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Simulating of Land Use Dynamics in Southeast Asia:
A Cellular Automaton Approach 2001 - 2005


The spatial pattern of village territories in Nang Rong district is complex.  Behind the spatial pattern are complex spatial processes.  Human decision-making takes place on a variety of spatial and temporal scales, and models are needed that integrate human dimensions at these space-time scales.


This project, using a temporally, substantively rich case study, is developing cellular automaton (CA) procedures to predict a spatially explicit model-based simulation of future land use and land cover change scenarios for Nang Rong, Thailand, and the broader region surrounding Nang Rong, including Cambodia, China, and Vietnam.

Scope of Work

The scenarios are based on empirically observed relationships in the following areas: a) history and spatial pattern of village settlement; b) road development, expansion of available vehicles, and changing geographic accessibility; c) electrification and the accompanying rise in TV viewership and consumerism; d) outmigration and urbanization, including the role of foreign investment in the broader region; e) global economic factors, including world cassava prices and the 1997 economic crisis; f) climate and monsoon history; g) spatial and temporal land titling and linkages to investment in various land uses; and h) basic demographic change, with an emphasis on changes in the number of households and their size/composition.  Results of the simulations will elucidate the spatial distribution and composition of LULCC.

The project exploits a rich collection of interlinked data sets for Nang Rong.  A collection of previously analyzed Landsat images (TM and MSS) dates to 1973.  Other remotely sensed data include AVHRR, SPOT, and SAR, as well as aerial photos dating to the 1950s.  Community and household level surveys are available for 1984, 1994, and 2000.  Out-migrants have been followed, and in-migrants added to the dataset.  Digital coverages showing roads, rivers, elevation, soil types and other spatial-thematic data are available within our GIS.  Daily precipitation and temperature data can be linked at the village level for 1984, 1994, and 2000, and at the household level for approximately 10,000 households in 2000.

Analytical Methods

The research draws heavily on recent work in remote sensing, demography, sociology, complexity theory, and related social and biophysical disciplines.  Both CA and agent-based models are used, and qualitative approaches back up and validate the models.  A CA model representing LULCC is being developed and validated using a time series of remotely sensed satellite and aircraft images from Northeast Thailand linked to spatially referenced biophysical and socioeconomic coverages as input data combined with "rules" derived from empirical analyses of those data.  The CA model will be used in dynamic simulations to explore LULCC as both cause and consequence.  After developing, calibrating, and validating the CA modeling scenarios for Nang Rong through the use of a deep satellite time series, spatially explicit LULCC patterns will be derived for the period 1950 - 2020.

Contribution to the Field

The spatial extent of the CA modeling and scenario evaluation will be expanded regionally by comparing Northeast Thailand to other sites in Northeast Cambodia, Southern China (Yunnan Province), and Northern Vietnam.  Using relationships, rules, and weights from these test sites, relative to Nang Rong scenarios, investigators simulate LULCC dynamics by perturbing CA-based Nang Rong simulations for conditions that represent alternate development processes that have occurred elsewhere within the Southeast Asia region.  These are countries with significant extant forest coverage, some of which has likely been preserved due to difficult political and social histories in the past 50 years.  While prediction is difficult, it seems that at least a sub-set of these countries is poised for substantial social and economic change, with resulting implications for LULCC and the carbon cycle.  See publications for examples of work emanating from this project.


This project is supported by a grant from the National Aeronautics and Space Administration.

  Last Modified: 03/22/2006 UNC Carolina Population Center