Complexity of urban systems necessitates the consideration of interdependency among various factors for land use change modeling and prediction. The objective of this study is to explore the applicability of computational neural networks in modeling urban sprawl and land use change coupled with geographic information systems (GIS) in Hilton Head Island, South Carolina. We are particularly interested in the capabilities of neural networks to identify land use patterns, to model new development, and to predict future change. A binary logistic regression model is estimated comparison.

This article solves and characterizes optimal decision rules to invest in irreversible land improvements conditional on land tenure insecurity. Economic model is a normative dynamic programming model with known parameter for the one period returns and transition equations. The decision rules are solved numerically conditional on alternative scenarios on the likelihood that the lease contract and, thus, farmer access to land is either renewed or expires. The model parameters represent Finnish soil quality and production conditions.

In the framework of the National Proyect: "Tipification, Cartography and Evaluation of Spanish Pastures" (INIA 00T00-037-C17-08) and Junta de Comunidades de Castilla-La Mancha, 2001-2004), promoted by the Spanish Society of Pastures Studies, "dehesas" areas are obtained depending on the uses of different cartographic sources. A comparative analyze has been carried out in Toledo province (Spain). Data used were obtained from the Spanish Forestry Map, the CORINE-LAND COVER 2000 proyect and Cadastral information.

En 1999, la FAO publiait la première version française du Thésaurus multilingue du foncier. Cette version avait surtout pour vocation d'être mise à l'épreuve du terrain, c'est-à-dire soumise aux critiques constructives tant des usagers à la recherche d'informations et d'éclairages nouveaux que des experts du foncier. En effet, sur le fond comme sur la forme, sont apparus un certain nombre de points forts mais aussi des lacunes, relevés depuis 1999 par l'équipe des rédacteurs et par de nombreux autres spécialistes du foncier.

In developing countries across the globe the impact of livestock on deforestation levels has
been profound. This paper explores the role of the cattle industry in household decision
making for small landholders in the Brazilian Amazon. Important inquiries raised in the
literature are addressed, including the determinants of the co-evolution of deforestation and cattle herds, the possibility of production specialization, and the role of cattle in household livelihoods. Panel data suggest that households have changed focus from crop