Prairie grassland bidirectional reflectances measured by different instruments at the FIFE site

Abstract

Land surface reflectance measurements were acquired during the First ISLSCP Field Experiment (FIFE) field campaigns using a variety of ground-based and airborne spectral radiometers. To examine the validity of the assumption that the values acquired by the several different instruments and teams were interchangeable, the surface radiation measurement teams converged on a common site for 1 day during the fifth intensive field campaign (IFC 5) in 1989. The instruments compared for near-surface measurements included two ground-based Spectron Engineering SE59Os, one helicopter-mounted SE590, one ground-based and one helicopter-mounted Barnes modular multiband radiometer (MMR), and the portable apparatus for rapid acquisitions of bidirectional observations of land and atmosphere (PARABOLA) field radiometer. Comparisons were made for nadir measurements over a range of solar zenith angles and a range of off-nadir viewing angles. The bidirectional reflectances from the different instruments were generally found to be quite comparable. For example, for a 52° solar zenith angle, the nadir red and near-infrared spectral reflectance factors ranged from 3.5 to 4.5% and 28.2 to 31.9%, respectively. At the smaller solar zenith angles, however, the differences were somewhat greater (red, 4.5–6.1%; near-infrared (NIR), 25.0–28.9%), and the coefficients of variation for the samples taken by all of the instruments increased. Off-nadir viewing caused major departures from nadir bidirectional reflectances (30% reflectance at nadir compared with 55% at 60° off nadir in the NIR, for example), but all of the instruments captured the effects reasonably well. Spectral vegetation indices were found to have a considerable dependence on both solar zenith angle and sensor viewing angle. In spite of the general agreement between most instruments and teams, the lack of a more consistent band-to-band agreement resulted in appreciable differences in the spectral vegetation index values, which could potentially affect the accuracy and precision of remote sensing assessments of biophysical parameters.