Remote sensing for monitoring regional carbon dynamics associated with land cover and land use change along the Mesoamerican Biological Corridor.

摘要

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.