Graduation date: 2007
Human activities are causing profound changes to the global environment, yet the
potential consequences of these changes on rising atmospheric carbon dioxide and
climate change are not well understood. Improving our understanding of these processes
requires an enhanced awareness of how global ecosystems are changing and how these
changes affect the global carbon cycle. Tropical ecosystems are considered crucial to the
global carbon budget, and more reliable data on the rates and extent of land cover and
land use changes in these ecosystems are needed to reduce the uncertainty of global
carbon flux estimates. Spatially explicit and repeatable observations from remotely
sensed data offer the best opportunity for monitoring the rapid changes taking place over
large spatial scales in tropical ecosystems.
As an important regional case study among global-wide efforts to understand land
cover and land use change and its effects on terrestrial carbon dynamics, the objective of
this research was to develop and test models based on high temporal frequency MODIS
data for monitoring land cover changes and modeling associated carbon flux over tropical
Central America. The first chapter introduces the issue involved with the development of
a methodology for scaling observations of changes in tropical forest cover to large areas
at high temporal frequency from coarse resolution satellite imagery. The approach for
estimating proportional forest cover change as a continuous variable was based on a
regression model that relates multi-spectral, multi-temporal MODIS data, transformed to
optimize the spectral detection of vegetation changes, to reference change data sets
derived from a Landsat data record for an individual study site. Chapter 2 reports on a
series of fundamental analyses designed to test and compare the utility of various MODIS
data and products for expanding the forest cover change models over multiple study sites
and time periods. The study described in Chapter 3 integrates satellite-derived data sets
on land cover and land use change with field-based parameters on terrestrial carbon
stocks and flux in a simple accounting model to track carbon dynamics associated with
these changes.