This paper comprises some general issues about the natural and agricultural context in arid and semiarid Mediterranean pastures. We include most of our studies concerning to shrublands characteristics: composition, production and diversity; which have been developed in the oriental sector of Andalusia for more than 20 years. This work is concluded with some personal considerations about the changes in the land uses, mainly due to rural abandonment, and its incidence in the global change.

SWAT (Soil and Water Assessment Tool) represents a dynamic catchment modelling application that can be applied to any river basin and used to quantify the impact of land management practices on water quality over a continuous period. The objective of this study is to apply the Soil and Water Assessment Tool (SWAT) to model pathogen transport, simulate management practices affecting water quality and predict pathogen loads in Irish catchments.

Remote-sensing technology provides a powerful means for land use/land cover (LU/LC) monitoring at global and regional scales. However, it is more efficient and effective to combine remote-sensing measurements with a geographic information system (GIS) database and expert knowledge for change updating than to use remote-sensing technology alone. In this article, these different sources of information are integrated in the proposed framework, which is able to provide rapid updating of LU/LC information.

The last decade has seen a remarkable increase in the number of modeling tools available to examine future land-use and land-cover (LULC) change. Integrated modeling frameworks, agent-based models, cellular automata approaches, and other modeling techniques have substantially improved the representation of complex LULC systems, with each method using a different strategy to address complexity. However, despite the development of new and better modeling tools, the use of these tools is limited for actual planning, decision-making, or policy-making purposes.

In automatic/semiautomatic mapping of land use/cover using very high resolution remote-sensing imagery, the major challenge is that a single class of land use contains ground targets with varied spectral values, textures, geometries and spatial features. Here we present an object-oriented strategy for automatic/semiautomatic classifications of land use/cover using very high resolution remote-sensing data. The strategy consists of character detecting, object positioning and coarse classification, then refining the classification result step by step.

We present the first comprehensive multi-temporal analysis of land-cover change for California across its major ecological regions and primary land-cover types. Recently completed satellite-based estimates of land-cover and land-use change information for large portions of the United States allow for consistent measurement and comparison across heterogeneous landscapes. Landsat data were employed within a pure-panel stratified one-stage cluster sample to estimate and characterize land-cover change for 1973-2000.

Remote-sensing data for protected areas in northern Togo, obtained in three different years (2007, 2000, and 1987), were used to assess and map changes in land cover and land use for this drought prone zone. The normalized difference vegetation index (NDVI) was applied to the images to map changes in vegetation. An unsupervised classification, followed by classes recoding, filtering, identifications, area computing and post-classification process were applied to the composite of the three years of NDVI images.

An understanding of changes in Amazonian landscapes depends on documentation about alterations in land cover. This article highlights the efforts of the Large Scale Biosphere-Atmosphere Experiment in Amazônia (LBA) related to the topic. In particular, a longitudinal study has analyzed the social and biophysical dimensions of land use/land cover, using a multi-scalar georeferenced approach. The study areas represent a gradient of soil fertility in Amazônia and include distinct landscape mosaics, from the Amazon estuary and the Bragantina region to northeastern Rondônia.

1. The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. 2.

Land use activities change the natural functions of a watershed impacting the flow of water and water quality, and impair aquatic ecosystems. Optimal allocation of land use depends on attributes related to terrestrial and aquatic environments. A dynamic model that links land use, overland flow, suspended sediment, and an aquatic species is used to evaluate alternate land use policies. The dwarf wedge mussel that is classified as endangered in the region is used as an indicator species of aquatic health in a watershed in Massachusetts.

Land use/cover change (LUCC) is often the cumulative result of individual farmer's decisions. To understand and simulate LUCC as the result of local decisions, multi-agent systems models (MAS) have become a popular technique. However, the definition of agents is not often based on real data, ignoring the inherent diversity of farmers and farm characteristics in rural landscapes. The aim of this paper is to describe an empirical method that defines an agent typology and allocates agents into the different agent types for an entire region.