A landscape epidemiology modeling framework is presented which integrates the simulation outputs from an established spatial agent-based model (ABM) of malaria with a geographic information system (GIS). For a study area in Kenya, five landscape scenarios are constructed with varying coverage levels of two mosquito-control interventions. For each scenario, maps are presented to show the average distributions of three output indices obtained from the results of 750 simulation runs. Hot spot analysis is performed to detect statistically significant hot spots and cold spots.

Agricultural census data and fieldwork observations are used to analyze changes in land cover/use intensity across Rondônia and Mato Grosso states along the agricultural frontier in the Brazilian Amazon. Results show that the development of land use is strongly related to land distribution structure. While large farms have increased their share of annual and perennial crops, small and medium size farms have strongly contributed to the development of beef and milk market chains in both Rondônia and Mato Grosso.

Rural livelihoods and the land systems on which they depend are increasingly influenced by distant markets through economic globalization. Place-based analyses of land and livelihood system sustainability must then consider both proximate and distant influences on local decision-making. Thus, advancing land change theory in the context of economic globalization calls for a systematic understanding of the general processes as well as local contingencies shaping local responses to global signals.

Land use patterns are the consequence of dynamic processes that often include important legacy issues. Evaluation of past trends can be used to investigate the role of path dependence in influencing future land use through a reference “business as usual” (BAU) scenario. These issues are explored with regard to objectives for woodland expansion in Scotland as a major pillar of climate change policy.

Miombo woodlands in Southern Africa are experiencing accelerated changes due to natural and anthropogenic disturbances. In order to formulate sustainable woodland management strategies in the Miombo ecosystem, timely and up-to-date land cover information is required. Recent advances in remote sensing technology have improved land cover mapping in tropical evergreen ecosystems. However, woodland cover mapping remains a challenge in the Miombo ecosystem.

While geographers and economists regularly work together on the development of land-use and land-cover change models, research on how differences in their modelling approaches affects the results is rare. Answering calls for more coordination between the two disciplines in order to build models that better represent the real world, we (two economists and a geographer) developed an economically grounded, spatially explicit, agent-based model to explore the effects of environmental policy on rural land use in New Zealand.

A landscape perspective is generally recognized as essential for conservation biology. The main underlying reason is that species respond to features of the landscape at various spatial scales, for example habitat area, connectivity, and matrix habitats. However, there is also an “historical” component of a landscape perspective, which has not received similar attention. The underlying reasons for historical effects are that humans have influenced landscapes during several millennia and that species and communities may respond slowly to land use change.

Values associated with scenic beauty are common “pull factors” for amenity migrants, however the specific landscape features that attract amenity migration are poorly understood. In this study we focused on three visual quality metrics of the intermountain West (USA), with the objective of exploring the relationship between the location of exurban homes and aesthetic landscape preference, as exemplified through greenness, viewshed size, and terrain ruggedness.

The identification of an appropriate justification for Agri-Environment-Climate (AEC) payments is a crucial issue in the new Rural Development Programme (RDP). Given the environmental importance of grasslands in Trentino (Italy), the Management Authority in charge of the RDP decided to integrate an approach based on Ecosystem Services (ES) into the calculation of AEC payments. The paper presents the methodology used for this approach as well as the preliminary results. The first step entails building a probabilistic model for the ES, named Sustainable Fodder Production.

This paper presents a method to optimise the calibration of parameters and land use transition rules of a cellular automata (CA) urban growth model using a self-adaptive genetic algorithm (SAGA). Optimal calibration is achieved through an algorithm that minimises the difference between the simulated and observed urban growth. The model was applied to simulate land use change from non-urban to urban in South East Queensland’s Logan City, Australia, from 1991 to 2001.

Mapping large areas for planning and conservation is a challenge undergoing rapid transformation. For centuries, the creation of broad-extent maps was the near-exclusive domain of expert specialist cartographers, who painstakingly delineated regions of relative homogeneity with respect to a given set of criteria. In the satellite era, it has become possible to rapidly create and update categorizations of Earth’s surface with improved speed and flexibility. Land cover datasets and landscape metrics offer a vast set of information for viewing and quantifying land cover across large areas.

Madagascar is renowned for the loss of the forested habitat of lemurs and other species endemic to the island. Less well known is that in the highlands, a region often described as an environmental “basket-case” of fire-degraded, eroded grasslands, woody cover has been increasing for decades. Using information derived from publically available high- and medium-resolution satellites, this study characterizes tree cover dynamics in the highlands of Madagascar over the past two decades.