Improving Business-as-Usual Scenarios in Land Change Modelling by Extending the Calibration Period and Integrating Demographic Data

Land use and land cover change (LUCC) models are increasingly being used to anticipate the future of territories, particularly through the prospective scenario method. In the case of so-called trend or Business-as-Usual (BAU) scenarios, the aim is to observe the current dynamics and to extend them into the future. However , as they are implemented as baseline simulation in most current software packages , BAU scenarios are calibrated from a training period built from only two dates. We argue that this limits the quantitative estimation of future change intensity, and we illustrate it from a simple model of deforestation in Northern Ecuadorian Amazon using the Land Change Modeler (LCM) software package. This paper proposes a contribution to improve BAU scenarios calibration by mainly two enhancements: taking into account a longer calibration period for estimating change quantities and the integration of thematic data in change probabilities matrices. We thus demonstrate the need to exceed the linear construction of BAU scenarios as well as the need to integrate thematic and particularly socio-demographic data into the estimation of future quantities of change. The spatial aspects of our quantitative adjustments are discussed and tend to show that improvements in the quantitative aspects should not be dissociated from an improvement in the spatial allocation of changes, which may lead to a decrease in the predictive accuracy of the simulations. 2

[1]  Françoise Gourmelon,et al.  La géoprospective – Apport de la dimension spatiale aux démarches prospectives , 2014 .

[2]  Sandra Lowe,et al.  Classification Methods For Remotely Sensed Data , 2016 .

[3]  R. Gil Pontius,et al.  Land-cover change model validation by an ROC method for the Ipswich watershed, Massachusetts, USA , 2001 .

[4]  J. Mas,et al.  Benchmarking of LUCC modelling tools by various validation techniques and error analysis , 2014 .

[5]  Mario Hiraoka,et al.  Agricultural development in the upper Amazon of Ecuador. , 1980 .

[6]  Omar Doukari,et al.  Description and validation of a “non path-dependent” model for projecting contrasting urban growth futures , 2016 .

[7]  Tak Kuen Siu,et al.  Higher-Order Markov Chains , 2013 .

[8]  P. Jarrín-V.,et al.  Demografía y transformación territorial: medio siglo de cambio en la región amazónica de Ecuador/ Demography and territorial transformation: half a century of change in the Amazonian Region of Ecuador , 2017 .

[9]  M. Janssen,et al.  Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review , 2003 .

[10]  P. Dirmeyer,et al.  University of Nebraska-Lincoln DigitalCommons @ University of Nebraska-Lincoln Papers in Natural Resources Natural Resources , School of 2014 Land cover changes and their biogeophysical effects on climate , 2016 .

[11]  J. Toledano,et al.  A Short Presentation of the Land Change Modeler (LCM) , 2018 .

[12]  Lawrence A. Brown,et al.  Complementary Perspectives as a Means of Understanding Regional Change: Frontier Settlement in the Ecuador Amazon , 1992 .

[13]  Heiko Balzter,et al.  Methods to Quantify Regional Differences in Land Cover Change , 2016, Remote. Sens..

[14]  Tom H. Oliver,et al.  Interactions between climate change and land use change on biodiversity: attribution problems, risks, and opportunities , 2014 .

[15]  J. Mas.  Monitoring land-cover changes: A comparison of change detection techniques , 1999 .

[16]  Shashi Shekhar,et al.  Triangulated Irregular Network , 2008, Encyclopedia of GIS.

[17]  Martin Paegelow,et al.  LUCC Modeling Approaches to Calibration , 2018 .

[18]  Pablo De Grande,et al.  El formato Redatam , 2016 .

[19]  Robert Gilmore Pontius,et al.  Useful techniques of validation for spatially explicit land-change models , 2004 .

[20]  Basheer Abuelaish.  Modelling land change scenarios in the gaza strip and impacts on the environmental elements , 2017 .

[21]  Jean-François Mas,et al.  Modelling deforestation using GIS and artificial neural networks , 2004, Environ. Model. Softw..

[22]  R. Kitchin,et al.  Big data and human geography , 2013 .

[23]  B. Soares-Filho,et al.  dinamica—a stochastic cellular automata model designed to simulate the landscape dynamics in an Amazonian colonization frontier , 2002 .

[24]  Samuel H. Preston,et al.  The effect of population growth on environmental quality , 1996 .

[25]  Paul M. Mather,et al.  Classification methods for remotely sensed data, 2nd ed , 2016 .

[26]  Robert Walker,et al.  Household Life Cycles and Secondary Forest Cover Among Small Farm Colonists in the Amazon , 2002 .

[27]  Martin Paegelow,et al.  Inductive pattern-based land use/cover change models: A comparison of four software packages , 2014, Environ. Model. Softw..

[28]  Martin Paegelow,et al.  Impact and Integration of Multiple Training Dates for Markov Based Land Change Modeling , 2018 .

[29]  Eric F. Lambin,et al.  Causes and Trajectories of Land-Use/Cover Change , 2006 .

[30]  R. G. Pontlus.  Quantification Error Versus Location Error in Comparison of Categorical Maps , 2006 .

[31]  Ian Bracken,et al.  The integration of socioeconomic and physical resource data for applied land management information systems , 1993 .

[32]  Dolors Armenteras,et al.  Deforestation dynamics and drivers in different forest types in Latin America: Three decades of studies (1980–2010) , 2017 .

[33]  Martin Paegelow,et al.  Geomatic Approaches for Modeling Land Change Scenarios , 2018 .

[34]  J. Gareth Polhill,et al.  Agent-based land-use models: a review of applications , 2007, Landscape Ecology.

[35]  Robert Gilmore Pontius,et al.  A Suite of Tools for ROC Analysis of Spatial Models , 2013, ISPRS Int. J. Geo Inf..

[36]  D. Southgate,et al.  Deforestation, Agrarian Reform and Oil Development in Ecuador, 1964-1994 , 2013 .

[37]  R. Pontius,et al.  Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment , 2011 .

[38]  David García Álvarez.  Tesis doctoral: Aproximación al estudio de la incertidumbre en la modelización del cambio de usos y coberturas del suelo (LUCC) , 2018 .

[39]  E. Lambin,et al.  Predicting land-use change , 2001 .

[40]  Guilhem Juteau-Martineau,et al.  Ambiente, petróleo y vulnerabilidad política en el Oriente Ecuatoriano: ¿hacia nuevas formas de gobernanza energética? , 2014 .

[41]  P. Stern,et al.  People and pixels : linking remote sensing and social science , 1999 .

[42]  Jianchu Xu,et al.  Multiple Impacts of Land-Use/Cover Change , 2006 .

[43]  R. G. Davies,et al.  Global hotspots of species richness are not congruent with endemism or threat , 2005, Nature.

[44]  Qihao Weng,et al.  A survey of image classification methods and techniques for improving classification performance , 2007 .

[45]  H. Rodrigues,et al.  A Short Presentation of Dinamica EGO , 2018 .

[46]  Martin Paegelow,et al.  Geomatic Approaches for Modeling Land Change Scenarios. An Introduction , 2018 .

[47]  Ray Bromley,et al.  THE COLONIZATION OF HUMID TROPICAL AREAS IN ECUADOR , 1981 .

[48]  María Teresa Camacho Olmedo,et al.  Modelos de simulación espacio-temporal y teledetección: el método de la segmentación para la cartografía cronológica de usos del suelo , 2010 .

[49]  D. Carr,et al.  Proximate Population Factors and Deforestation in Tropical Agricultural Frontiers , 2003, Population and environment.

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

[51]  Ling Liu,et al.  Encyclopedia of Database Systems , 2009, Encyclopedia of Database Systems.

[52]  Chris W. Baynard,et al.  Roads, petroleum and accessibility: the case of eastern Ecuador , 2013 .

[53]  Richard E. Bilsborrow,et al.  Changes in Population and Land Use Over Time in the Ecuadorian Amazon. , 2004 .

[54]  Nicolas Maestripieri,et al.  Validation spatiale de deux modèles de simulation : l’exemple des plantations industrielles au Chili , 2013 .

[55]  J. W. Bruce,et al.  The causes of land-use and land-cover change: moving beyond the myths , 2001 .

[56]  Richard E Bilsborrow,et al.  Socioeconomic Drivers of Deforestation in the Northern Ecuadorian Amazon , 2006, Environmental management.

[57]  Jean-Christophe Castella,et al.  Combination of process-oriented and pattern-oriented models of land-use change in a mountain area of Vietnam , 2007 .