Multi-angular Satellite Remote Sensing and Forest Inventory Data for Carbon Stock and Sink Capacity in the Eastern United States Forest Ecosystems

Terrestrial vegetation plays a major role in regulating the global carbon cycle and in turn the climate of the Earth system. It is believed that the North America forest ecosystems are a net sink for anthropogenic carbon. However, significant uncertainties exist in quantifying this claim. Inaccurate and incomplete characterization of forest vegetation is among the main causes to these uncertainties. To characterize forest vegetation for global carbon cycle and climate change research at large spatial scales, satellite remote sensing, particularly coarse-resolution remote sensing is an appropriate means. While there have been many successful applications of AVHRR and MODIS data, improvements in accuracy are still urgently needed for reducing uncertainties in related carbon cycle modeling. Multi-angular remote sensing is a new field in remote sensing and has been recently accepted as necessary. It is different from conventional nadir-only remote sensing observations in that multi-angular spectral measurements are sensitive to vegetation canopy structures, thus having the potential to enhance the characterization of forest vegetation. In this paper, we present a case study using MISR to characterize not only land cover types but also forest growth stages in the eastern United States forest ecosystems. Combined with forest inventory data, the magnitude of current carbon stock and carbon sink capacity in the Shenandoah National Park forest has been estimated. It is demonstrated that by introducing forest age differentiation, significant improvements can be made in estimating the magnitude of carbon stocks and sinks in the forest ecosystems.