Graduate Thesis Or Dissertation
 

Fighting and Foliage: Land System Dynamics in the Colombian Andes-Amazon region

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/3n2045787

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  • In the Colombian Amazon there has been a complex interplay of rebel groups’ control over land, drug trafficking, and absence of the Government of Colombia. Here, I use satellite remote sensing, ethnographic research and statistical models to provide insights into causal effect and causal mechanisms of land change and economic well-being that affect conflict areas around the world. Chapter 1 utilizes near-real-time satellite remote sensing and field interviews to document an alarming rise in illegal deforestation activities – particularly in Protected Areas in Colombia’s Amazon and deeper into the Amazon watershed region – triggered by socio-political changes emerging after the peace agreement between the Colombian Government and Revolutionary Armed forces of Colombia (FARC). This work highlights how a rapid shift in the institutional framework affects landscape change at a rate never seen before. Chapter 2 examines whether individual hot spots of violent conflict within Colombia Amazon led to significant localized land change patterns, such as forest regeneration of developed areas or agriculture expansion of undeveloped areas. It also presents regional spatiotemporal detailed analysis covering conflict and the post-conflict periods. This chapter is a novel combination of statistical theories of social science with technical mapping of land change during the last 30 years. Chapter 3 evaluates the hypothesis that illicit land activities (coca and illegal cattle ranching) lead to deforestation. Contrary to the prevailing narrative that coca farming is the initial spearhead of deforestation, we find that coca farming is relatively persistent, but that clearing for new cattle grazing has increased exponentially and is now pushing deeper into the Amazon watershed. This type of clearing is not driven by small landholders, but ultimately by wealthier actors with future expectations of capitalized new lands. This chapter links observable patterns of illicit activities with the specific processes that drive them. We corroborate these linkages using deep learning algorithms (convolutional neural networks applied to time-series satellite imagery) and associated them with policy regimes (i.e., war on drugs, recent peace accord).
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  • Pending Publication
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  • 2020-12-07 to 2022-01-07

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