Remote Sensing biomass of forested ecosystems: Modelling the carbon cycle of the Iztaccíhuatl - Popocatépetl National Park, México

Increases in the concentration of carbon dioxide, as well as of other so-called greenhouse gases, in the Earth’s atmosphere will lead to climate change. So far, policy responses to limit the effects of climate change have focused on the reduction of emissions of greenhouse gases at source. Another possibility would be to enhance the capacity of ecosystems to act as carbon sinks, such as by increased afforestation, in order to reduce carbon dioxide (CO2) concentrations in the atmosphere. Many countries, especially in the Third World, lack sufficient information on the actual ground cover of different types of (agro) ecosystems, i.e. on carbon pools in the form of terrestrial ecosystems. Without such land cover data, it is almost impossible to analyze properly the non-fossil cycles of these countries. However, such data can be obtained with remotely sensed data from satellite images. To obtain insight into the effects of changes in land cover and the time-scales over which they occur, a dynamic simulation model on carbon cycling of terrestrial ecosystems has been converted into a GIS environment. The results of our case study show a significant correlation between field data on the amount of biomass/carbon of different natural forests and NDVI values from a satellite image of the study area. The results on field data and on NDVI data in combination with production and decomposition rates from literature have been used to calibrate the simulation model. After a sensitivity test, the model has been applied to study the effects of fragmentation on the carbon cycle of the Iztaccihuatl — Popocatepetl National Park and its surrounding buffer areas.