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To evaluate a specific form of resource management, for example, the maintenance of valuable cultural landscapes, the contributions of many different viewpoints must be considered. In this paper, a model for assessing and integrating the different aspects contributing to landscape evaluation is proposed. Some results of its use in landscape assessment in the Madrid region (central Spain) are discussed.The model takes into account five assessment dimensions which are considered to be independent—the ecological, productive, economic, social and cultural evaluative systems and it recognises and assumes conflicts and trade-offs between these components. The inclusion of the production system as an independent assessment dimension is original and is justified because it is the link that connects the ecological and economic systems. Since this dimension acts most directly on the ecosystem, the production system includes the attribute of ecological or strong (in the sense of [For the Common Good, Beacon Press, Boston, 1994]) sustainability.The evaluation method places special emphasis on defining a conceptual framework, and from this defines scenarios in comparison with which particular development models (landscape planning, resources management) can be evaluated. Seven scenarios, coming from a hypothetical, traditional sustainable scenario of resources management, are defined. One of these, the sound sustainable scenario, is defended as the only one viable in the long term, particularly in developing countries.This method was employed to evaluate the agricultural and natural landscape of the Madrid region municipalities. The multivariate approach adopted was based on the selection of indicator sets for each evaluative dimension. The structure of relationships among indicators was then analysed separately for each dimension and values assigned to the municipalities according to their position on the main axes of the multivariate analyses. Each municipality was assigned to one of the seven development scenarios by means of discriminant analysis. The approach’s greatest assets are its flexibility in the selection of the indicators and the efficacy in its monitoring and comparison of the different analysed cases once a rigorous conceptual framework was established.The paper discusses the conditions for the sustainability of the human activities and provides a method for evaluating and comparing scenarios of resources management. [Copyright &y& Elsevier]

The majority of wildfires in the Mediterranean Basin are caused directly or indirectly by human activity. Many biophysical and socioeconomic factors have been used in quantitative analyses of wildfire risk. However, the importance and effects of socioeconomic factors in spatial modelling have been given inadequate attention. In this paper, we use different approaches to spatially model our data to examine the influence of human activity on wildfire ignition in the south west of the Madrid region, central Spain. We examine the utility of choropleth and dasymetric mapping with both Euclidean and functional distance surfaces for two differently defined wildfire seasons. We use a method from Bayesian statistics, the Weights of Evidence model, and produce ten predictive maps of wildfire risk: (1) five maps for a two-month fire season combining datasets of evidence variables and (2) five maps for the four-month fire season using the same dataset combinations. We find that the models produced from a choropleth mapping approach with spatial variables using Euclidian and functional distance surfaces are the best of the ten models. Results indicate that spatial patterns of wildfire ignition are strongly associated with human access to the natural landscape. We suggest the methods and results presented will be useful to optimize wildfire prevention resources in areas where human activity and the urban–forest interface are important factors for wildfire ignition. [Copyright &y& Elsevier]