|Schiebe, Frank - SST DEVELOPMENT GROUP INC|
Submitted to: Remote Sensing of Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 15, 2002
Publication Date: May 30, 2003
Citation: Chopping, M.J., Rango, A., Havstad, K.M., Schiebe, F.R., Ritchie, J.C., Schmugge, T.J., French, A.N., Su, L., McKee, L., Davis, M.R. 2003. Canopy attributes of desert grassland and transition communities derived from multiangular airborne imagery. Remote Sensing of Environment. 85(3). p. 339-354. Interpretive Summary: The aim of this study was to examine features of the bidirectional reflectance distribution function (BRDF) which may provide valuable information on canopy physiognomy. Remote metrics of canopy attributes provide indicators of the extent to which former Chihuahuan Desert grasslands have become shrub-dominated and can enhance nadir-spectral measures in which vegetation cover, leaf greenness and foliage density are confounded. It is difficult to sample BRDF features from the ground because of long intrinsic-length scales; and, hitherto, only point target, multi-angular reflectance data have been collected over Chihuahuan Desert communities from the air using tilted, single field-of-view radiometers. It has thus been impossible to evaluate the variability of BRDF features within, as well as between, communities. In this study, a low-cost digital camera was used to derive mutli-angular reflectance images from the air over grassland and grass-shrub transition zones; and, a BRDF model based o geometric optics and volume scattering was developed and adjusted against these data. The majority of the retrieved parameter values were reasonable, but the interpretation of facet area index maps was sometimes problematic. Other retrieved parameter maps (protrusion density and width and crown shape) and derived values (fractional cover and canopy height) reveal variations in canopy architecture which are clearly related to structural and optical features in high resolution panchromatic and vegetation index images. To our knowledge, this paper reports on the first attempts to acquire spatial BRDF features and canopy attributes of Chihuahuan Desert landscapes using single-wavelength, multiple view angle data at scales less than 1 km.
Technical Abstract: Overlapping multi-angular spectral reflectance images were collected over desert grassland and grass-shrub transition communities (USDA, ARS, Jornada Experimental Range, Las Cruces, NM) using a DuncanTech multispectral digital camera mounted on a tilting bracket installed in an ARS research aircraft. Flightlines were oriented in the principal plane with three flights providing observations at three solar zenith angles (37 deg, 47 de and 60 deg). The 0.65um band images were calibrated to spectral radiance (W m2 um-1 sr-1) using laboratory measurements, corrected for atmospheric attenuation using the 6Sv4.2 code and resampled to a 2m UTM grid. The surface reflectance estimates were checked with air- and ground-based observations of 8m2 reference tarps. The images were convolved with a 50m2 pseudo-Gaussian point spread function and sampled at 25m to simulate samples from a sensor with a larger instantaneous field-of-view to properly ycapture the bidirectional reflectance distribution function (BRDF; intrinsic surface length scales are greater than 10m). A BRDF model based on geometric optics and volume scattering functions was developed to account for variation in directional reflectance signal with viewing and illumination angles. It was adjusted to the set of multi-angular observations for each location using the Hooke and Jeeves algorithm (1961), inverting the model for 2 (facet area index and plant protrusion density) and 3 parameters (facet area index, plant protrusion density and width) simultaneously and for these parameters plus a crown shape factor with stepwise inversion of each parameter sequentially. The retrieved parameter maps were assessed for value distributions and compared with 1m panchromatic and 4m vegetation index images from the IKONOS satellite.