A geospatial approach for detecting and characterizing non-stationarity of land-change patterns and its potential effect on modeling accuracy

The non-stationarity of land-change patterns can potentially affect the accuracy of a spatially explicit land-change projection. Thus, methods for understanding this phenomenon are urgently needed. This paper presents a geospatial approach for detecting and characterizing the non-stationarity of land-change patterns and examining its potential effect on land-change modeling accuracy. It proposes two types of non-stationarity of land-change patterns, viz., non-stationarity+ and non-stationarity–. The former is characterized by an increase in the rate of land change, for example, non-built to built, across the calibration and simulation intervals along the gradient of an explanatory variable, for example, slope, while the latter is characterized by a decrease.

[1]  Paul Schot,et al.  Land use change modelling: current practice and research priorities , 2004 .

[2]  Henk J. Scholten,et al.  Modelling Land-use change; Progress and Applications , 2007 .

[3]  Eric Koomen,et al.  Comparing the input, output, and validation maps for several models of land change , 2008 .

[4]  R. Gil Pontius,et al.  Modeling the spatial pattern of land-use change with GEOMOD2: application and validation for Costa Rica , 2001 .

[5]  A. Veldkamp,et al.  Introduction to the Special Issue on Spatial modeling to explore land use dynamics , 2005, Int. J. Geogr. Inf. Sci..

[6]  Jianguo Wu,et al.  A gradient analysis of urban landscape pattern: a case study from the Phoenix metropolitan region, Arizona, USA , 2004, Landscape Ecology.

[7]  Hao Chen,et al.  Diagnostic tools to evaluate a spatial land change projection along a gradient of an explanatory variable , 2010, Landscape Ecology.

[8]  Martha M. Bakker,et al.  Changing relationships between land use and environmental characteristics and their consequences for spatially explicit land-use change prediction , 2012 .

[9]  A. Rompaey,et al.  Detecting and modelling spatial patterns of urban sprawl in highly fragmented areas: A case study in the Flanders–Brussels region , 2009 .

[10]  A. Bregt,et al.  Revisiting Kappa to account for change in the accuracy assessment of land-use change models , 2011 .

[11]  Yuji Murayama,et al.  Introducing new measures of accuracy for land-use/cover change modeling , 2012 .

[12]  E. Lambin,et al.  The emergence of land change science for global environmental change and sustainability , 2007, Proceedings of the National Academy of Sciences.

[13]  Robert Gilmore Pontius,et al.  Uncertainty in Extrapolations of Predictive Land-Change Models , 2005 .

[14]  B. Turner,et al.  Correction for Turner et al., Land Change Science Special Feature: The emergence of land change science for global environmental change and sustainability , 2008, Proceedings of the National Academy of Sciences.

[15]  A Veldkamp,et al.  Modelling land use change and environmental impact. , 2004, Journal of environmental management.

[16]  Richard Aspinall,et al.  Modelling land use change with generalized linear models--a multi-model analysis of change between 1860 and 2000 in Gallatin Valley, Montana. , 2004, Journal of environmental management.

[17]  M. Mcdonnell,et al.  The use of gradient analysis studies in advancing our understanding of the ecology of urbanizing landscapes: current status and future directions , 2008, Landscape Ecology.

[18]  Timothy Evans,et al.  A Review and Assessment of Land-Use Change Models Dynamics of Space, Time, and Human Choice , 2002 .

[19]  Yuji Murayama,et al.  Examining the potential impact of land use/cover changes on the ecosystem services of Baguio city, the Philippines: A scenario-based analysis , 2012 .

[20]  B. Pijanowski,et al.  Using neural networks and GIS to forecast land use changes: a Land Transformation Model , 2002 .