There are few published examples of comprehensively validated large-scale land-use agent-based models (ABMs).
We test how these different landscapes affect the AOR-index of six model animal species in four different land use scenarios using an agent-based model framework (ALMaSS).
The parallel Schelling model was applied to the County of San Diego's one million household agents and one million housing unit agents using land use data and 2000 Decennial Census data.
Here, we present an agent based land use modelling framework designed to be run over large spatial extents and to be capable of accounting for relevant forms of human behaviour, variations in land use intensities, multifunctional ecosystem service production and the actions of institutions that affect land use change.
Results of this research are important as they may be integrated with the agent-based land use and landscape evolution models.
The use of more dynamic economic modelling approaches have been identified as the best means of estimating changes in land use, for example, equilibrium and agent-based modelling [116 118].
Intriguingly, no research exists on historical pastoralist land use and livestock management as agents of heterogeneity creating hotspots of nutrient fertility in the Serengeti landscape, despite this having been demonstrated in adjacent systems.
However, this approach to drought tolerance classification lacks a mechanistic understanding of what determines species' tolerance, as geographic distributions may be confounded by numerous other factors (e.g., successional change, land use, competitive interactions, and biotic agents).
By loosely coupling an agent based probabilistic land use change model with a hydrologic model, we investigated the consequences of present trends of urban growth to identify potential future hotspots of hydrological change across a watershed in central New Jersey undergoing suburbanization.
This paper presents an agent-based model of land use designed to explore the impacts of edge-effect externalities distance-dependent spatial externalities distance-dependentn.
This paper describes a spatially disaggregated, economic agent-based model of urban land use, which is named for its innovative feature of coupled housing and land markets (CHALMS).
