Collaborative Research: Living with Deforestation: Analyzing Transformations in Welfare and Land Use on an Old Amazonian Frontier

Salisbury University, Salisbury MD

Investigators

Abstract

PROJECT ABSTRACT Living with Deforestation Analyzing Transformations in Welfare and Land Use on an Old Amazonian Frontier Tropical deforestation is a striking form of land cover transformation resulting in a complex mosaic of shifting land-use patterns across space and time. While research on forest conversion has been prolific, there has been relatively less attention given to long term impacts on the socio-economic welfare of frontier inhabitants along with the reciprocal effects of income and wealth on land use. Moreover, there is limited understanding of how post-deforestation trajectories are related to employment, migration, and inequality. These lacunae are directly related to the difficulty of obtaining the data required to track and evaluate these processes. Nevertheless, as the "old frontier" expands in tropical forest zones, it is critical to understand the dynamic economic and landscape processes that follow deforestation. This project will address these issues by adding a fourth round to a spatial panel of farm households, expanding the database to multiple scales with new secondary data, improving classification methods for remote sensing data, and modeling land use decisions and their consequences in the heavily deforested state of Rondônia, Brazil. A principle outcome of this project will be a public dataset that can be used by researchers from various disciplines to analyze questions related to the dynamic and spatial processes on forest frontiers. Specifically, spatially-referenced household panel survey data collected (from the same households and farm lots in four time periods) in the core study area of Ouro Preto do Oeste will be combined with several sources of data that cover an expanded study region: cadastral maps matched with satellite imagery to quantify land cover change; spatial data on biophysical factors, markets, and public infrastructure; and secondary data at multiple scales from official sources such as the current agricultural census. A second outcome will be improved land cover classification methods developed through traditional ground referencing and household-reported land use histories. Lastly, this research will draw more general conclusions regarding the co-evolution of land use and socio-economic welfare through combined analysis of complementary secondary data that expands the temporal and spatial range of the detailed household survey and linked remote sensing data.