Rapid Land-Use Changes in the Agricultural Frontier of Brazil: Linking Remote Sensing, Ecosystems Modeling and Socioeconomic Analysis
Gillian
Laura
Galford, Brown University & The Ecosystems Center (MBL), ggalford@mbl.edu
(Presenting)
John
F
Mustard, Brown University, john_mustard@brown.edu
Jerry
M
Melillo, The Ecosystems Center (MBL), jmelillo@mbl.edu
David
Kicklighter, The Ecosystems Center (MBL), dkick@mbl.edu
Carlos
E. P.
Cerri, ESALQ, Universidade de Sao Paulo, cepcerri@esalq.usp.br
J.
Christopher
Brown, University of Kansas, jcbrown2@ku.edu
Jude
H
Kastens, University of Kansas, jkastens@ku.edu
Wendy
Jepson, Texas A&M, wjepson@geog.tamu.edu
Rapid land use change in the southwestern Amazon, particularly conversion of native vegetation to mechanized row-crop agriculture, has many ecological consequences, including changes in biogeochemical cycles. Quantifying patterns and magnitude of changes in row-crop agriculture, and subsequent intensification, are important boundary conditions for estimating regional-scale environmental impacts. We use five years of MODIS data to identify annual changes in row-crop agriculture, focusing on expansion and intensification of croplands in Mato Grosso and Rondônia with validation at local farms. After creating an EVI time series, we used annual phenology statistics to distinguish areas of cropland from other land covers. Results show increases in area of row-crop agriculture of 1% in Rondônia and 6% in Mato Grosso between 2001-2005. We created a wavelet-smoothed time series from which we can distinguish cropping types (single or double) and other curve parameters for distinguishing crop types. Between 2001-2005, farmers in Mato Grosso have intensified from single to double cropping on more than 11,000 km2, while in Rondônia, farmers have transitioned to double cropping on over 20 km2. These results of land cover and use change are now being used as boundary conditions for our biogeochemical model the Terrestrial Ecosystems Model (TEM). We are using TEM to estimate carbon dioxide and nitrous oxide emissions associated with the rapid conversion of native ecosystems and managed pastures to heavily industrialized agriculture. Additionally, we present the framework for integrating these remote sensing products in socioeconomic analysis of land conservation and agricultural intensification in mechanized agriculture.
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