Dynamic Spatial Simulation Modeling of the Population-Environment Matrix in the Ecuadorian Amazon
This research uses multithematic and spatially explicit data combined from a longitudinal socioeconomic and demographic survey conducted in 1990 and 1999, GIS coverages of resource endowments and geographic accessibility, and a classified Landsat Thematic Mapper (TM) satellite time series. The goal was to combine such data with expert knowledge, a set of analytic results, and dynamic modeling approaches to describe, explain, and explore the causes and consequences of land use and cover change (LUCC) in the northern Oriente region of the Ecuadorian Amazon. First, a cellular automaton (CA) model representing LUCC was developed using a time series of remotely sensed Landsat TM images for a 90 000-ha intensive study area within the region and calibrated using alternative images from the time series. The classified images were linked to spatially referenced biophysical and socioeconomic coverages used as input data, and then combined with \'rules\' derived from empirical analyses. Second, the CA model was used in dynamic simulations to explore LUCC as both causes and consequences of (a) road development, (b) agricultural extensification and land abandonment, (c) major shifts in world markets and crop prices, and (d) urban expansion of the central city within the region. Finally, complexity theory was explored within the spatial and temporal dynamics associated with population-environment interactions, particularly, deforestation, urbanization, and subsistence and commercial cultivation of agricultural crops on lands made accessible by petroleum-company-built roads and the corresponding in-migration of spontaneous colonists beginning in the late 1960s. This research contributes to the study of population-environment interactions in a frontier environment, and examines how dynamic and complex systems can be modeled using CA-based spatial simulations.