulations leading to a different actors’ behaviour.

It is increasingly recognised that land-use change processes are the outcome of decisions made by individual actors, such as land owners, authorities, firms and households. In order to improve the theoretical basis of land-use modelling and to represent land-use changes in a behaviourally more realistic way, we are developing (Predicting Urbanisation with Multi-Agents), a fully fledged multi-agent system of urban processes. will consist of various modules, representing the behaviours of specific actors. The land conversion module describes farmers’, authorities’, investors’ and developers’ decisions to sell or buy land and develop it into other uses. The households module describes households’ housing and work careers in relation to life cycle events (marriage, child birth, ageing, job change .) and also their daily activity patterns. The firms module includes firms’ demography and their related demand for production facilities leading to (re)location processes. The chapter describes the conceptual model, the first phase of operationalisation and initial results.

The evolution of cities at an urban-regional scale reflects complex relationships between ways in which urban structure develops in response to local decisions involving land development which is set within the more aggregate pattern of urban and regional structure. There is a mutual interaction between physical development and the urban hierarchy which is not often accounted for in the new wave of cellular models that have appeared in the last ten years. This chapter describes an implementation of a simulation model that is based on integrating these local and regional dynamics. We call it the and we develop the integration using two different cell-based modelling techniques: cellular automata (CA) and raster GIS. The model is implemented using an object-oriented programming approach, and after we describe its rudiments, albeit briefly, we show its application to real data from Chiang Mai, a major city in Thailand. Finally, this chapter indicates how the model can be used as a part of a spatial decision support system (SDSS) generating predictive outcomes that represent possibilities for implementing predictive and scenario-based applications in urban and regional planning and related fields.

Changes in land use may have important implications for nature, environment and water management. Thus, insights into future land-use patterns are needed for explorations of the future state of the environment and subsequent policy making. The Netherlands Environmental Assessment Agency, in co-operation with other partners, funded a consortium with the aim to invest in further development of the (). This system contains a cellular automata-oriented model and an economics-based model. Both models are discussed here as well as a number of their applications. This chapter ends with an evaluation of these applications and the model performance to date.

The Joint Research Centre (JRC) has implemented the following elements for a growing and representative sample of cities and urbanised regions: (1) high resolution spatial databases of land-use change over approximately 40 years, (2) urban sustainability indicators, and (3) a modelling framework enabling the implementation of hybrid land-use models representing urban regions ranging from the single, average-sized city to complex hierarchies of cities. The core of the latter framework enables the configuration of dynamic spatial models operating at a macro- and a micro-geographical scale. Both levels are intimately linked and permit an integral and detailed representation of the evolving spatial system. The models are complemented with: a series of spatial indicators, tools for interactive design, analysis and evaluation of policy measures or scenarios and a set of routines enabling the semi-automatic calibration and validation of the applications developed.

The (Conversion of Land Use and its Effects) model is one of the most widely applied models with approximately 30 applications in different regions of the globe focusing on a wide range of land-use change trajectories including agricultural intensification, deforestation, land abandonment and urbanisation. The model is a tool to better understand the processes that determine changes in the spatial pattern of land use and to explore possible future changes in land use at the regional scale. This chapter describes the functioning of the model and illustrates the potential of the model for scenario-based simulation of land-use change trajectories with two case studies, one which is a rural landscape in the eastern part of the Netherlands and one which is a strongly urbanized watershed surrounding Kuala Lumpur in Malaysia.

Urban growth has been replaced by decline of the urban fabric in many parts of Europe. Reasons for this shrinkage are to be found in processes of demographic change and migration in city regions. This chapter presents relevant indicators and a rule-based modelling approach to residential change and building demolition in Eastern Germany. The first part will focus on the research objectives and briefly discusses the urban decline phenomenon and the need for a new modelling approach in order to understand the current shifts in urban development. Besides this, relevant predictor variables for identifying spatial shrinkage and residential vacancy are discussed. Finally, their integration into a GIS-based spatially explicit model completes the chapter.

Land use is one of the major components influencing local hydrological characteristics. Future land use is thus important in studies that focus on the upcoming challenges for water management. This chapter describes two applications of the model on a national or larger scale, in which the scenario method is used to simulate future land-use patterns.