Temporal Modeling of Bidirectional Reflection Distribution Function (BRDF) in Coastal Vegetation

Document Type

Article

Publication Date

1-1-2004

Department

Geography and Geology

School

Biological, Environmental, and Earth Sciences

Abstract

The bidirectional reflection distribution function (BRDF) is a theoretical concept that describes the relationship between a target's irradiance geometry and the viewing angle of the sensor relative to the target. The BRDF can significantly affect the radiometric quality of remotely sensed data, particularly in off-nadir views. This research used a NASA Sandmeier Field Goniometer (SFG) to collect hourly canopy spectral reflectance at 76 hemispherical angles at two study sites within the North Inlet-Winyah Bay National Estuarine Research Reserve during late winter (March 2000—low live biomass and high dead biomass) and late summer (October 2000—high live biomass and low dead biomass). The objective of this research was to compare and quantify the temporal differences of high spectral and angular resolution BRDF diurnal data for smooth cordgrass (Spartina alterniflora) communities. These data were collected to model and quantify BRDF canopy patterns as they relate to in situ biophysical measurements and phenological change. The hypothesis tested was that temporal changes in LAI, biomass, height, geometry, understory, and tide levels throughout the phenological cycle can be spectrally quantified to provide insight into BRDF research. These data were used to create graphic plots to provide a quantitative assessment of temporal BRDF patterns and biophysical characteristics. This research identified bands that are least impacted by the BRDF, recognized optimal Sun/sensor angles-of-view, and provided insight into radiometrically adjusting remotely sensed data to minimize BRDF effects. Once scientists understand the nature of BRDF in relation to phenological changes within the vegetation canopy, they can begin to apply models to improve the accuracy of information extracted from remotely sensed data.

Publication Title

GIScience & Remote Sensing

Volume

41

Issue

2

First Page

116

Last Page

135

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