A historical land cover map of the Cerrado region of Brazil based on Landsat MSS imagery

Stephen Hagen, Applied Geosolutions, LLC, steve.hagen@agsemail.com
Laerte Ferreira, LAPIG, Universidade Federal de Goiás - UFG, Goiania, Brazil, laerte@iesa.ufg.br
Michael Palace, CSRC-University of New Hampshire, michael.palace@unh.edu (Presenter)
Mercedes Bustamante, Departamento de Ecologia, Universidade de Brasília, Brasilia, Brazil, mercedesmcb@gmail.com

The Cerrado region of Brazil is one of the largest tropical savannas in the world and it is undergoing rapid development. Native savanna vegetation is being converted to agricultural land, and in the process the carbon and water cycles are significantly affected. To understand and account for the full magnitude of change, we need to have a clear picture of the landscape over time. Much work has been accomplished in mapping current land cover in this region (e.g. Probio), but less attention has been put on understanding and mapping land cover before the large scale conversion began. Here, we present results from our efforts to map land cover in the Cerrado in 1975, using imagery collected from Landsat Multispectral Scanner (MSS). We used the 2002 Probio land cover map together with DEM data within a maximum likelihood framework to classify the MSS imagery into several vegetation classes. These images have limited radiometric quality and provide significant challenges for classification, but they are only historical data with wide spatial coverage of the region. With a land cover map from the mid-1970s and today, we can better quantify changes in the carbon and water cycles, and prioritize areas for conservation.

Presentation Type:  Poster

Session:  Global Change Impact & Vulnerability   (Tue 11:30 AM)

Associated Project(s): 

• Keller, Michael: A Historical Reconstruction of Vegetation Change and a Carbon Budget for the Brazilian Cerrado Using Multiple Satellite Sensors and Historical Aerial Photography ...details
• Palace, Michael: Scaling Forest Biometric Properties Derived from High Resolution Imagery to the Amazon Basin using Moderate Resolution Spectral Reflectance Data ...details

Poster Location ID: 274