SCALING AND UNCERTAINTY IN THE RELATIONSHIP BETWEEN THE NDVI AND LAND-SURFACE BIOPHYSICAL VARIABLES - AN ANALYSIS USING A SCENE SIMULATION-MODEL AND DATA FROM FIFE

Biophysical inversion oi remotely sensed data is con strained by the c omplexity of the remote sensing process. Variations in sensor response associated with solar and sensor geometries, surface directional refl ectance, topography, atmospheric absorption and scattering, and sensor electrical-optical engineering interact in complex manners that are d ifficult to deconvolve and quantify in individual images or in time se ries of images. We have developed a model of the remote sensing proces s to allow systematic examination of these factors. The model is compo sed of three main components, including a ground scene model, an atmos pheric model, and a sensor model, and may be used to simulate imagery produced by instruments such as the Landsat Thematic Mapper and the Ad vanced Very High Resolution Radiometer. Using this model, we examine t he effect of subpixel variance in leaf area index (LAI) on relationshi ps among LAI, the fraction of absorbed photosynthetically active radia tion (FPAR), and the normalized difference vegetation index (NDVI). To do this, we use data from the first ISLSCP Field Experiment (FIFE) to parameterize ground scene properties within the model. Our results de monstrate interactions between sensor spatial resolution and spatial a utocorrelation In ground scenes that produce a variety of effects in t he relationship between both LAI and FPAR and NDVI. Specifically, sens or regularization, nonlinearity in the relationship between LAI and ND VI, and scaling the NDVI all influence the range, variance, and uncert ainty associated with estimates of LAI and FPAR inverted from simulate d NDVI data. These results have important implications for parameteriz ation of land surface process models using biophysical variables such as LAI and FPAR estimated from remotely sensed data.