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  • Water Production Connections

Transitions on an Amazonian Frontier - Impressions

By Jamison Douglas

The study region for this project includes 17 municipalities in Rondonia Brazil, a state located in the heart of the Amazon but in a region of this majestic forest that is heavily deforested. When people think about the Brazilian rainforest, their imaginations tend to drift to romanticized images of lush, verdant tropical foliage filled with towering trees, creeping vines and orchids, colorful species of noisy, lyrical birds and chattering monkeys that are bathed by daily thunderstorms. However, for the faculty and students conducting research in this region the image is much different: cattle pastures reminiscent of west Texas are bisected by dusty, unpaved roads and barbed wire fences extending across newly exposed rolling hills and rocky outcrops that are parched by a strong dry season tropical sun. this article outlines field work undertaken in 2009 that has led to the research questions we are addressing today.

Forest Conversion in Brazil

Tropical deforestation is a striking form of land cover transformation that has attracted the attention of researchers across multiple disciplines seeking to explain and predict the progression of the deforestation frontier. Brazil has the largest, contiguous area of dense tropical forest in the world, and despite numerous policy initiatives to slow deforestation, the region continues to experience relatively high rates of clearing each year. Nearly 30 percent of the original forest found within the Brazilian Amazon has been deforested. Researchers, politicians and citizens within Brazil and abroad are concerned about the loss of biodiversity and impacts on climate change. Global media continues to expose the public to frequent images of forest fires and anthropogenic alterations of the landscape. But what is really going on and why are people still deforesting their land? To better understand these influences and the expected impact on rainfall, the research team began investigating the drivers at the beginning of the current century by collecting survey data from households and merging these with spatial and remote sensing data.

The Household Surveys
During our last field campaign in 2009, the typical field day began with a breakfast meeting at 6:30 am. The survey team were allocated their assignments of approximately 10-20 surveys each in this meeting. For the first time in this long-term project, surveys were administered via Computer Aided Personal Interviewing (CAPI) software on ruggedized laptops instead of using pen and paper. The survey management team was responsible for aggregating and storing the data and running error check algorithms, to maintain internal consistency across interviewers.

Geographical Analysis

The geospatial team collected biophysical and infrastructure spatial data from throughout the study area. These data were collected via global positioning systems (GPS) and coordinated with additional regional-scale data sources, including cadastral maps and satellite imagery in a geographic information system (GIS). This process linked survey data spatially with the remote sensing images classified. Data collected in the field help to refine pixel classification and enable a review of the accuracy of previous classifications. The geospatial team also spent time in the field mapping local roads and improving the positional accuracy of the satellite images relative to each surveyed lot.

Regional Data Collection

Finally, the regional data acquisition team met with government agencies, health organizations, education institutions and other potential sources of secondary data to compare the primary data being collected in the study region to regional and state data. The team uses both these secondary data sources and primary data sources such as previous surveys in the study region, to place the research in context and add to its credibility.

Combining the Data

The data collected by the three teams were combined to generate an extensive overview of current deforestation trends and to illustrate how the individual as well as the individual’s land is affected over time. These analyses offer insights into the causal processes and agents of deforestation and produce policy recommendations given concrete, empirical insight.

Given the team’s on going multidisciplinary research, they hope to use data collected from households, satellites, and secondary sources the objective in 2009 was to present a more comprehensive picture of the human side of forest clearing by linking local decision-making to regional and basin-wide patterns. Using first-person accounts in the form of resident interviews and technology-based visualizations employing GPS, GIS and satellite imagery, the team hopes to create a multi-modal representation of Amazonian deforestation phenomena.


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