V. Diogo

Estimating demand for industrial and commercial land use given economic forecasts.

Current developments in the field of land use modelling point towards greater level of spatial and thematic resolution and the possibility to model large geographical extents. Improvements are taking place as computational capabilities increase and socioeconomic and environmental data are produced with sufficient detail. Integrated approaches to land use modelling rely on the development of interfaces with specialized models from fields like economy, hydrology, and agriculture. Impact assessment of scenarios/policies at various geographical scales can particularly benefit from these advances. A comprehensive land use modelling framework includes necessarily both the estimation of the quantity and the spatial allocation of land uses within a given timeframe. In this paper, we seek to establish straightforward methods to estimate demand for industrial and commercial land uses that can be used in the context of land use modelling, in particular for applications at continental scale, where the unavailability of data is often a major constraint. We propose a set of approaches based on ‘land use intensity’ measures indicating the amount of economic output per existing areal unit of land use. A base model was designed to estimate land demand based on regional-specific land use intensities; in addition, variants accounting for sectoral differences in land use intensity were introduced. A validation was carried out for a set of European countries by estimating land use for 2006 and comparing it to observations. The models’ results were compared with estimations generated using the ‘null model’ (no land use change) and simple trend extrapolations. Results indicate that the proposed approaches clearly outperformed the ‘null model’, but did not consistently outperform the linear extrapolation. An uncertainty analysis further revealed that the models’ performances are particularly sensitive to the quality of the input land use data. In addition, unknown future trends of regional land use intensity widen considerably the uncertainty bands of the predictions.

A utility-based suitability framework for integrated local-scale land-use modelling

Abstract Models that simulate land-use patterns often use either inductive, data-driven approaches or deductive, theory-based methods to describe the relative strength of the social, economic and biophysical forces that drive the various sectors in the land system. An integrated framework is proposed here that incorporates both approaches based on a unified assessment for local land suitability following a monetary, utility-based logic. The framework is illustrated with a hedonic pricing analysis of urban land values and a net present value assessment for agricultural production system in combination with statistics-based assessments of land suitability for other sectors. The results show that limited difference exists between the most commonly applied inductive approaches that use either multinomial or binomial logistic regression specifications of suitability. Land-use simulations following the binomial regression based suitability values that were rescaled to bid prices (reflecting relative competitiveness) perform better for all individual land-use types. Performance improves even further when a land value based description of urban bid prices is added to this approach. Interestingly enough the better fitting description of suitability for urban areas also improves the ability of the model to simulate correct locations for business estates and greenhouses. The simulation alternatives that consider the net present values for agricultural types of land use show the relevance of this approach for understanding the spatial distribution of these types of land use. The combined use of urban land values and net present values for agricultural land use in defining land suitability performs best in our validation exercise. The proposed methodology can also be used to incorporate information from other research frameworks that describe the utility of land for different types of use.

Land-Use Change in Portugal, 1990–2006: Main Processes and Underlying Factors

ABSTRACT This article studies the processes of land-use change in Portugal between 1990 and 2006 and analyses the effects of different driving forces in shaping land-use patterns during that period. While urbanization and the abandonment of agricultural land were the most prevalent processes between 1990 and 2000, concurrent processes of land abandonment and agriculture intensification seem to have predominated in recent years. Nevertheless, annual rates of change for all land-use change processes appear to be increasing overall, following a sharp increase in economic growth. The effect of driving forces in shaping land-use change tends to remain stable over time, but the deployment of new infrastructure and the gradual enforcement of spatial planning policies appear to be important factors in dynamically changing spatial patterns of land-use change.

Interactive Spatial Decision Support for Agroforestry Management

Forest managers, stakeholders and investors want to be able to evaluate economic, social and environmental information in order to improve the outcomes of their decisions and enhance sustainable forest management. We propose a spatial information system that provides: (1) an approach to identifying the most beneficial locations for agroforestry projects based on the biophysical properties and evaluate its economic, social and environmental impact; (2) a simulation environment that enables evaluation via a simple dashboard and with the opportunity to perform straight forward sensitivity analysis for key parameters; (3) a tool to inform prospective investors of the potential and opportunities for integrated forest management; (4) a 3D interactive geographic visualization of the economic, social and environmental outcomes to facilitate direct understanding, also by non-experts. The presented tool intends to inform investors and improve forestry management decision-making, integrating the value of environmental services and collaborative decision making of multiple decision makers and stakeholders.