Constrained radiative transfer inversions for vegetation moisture retrievals in grasslands
Document Type: Journal Article
Author(s): S. Dasgupta; J. J. Qu; S. Bhoi
Publication Year: 2009

Cataloging Information

  • fire management
  • fuel moisture
  • grasslands
  • grasslands
  • live fuel moisture content
  • radiative transfer models
  • range management
  • rate of spread
  • remote sensing
  • soil moisture
  • wildfires
Record Maintained By:
Record Last Modified: June 1, 2018
FRAMES Record Number: 52660
Tall Timbers Record Number: 29824
TTRS Location Status: Not in file
TTRS Call Number: Available via ILL only
TTRS Abstract Status: Okay, Fair use, Reproduced by permission

This bibliographic record was either created or modified by the Tall Timbers Research Station and Land Conservancy and is provided without charge to promote research and education in Fire Ecology. The E.V. Komarek Fire Ecology Database is the intellectual property of the Tall Timbers Research Station and Land Conservancy.


The retrieval of Live Fuel Moisture Content (LFMC) over fire prone grasslands is important for fire risk and drought assessment. Radiative transfer (RT) model based inversion of measured reflectances for retrievals of LFMC offers a promising method for estimating LFMC. This paper evaluates the extent to which inverse RT model based LFMC retrievals over grasslands can be improved by the use of prior information on soil moisture and LAI. However due to the uncertainty in the procedures used in obtaining the pre-retrieval information about LAI and soil moisture, the prior information is more likely to be in terms of an expected range for LAI and soil moisture rather than exact values. This study uses simulations from coupled soil-leaf-canopy radiative transfer models to investigate the extent to which such categorical prior information may reduce the uncertainty in LFMC retrievals. Results show that under the experimental conditions used in this study, prior information on LAI and soil moisture improves LFMC estimation on the average by about 2.3 to 3.4% (absolute LFMC) depending on the quality and accuracy of the prior information. This can be equivalent to a relative improvement of about 18-27%. This can be significant, since at the dry conditions represented by this study, when fire spread is highly sensitive to LFMC, such improvements in LFMC could considerably improve fire spread predictions and aid fire management decision making. Uncertainty analysis in terms of prediction intervals and standard deviation of errors also show that improvements are significant. © 2009 Society of Photo-Optical Instrumentation Engineers

Dasgupta, S., J. J. Qu, and S. Bhoi. 2009. Constrained radiative transfer inversions for vegetation moisture retrievals in grasslands. Journal of Applied Remote Sensing, v. 3, no. 1, p. 031503 [article no. online]-11 pp [total pages online]. 10.1117/1.3075052.