Simulating Complexity in a Dynamic Landscape: Land-Use and Land-Cover Change in Nang Rong, Thailand

Understanding the role of individual, collective, and institutional human behavior is fundamental to an understanding of land-use and land-cover change. Human dimensions have been difficult to model, however, because of the need to incorporate the stochastic behavior of social units at multiple levels of social organization, the need to make human actions spatially explicit, and the need to be more explicit about what humans are doing and why, particularly at specific locations for specific time periods. This project examines the consequences of land-use and land-cover change in the Nang Rong district of northeast Thailand. The overall goal of this project is to develop a better understanding of human behavior in the transformation of the Earths surface. Nang Rong serves as an appropriate laboratory for this purpose. The data available for Nang Rong are unique in their coverage of social, biophysical, and spatial domains and include three panels of individual, household, and village-level data, which were collected in 1984, 1994, and 2000. A time series of remotely sensed data that includes aerial photography (beginning in 1954) and satellite data (beginning in 1972) also has been collected for the district along with a digitized base-map and a collection of derived GIS thematic coverages. Verification data has been obtained during multiple field visits, and qualitative interviews will be conducted as part of the project. The projects first aim is to develop, calibrate, and validate a cellular automaton (CA) model representing land use and land cover change over the past half century in Nang Rong. CA models provide a formal framework for investigating the behavior of complex, extended systems. The CA model to be developed in this project focuses on the spatial and temporal dynamics of deforestation, agricultural extensification, and plant succession. Rules for the CA modeling will be derived from formal theories of growth and change, and models will incorporate the results of empirical analyses. The second aim of the project is to use the CA model in dynamic simulations to explore land-use and land-cover change as both cause and consequence of patterns of village settlement in a frontier environment; road development and increases in vehicular traffic; migration and household formation as the frontier closes; land tenure; monsoonal variability; agricultural intensification; cooperative use of the hydrological layer; major shifts in world markets; electrification; the rise in television ownership; and the spread of consumerism. Results of the simulations will be used to examine the spatial distribution as well as composition of land-use and land-cover change, and they will be used to evaluate trajectories for a sample of pixels and other spatial units. The projects third aim is to package the simulations into a multimedia GIS database. This database, together with other materials explaining the situation, will be adapted to and tested for use at the secondary and college levels and then made publicly available via the Internet. Through the conduct of this project, the challengers of understanding the role of human behavior in land-use and land-cover change will be met through the development, elaboration, and evaluation of the cellular automaton (CA) modeling described above for the Nang Rong district. The temporal depth, areal extent, and grain size of the social surveys, remote images, and GIS data afford a unique capability to examine complex systems operating within a complexity theory context. The coupling of the simulation power of CA modeling, with its ability to allow for nonlinearities and feedbacks, and a rich set of empirically derived relationships will provide valuable new insights into the complex interactions among natural and human systems. The project also will facilitate collaborations between U.S. scientists and scientists at Mahidol University in Thailand. This project is an award emanating from the FY 2001 special competition in Biocomplexity in the Environment focusing on the Dynamics of Coupled Natural and Human Systems.