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Tropical Ecosystem Modeling

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Figure 1. Spider Monkeys in Tikal, Guatemala;

Tropical forests provide important habitat for a tremendous diversity of plant and animal species (Figure 1-2). Limitations in measuring and monitoring the structure and function of tropical forests has caused these systems to remain poorly understood. Remote-sensing technology has provided a powerful tool for quantification of structural patterns and associating these with resource use. Satellite and aerial platforms can be used to collect remotely sensed images of tropical forests that can be applied to ecological research and management. Our research has highlighted the resources available for tropical forest remote sensing and presents here an application to a neotropical forest located in the Petén region of northern Guatemala.


Balzotti, C.S., S.L. Petersen, R.E. Terry, A.K. Scherer, and C.Golden. 2010. Remote sensing as a tool for tropoical ecology. Geography Compass 4/8:993-1012.

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1. Land-change maps generated using Landsat imagery draped over an AIRSAR-generated digital elevation model. A = 1988, B = 2000, C = 2006, D = 2009, E = all years combined. 2. Land-change maps generated using Landsat imagery draped over an AIRSAR-generated digital elevation model. A = 1988, B = 2000, C = 2006, D = 2009, E = all years combined. 3. Land-change maps generated using Landsat imagery draped over an AIRSAR-generated digital elevation model. A = 1988, B = 2000, C = 2006, D = 2009, E = all years combined. 4. Land-change maps generated using Landsat imagery draped over an AIRSAR generated digital elevation model. A = 1988, B = 2000, C = 2006, D = 2009, E = all years combined. 5. Landchange maps generated using Landsat imagery draped over an AIRSAR-generated digital elevation model. A = 1988, B = 2000, C = 2006, D = 2009, E = all years combined.

Geospatial Modeling of Ancient Mayan Farming Practices


The ancient Mayan people have been extensively studied by archaeologists and soil scientists, but little is known about subsistence and ancient farming techniques that sustained its inhabitants. We conducted research that created a predictive model using geospatial techniques for ancient maize (Zea mays L.) agriculture in the Tikal National Park, Petén, Guatemala. This work has improved our understanding of settlement patterns and ecological potentials surrounding the site in a cost effective manner.

Balzotti, C., D.L. Webster, T.M. Murtha, S.L. Petersen, R.L. Burnett, and R.E. Terry. 2013. Modelling the ancient maize agriculture potential of landforms in Tikal National Park, Guatemala. International Journal of Remote Sensing 34:5868-5891.