Spatial modeling of agricultural land use change at global scale

Abstract

a b s t r a c tLong-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns.We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling communities.

Emerging Opportunities for Landscape Ecological Modelling

“…Such models have been developed to include demands for different land uses, allowing alternative future scenarios to be investigated [109]. There now exist very sophisticated and widely used models of land-use change that project future development of the land system on the basis of systemic equations describing relationships between specific drivers and observed changes [96,[110][111][112][113]. These form the basis of the scenario-based climate change projections of the Intergovernmental Panel on Climate Change [114].…”

Dynamics and determinants of land change in India: integrating satellite data with village socioeconomics

“…Our statistical modeling technique draws on our recent work (Meiyappan et al, 2014) and is common to land change modeling studies. We model the relationship between dependent and independent variables as a ''fractional'' binomial logit model (Text S1).…”

A philosophical case for process-based modelling of land use change

“…This approach is well-established and allows for the application of successful models across large geographical extents (Heistermann et al 2006;van Meijl et al 2006;Verburg et al 2008;Verburg and Overmars 2009;Meiyappan et al 2014). However, many other models take an alternative 'bottom-up' (or 'process-based') approach that focuses on basic processes and entities and allows system-wide developments to emerge from these, synthetically producing output data from local interactions.…”