Coupling a grassland ecosystem model with Landsat imagery for a 10-year simulation of carbon and water budgets

In this study, high-spatial, low-temporal scale visible remote sensing data were used to calibrate an ecosystem model (EM) for semiarid perennial gras slands. The model was driven by daily meteorological data and simulated pla nt growth and water budget on the same time step. The model was coupled wit h a canopy reflectance model to yield the time course of shortwave radiomet ric profiles. Landsat Thematic Mapper (TM) and Enhanced TM Plus (ETM+) imag es from 10 consecutive years were used to refine the model on a spatially d istributed basis. A calibration procedure, which minimized the difference b etween the normalized difference vegetation index (NDVI) simulated from the coupled model and measured by the TM and ETM+ sensors, yielded the spatial distribution of an unknown parameter and initial condition. Accuracy of mo del products, such as daily aboveground biomass, leaf area index (LAI) and soil water content, was assessed by comparing them with field measurements. The promising results suggest that this approach could provide spatially d istributed information about both vegetation and soil conditions for day-to -day grassland management. (C) 2001 Elsevier Science Inc. All rights reserv ed.