It is the intent of this paper to demonstrate the veracity of a method to estimate the total solid contaminant mass present on a sparsely coated surface encompassing a pixel from longwave infrared spectra. Sparsely coated surfaces create complex radiometry due to the interactions of electromagnetic energy between intimate materials. Current algorithms can be used on intimate mixtures to identify the abundances of materials in a pixel, but they cannot provide additional property information. Radiative transfer models can create mixture signatures, but only with a set of well-characterized physical parameters that are typically not known or are difficult to retrieve. The approach described here creates a parameter inversion model from a radiative transfer model and uses empirically measured mixture data to retrieve physical characteristics of the contaminated surface and derive a total contaminant mass present.
Timothy J. Gibbs,
David W. Messinger,
"Remotely sensed physical property estimation from powder contaminated surfaces," Journal of Applied Remote Sensing 11(4), 046021 (15 December 2017). https://doi.org/10.1117/1.JRS.11.046021
. Submission: Received: 30 May 2017; Accepted: 14 November 2017
Received: 30 May 2017; Accepted: 14 November 2017; Published: 15 December 2017