Theory, data, methods: developing spatially explicit economic models of land use change

Abstract

Questions of land use/land cover change have attracted interest among a wide variety of researchers concerned with modeling the spatial and temporal patterns of land conversion and understanding the causes and consequences of these changes. Among these, geographers and natural scientists have taken the lead in developing spatially explicit models of land use change at highly disaggregate scales (i.e. individual land parcels or cells of the landscape). However, less attention has been given in the development of these models to understanding the economic process -namely, the human behavioral componentthat underlies land use change. To the extent that researchers are interested in explaining the causal relationships between individual choices and land use change outcomes, more fully articulated economic models of land use change are necessary.This paper reviews some of the advances that have been made by geographers and natural scientists in developing these models of spatial land use change, focusing on their modeling of the economic process associated with land use change. From this vantage point, it is argued that these models are primarily "ad hoc," developed without an economic theoretical framework, and therefore are susceptible to certain conceptual and estimation problems. Next, a brief review of traditional economic models of land use determination is given. Although these models are developed within a rigorous economic framework, they are of limited use in developing spatially disaggregate and explicit models of land use change. Recent contributions from economists to the development of spatially explicit models are then discussed, in which an economic structural model of the land use decision is developed within a spatially explicit framework and from which an estimable model of land use change is derived. The advantages of this approach in terms of simulating policy scenarios and addressing econometric issues of spatial dependency and endogeneity are discussed. We use some specific examples from ongoing research in the Patuxent Watershed, Maryland, USA to illustrate our points. The paper concludes with some summary remarks and suggestions for further research.

Map of changes in landscape naturalness in the Fiastra and Salino catchment basins (central Italy)

“…Describing and analysing proportional change of different land cover types through time can prove highly valuable, not only for preserving biological diversity, but also for developing general landscape models useful for ecosystem management, environmental policies, and human welfare (Christensen et al, 1996;Franklin, 1993;Jobin, Latendresse, Grenier, Maisonneuve, & Sebbane, 2010). It is thought that landscape changes are driven by complex socioeconomic interactions (Forman, 1995;Irwin & Geoghegan, 2001;Wear & Bolstad, 1998;Zonneveld, 1995), but environmental factors (first of all, physical and bioclimatic ones) often influence land use as well (Blasi, Smiraglia, & Carranza, 2003). Analysis of environmental features that affect landscape ecology and dynamics can be performed by interpreting the factors that affect a territory in terms of different hierarchically determined spatio-temporal intervals (Allen & Starr, 1982;Catorci, Orsomando, & Silvi, 1995;King, 1977; ISSN 1744-5647 online # 2012 Andrea Catorci, Monica Foglia, Federico Maria Tardella and Alessandra Vitanzi http://dx.doi.org/10.1080/17445647.2012.668769 http://www.tandfonline.com O'Neill & King, 1998).…”

Integrating socio-economic and biophysical data to support water allocations within river basins: An example from the Inkomati Water Management Area in South Africa

“…geography and ecology), which are concerned with understanding and modelling the causes and consequences of land-use changes over space and time (Irwin and Geoghegan, 2001;Van Delden et al, 2007). The importance of space in influencing human behaviour is also acknowledged and accounted for in economic-related disciplines.…”

Evolution of land use-change modeling: routes of different schools of knowledge

“…The patterns utilize the estimation model's parameters in order to predict the spatial drivers of LUCC that can possibly occur within various scenarios imposed exogenously (Irwin and Geoghegan 2001). Some examples of hybrid models are: land use scanner (LUS) (Hilferink and Rietveld 1999), spatially explicit landscape event simulator (SELES) (Haase et al 2007), ProLand and UPAL (Sheridan et al 2007), the simulated land use-dependent on edge-effect externalities (SLUDGE) (Verburg et al 2006b), Dyna-CLUE (Verburg et al 2008), and monitoring land use changes (MOLAND) (Engelen et al 2007).…”