Land use change modelling: current practice and research priorities

By Peter H. Verburg, Paul P. Schot, Martin Dijst, A. Veldkamp. 2004

1,107 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Global and Planetary Change, Transportation

View Paper: https://www.semanticscholar.org/paper/3cea3baf9469411d11399496a9590e18b954cbe4

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Citations in the corpus

Simulating urban land use change by incorporating an autologistic regression model into a CLUE-S model (2015, background): “Scholars often use spatial change models to simulate and predict land use change in order to understand the reasons and progress of land use conversion (Liu et al., 2014; Koomen et al., 2008; He et al., 2005; Verburg et al., 2004).”
Prediction of Land Use and Land Cover Changes for North Sumatra, Indonesia, Using an Artificial-Neural-Network-Based Cellular Automaton (2019, background): “[3] also explicitly dealt with temporal dynamics and achieved a higher level of integration among disciplinary approaches and between models studying urban and rural land use changes.”
Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review (2003, background): “2002 ; Veldkamp and Lambin 2001 ; Verburg et al.”
Agricultural land abandonment and natural forest re-growth in the Swiss mountains: A spatially explicit economic analysis (2007, background): “Verburg et al. (2004) point out that: ‘‘aggregation of detailed scale processes does not straightforwardly lead to a proper representation of the higher-level process.”
Scenario Simulation and the Prediction of Land Use and Land Cover Change in Beijing, China (2015, methodology): “The CLUE-S model is preferred for addressing the spatial allocation of LULC change [14,31], but has some limitations in that it requires another mathematical model to calculate future land use demand.”
Linking Land Change with Driving Forces and Actors: Four Conceptual Models (2010, methodology): “Land change models are tools that support the analysis of the causes and consequences of land use changes in order to better understand the functioning of the land use system and to support land use planning and policy (Verburg et al. 2004).”
Forest Cover Change in Space and Time: Combining the Von Thunen and Forest Transition Theories (2007, positive): “There is a dangerous “fallacy of average” (Verburg et al., 2002), i.e., there are threshold effects and non-linearities which sometimes give surprising outcomes.”
Inductive pattern-based land use/cover change models: A comparison of four software packages (2014, neutral): “…(Silvestrini et al., 2011; Soares-Filho et al., 2012), rent and opportunity cost of public policies or timber industry (http://www. springerlink.com/content/100370/ Merry et al., 2009; Bowman et al., 2012; Giudice et al., 2012), the evaluation of the costs and bene ﬁ ts of reducing carbon…”
Spatial modeling of agricultural land use change at global scale (2013, methodology): “land use change models is evident from the wide range of existing modeling approaches and applications (see reviews by NRC, 2014; Heistermann et al., 2006; Verburg et al., 2004; Parker et al., 2003; Agarwal et al., 2002; Irwin and Geoghegan, 2001; Briassoulis, 2000; U.S. EPA, 2000).”