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Manson > Research
Research
 

Global Environmental ChangeVietnam flooding

Global warming, the ozone hole, mass deforestation - these are a few ways in which we are affecting the earth and ourselves. While we have a general idea of the nature of global-scale change, we still face major hurdles in determining the local and regional impacts of this change. Land change in locales ranging from the Twin Cities of Minnesota to the southern Yucatan peninsular region. Bayesian and computational intelligence approaches give insight into human decision making and how it both contributes and responds to environmental change (paper reprints below).

Complexity Theory

Researchers from across the social, natural, and information sciences apply complexity theory to topics ranging from cultural transmission and economic growth to the braiding of rivers. While such a wide array of applications is heartening because it speaks to the utility of complexity theory, it is important to move beyond the hyperbole and critically examine the nature of complexity research. It is necessary to understand the evolution of complexity research, its advantages and drawbacks, and areas of further research (paper reprints below).

Land-use and Land-cover Change

Much of what makes global change important is the context given by land change ranging from tropical deforestation to urbanization. Techniques such as computational intelligence and agent based modeling allow us to combine local knowledge, ecological understanding, and societal context so we can better understand what is happening today and plan for a sustainable tomorrow (paper reprints below).

Geographic Information Science & Spatial Analysis and Modeling

GIS and SAM encompass spatial statistical, cartographical, mathematical, and computational techniques for the scientific study of physical, environmental and socioeconomic systems. Of particular interest are methods arising from the complexity sciences, such as agent-based models and cellular automata (paper reprints below ).

Reprints

Manson, S. M., H.A. Sander, D. Ghosh, J. M. Oakes, M. W. Orfield, W. J. Craig, T. F. Luce, E. Myott, S. Sun (2009). Parcel data for research and policy. Geography Compass 3 (2): 698–726. [PDF | DOI]

Messina, J. P., T. P. Evans, S. M. Manson, A. M. Shortridge, P. J. Deadman, and P. H. Verburg (2008). Complex systems models and the management of error and uncertainty. Journal of Land Use Science, 3 (1): 11-25. [DOI]

Parker, D. C., B. Entwisle, R. R. Rindfuss, L. K. VanWey, S. M. Manson, E. Moran,  L. An, P. Deadman,T. Evans, M. Linderman, S. M. Mussavi Rizi, and G. Malanson (2008). Case studies, cross-site comparisons, and the challenge of generalization: comparing agent-based models of land-use change in frontier regions. Journal of Land Use Science 3 (1): 41-72. [DOI]

Ghosh, D. and S. M. Manson (2008). Robust principal component analysis and geographically weighted regression: urbanization in the Twin Cities Metropolitan Area (TCMA). URISA Journal 20 (1): 15-25. [PDF]

Parker, D. C., D. G. Brown, J. G. Polhill, P. J. Deadman and S. M. Manson(2008). Illustrating a new 'conceptual design pattern' for agent-based models of land use via five case studies—the MR POTATOHEAD framework. In Agent-Based Modelling in Natural Resource Management. A. L. Paredes and C. H. Iglesias (eds). Upper Saddle River, New Jersey: Pearson Education, pp. 23-51.

Wu, J., M. Bauer, D. Wang andS. M. Manson (2008).  A comparison of illumination geometry-based methods for topographic correction of QuickBird images of an undulant area. ISPRS Journal of Photogrammetry and Remote Sensing 63: 223–236. [DOI]

Manson, S. M. (2008). Does scale exist? An epistemological scale continuum for complex human-environment systems. Geoforum 39 (2): 776-788. [PDF | DOI]

Manson, S. M. and T. Evans (2007). Agent-based modeling of deforestation in southern Yucatán, Mexico, and reforestation in the Midwest United States. Proceedings of the National Academy of Sciences 104 (52): 20678–20683. [PDF | DOI]

Sander, H. and S. M. Manson (2007). Heights and locations of artificial structures in viewshed calculation: how close is close enough? Landscape and Urban Planning 82(4): 257-270. [DOI]

Manson, S. M. (2007). Challenges in evaluating models of geographic complexity. Environment and Planning B 34(2): 245-260. [PDF | DOI]

Evans, T. and S. M. Manson (2007).  Space, complexity, and agent-based modeling (Invited editorial). Environment and Planning B 34(2): 196-199. [PDF, EPB site]

Manson, S. M. (2006). Catastrophe Modeling: A New Approach to Managing Risk (Book Review). .Journal of Regional Science 46(4): 794–796.

Manson, S. M. and M. Bauer (2006).  Changing Landscapes in the Twin Cities Metropolitan Area. CURA Reporter 36(3): 3-11. [PDF, CURA site]

Manson, S. M. (2006).  Bounded rationality in agent-based models: experiments with evolutionary programs. International Journal of Geographic Information Science (20) 9: 991-1012. [PDF | DOI]

Manson, S. M. (2006). Global Complexity (Book Review). Progress in Human Geography. 30(3): 420-422.

Manson, S. M. (2006). Land use in the Southern Yucatan Peninsular Region of Mexico: scenarios of population and institutional change. Computers, Environment, and Urban Systems 30 (3): 230-253. [PDF | DOI]

D. O'Sullivan, Manson, S. M., Messina, J. and Crawford, T. (2006). Space, place and complexity science (Invited editorial). Environment and Planning A 38(4): 611-617. [PDF, EPA site]

Manson, S. M. and D. O'Sullivan (2006). Complexity theory in the study of space and place. Environment and Planning A 38(4): 677-692. [PDF | DOI]

Manson, S. M. , J. Geoghegan and B. L. Turner, II (2006). State of the art in describing future changes in ecosystem services: forecasting changes in land use and land cover. In Millennium Ecosystem Assessment: Ecosystems and Well-Being (Volume 2: Scenarios). H. Mooney and A. Cropper (eds). Geneva, Switzerland: Island Press, pp. 74-76.

Crawford, T., Messina, J., Manson, S. M., and D. O'Sullivan. (2005). Complexity science, complex systems, and land use research (Invited editorial). Environment and Planning B (32)6: 792-797. [PDF, EPA site]

Manson, S.M. (2005). Agent-based modeling and genetic programming for modeling land change in the Southern Yucatan Peninsular Region of Mexico. Agriculture, Ecosystems and Environment 111(1): 47-62. [PDF | DOI]

Manson, S. M. (2004). The SYPR integrative assessment model: complexity in development. Integrated Land-Change Science and Tropical Deforestation in the Southern Yucatán: Final Frontiers. B. L. Turner, II, D. Foster and J. Geoghegan. Oxford, United Kingdom, Clarendon Press: 271-291. [PDF]

Brown, D. G., Walker, R., Manson, S. and Seto, K. 2004. Modeling land use and land cover change. In Land Change Science: Observing, Monitoring, and Understanding Trajectories of Change on the Earth's Surface. Eds. G. Gutman, A. Janetos, C. Justice, E. Moran, J. Mustard, R. Rindfuss, D. Skole and B. L. Turner, II. (Dordrecht, Netherlands, Kluwer Academic Publishers) pp. 395-409.

Manson, S. M . (2004). Evolutionary Modeling of Spatial Information (Book Review). Journal of Artificial Societies and Social Simulation 7(2): R1. [PDF - WWW]

Manson, S. M. (2004). Self-Organization and the City (Book Review). Political Geography 23(8): 1063-1065.

Manson, S. M. (2003). Validation and verification of multi-agent models for ecosystem management. In Complexity and Ecosystem Management: The Theory and Practice of Multi-Agent Approaches. ed. M. Janssen. Northampton, Massachusetts, Edward Elgar Publishers: 63-74.[PDF]

Manson, S. M. (2003). Epistemological possibilities and imperatives of complexity research: a reply to Reitsma. Geoforum 34 (1): 17-20.

Parker, D. C., S. M. Manson, M. Janssen, M. J. Hoffmann and P. J. Deadman (2003). Multi-agent systems for the simulation of land use and land cover change: a review. Annals of the Association of American Geographers 93 (2): (316-340). [PDF | DOI]

Parker, D. C., S. M. Manson, M. A. Janssen, M. J. Hoffmann and P. Deadman (2002). Multi-Agent Systems for the Simulation of Land-Use and Land-Cover Change: A Review. Bloomington, Indiana, Center for the Study of Institutions, Population, and Environmental Change, Indiana University. CIPEC Working Paper CW-01-05. [PDF]

Manson, S. M., S. J. Ratick and A. R. Solow (2002). Decision making and uncertainty: Bayesian analysis of potential flood heights. Geographical Analysis 34 (2): 112-129.  [PDF]

Manson, S. M. (2002). Tools for Land Use Analysis on Different Scales with Case Studies for Costa Rica. System Approaches for Sustainable Agriculture Development (Book Review). Journal of Artificial Societies and Social Simulation 4 (3): R1. [PDF - WWW]

Manson, S. M. (2001). Simplifying complexity: a review of complexity theory. Geoforum 32 (3): 405-414. [PDF | DOI]

Turner II, B. L., S. Cortina Villar, D. Foster, J. Geoghegan, E. Keys, P. Klepeis, D. Lawrence, P. Macario Mendoza, S. M. Manson, Y. Ogneva-Himmelberger, et al. (2001). Deforestation in the southern Yucatan peninsular region: an integrative approach. Forest Ecology and Management 154(3): 353-370.

Manson, S. M<. (2000). Agent-based dynamic spatial simulation of land-use/cover change in the Yucatán peninsula, Mexico. Fourth International Conference on Integrating GIS and Environmental Modeling (GIS/EM4), Banff, Alberta. [PDF]

Manson, S. M. (1999). Principles of Geographic Information Systems : Spatial Information Systems and Geostatistics. Economic Geography 75(4): 422-423.

 

 

 

 

 
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