skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: An efficient strategy for the inversion of bidirectional reflectance models with satellite remote sensing data

Abstract

The angular distribution of radiation scattered by the earth surface contains information on the structural and optical properties of the surface. Potentially, this information may be retrieved through the inversion of surface bidirectional reflectance distribution function (BRDF) models. This report details the limitations and efficient application of BRDF model inversions using data from ground- and satellite-based sensors. A turbid medium BRDF model, based on the discrete ordinates solution to the transport equation, was used to quantify the sensitivity of top-of-canopy reflectance to vegetation and soil parameters. Results were used to define parameter sets for inversions. Using synthetic reflectance values, the invertibility of the model was investigated for different optimization algorithms, surface and sampling conditions. Inversions were also conducted with field data from a ground-based radiometer. First, a soil BRDF model was inverted for different soil and sampling conditions. A condition-invariant solution was determined and used as the lower boundary condition in canopy model inversions. Finally, a scheme was developed to improve the speed and accuracy of inversions.

Authors:
Publication Date:
Research Org.:
Colorado Univ., Boulder, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Research, Washington, DC (United States)
OSTI Identifier:
527478
Report Number(s):
DOE/OR/00033-T710
ON: DE97053337; TRN: AHC29720%%70
DOE Contract Number:  
AC05-76OR00033
Resource Type:
Technical Report
Resource Relation:
Other Information: TH: Thesis (Ph.D.); PBD: 1994
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; REMOTE SENSING; TERRESTRIAL ECOSYSTEMS; EXPERIMENTAL DATA; CANOPIES; SATELLITES; ALBEDO; B CODES; ALGORITHMS; RADIOMETERS

Citation Formats

Privette, J.L. An efficient strategy for the inversion of bidirectional reflectance models with satellite remote sensing data. United States: N. p., 1994. Web. doi:10.2172/527478.
Privette, J.L. An efficient strategy for the inversion of bidirectional reflectance models with satellite remote sensing data. United States. doi:10.2172/527478.
Privette, J.L. Sat . "An efficient strategy for the inversion of bidirectional reflectance models with satellite remote sensing data". United States. doi:10.2172/527478. https://www.osti.gov/servlets/purl/527478.
@article{osti_527478,
title = {An efficient strategy for the inversion of bidirectional reflectance models with satellite remote sensing data},
author = {Privette, J.L.},
abstractNote = {The angular distribution of radiation scattered by the earth surface contains information on the structural and optical properties of the surface. Potentially, this information may be retrieved through the inversion of surface bidirectional reflectance distribution function (BRDF) models. This report details the limitations and efficient application of BRDF model inversions using data from ground- and satellite-based sensors. A turbid medium BRDF model, based on the discrete ordinates solution to the transport equation, was used to quantify the sensitivity of top-of-canopy reflectance to vegetation and soil parameters. Results were used to define parameter sets for inversions. Using synthetic reflectance values, the invertibility of the model was investigated for different optimization algorithms, surface and sampling conditions. Inversions were also conducted with field data from a ground-based radiometer. First, a soil BRDF model was inverted for different soil and sampling conditions. A condition-invariant solution was determined and used as the lower boundary condition in canopy model inversions. Finally, a scheme was developed to improve the speed and accuracy of inversions.},
doi = {10.2172/527478},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1994},
month = {12}
}