Predicting Ecosystem Properties from Physical Data: A Case Study of Nested Soil Moisture-Climatic Gradients Along the Appalachian Chain

摘要

The ultimate goal of biological remote sensing is to monitor and predict spatial and temporal variation of biomass and productivity. While direct measurement of greenness has shown the value of remote sensing in arid regions, problems with multilayered canopies and the required ground truth data may limit the applicability of this direct approach. An alternative approach is to combine direct measurements with models that estimate biomass and primary production from physical parameters obtainable from remote sensing as well as other sources, and that have been or can be validated in the field. Variability within units resolved by remote sensing techniques may be critical for estimating landscape-scale properties. Models can be the critical link between regional remote sensing and validation at a few intensively studied sites. As an example of this approach, we will discuss how a particular model can be used to assess the influence of soil moisture gradients nested within climatic gradients on ecosystem properties. (ERA citation 12:035712)