GLAM Bio-Lith RT: A Tool for Remote Sensing Reflectance Simulation and Water Components Concentration Retrieval in Glacial Lakes
Kargel, Jeffrey S.
Watson, Cameron Scott
Shugar, Dan H.
Haritashya, Umesh K.
AffiliationUniv Arizona, Dept Syst & Ind Engn
Univ Arizona, Dept Aerosp & Mech Engn, Dept Syst & Ind Engn
Univ Arizona, Dept Hydrol & Atmospher Sci
Inverse mode problem
MetadataShow full item record
PublisherFRONTIERS MEDIA SA
CitationSchiassi E, Furfaro R, Kargel JS, Watson CS, Shugar DH and Haritashya UK (2019) GLAM Bio-Lith RT: A Tool for Remote Sensing Reflectance Simulation and Water Components Concentration Retrieval in Glacial Lakes. Front. Earth Sci. 7:267. doi: 10.3389/feart.2019.00267
JournalFRONTIERS IN EARTH SCIENCE
RightsCopyright © 2019 Schiassi, Furfaro, Kargel, Watson, Shugar and Haritashya. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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AbstractA new open-source software tool, called GLAM BioLith-RT (Glacier Lakes Assisted Melting Biological Lithological Radiative Transfer), has been developed for modeling of Radiative Transfer (RT) in water bodies containing suspended lithic particles, phytoplankton, dissolved salts, and colored dissolved organic matter. Although our objective is an application to glacial lakes of High Mountain Asia, the model has potential application for the study of seawater, organic-rich lakes, rivers, etc. The tool is built on a solid foundation of an existing published open-source code called WASI, which has been reviewed and augmented with new capabilities, notably the addition of a suspended lithic particle grain size parameterization. GLAM BioLith-RT operates in both a forward modeling and inverse modeling mode. The forward mode is specifically designed to compute the reflectance spectra of glacier lakes from inherent optical water properties. Conversely, in the inverse mode, measured spectral reflectance is employed with other inputs to derive best fitting water component properties (e.g., suspended particles concentration). The inverse modeling includes Bayesian inversion of the output which is a significant advance over the existing software. We have tested the code for sensitivity to noise, and uncertainties in input parameters. The model succeeds in nearly reproducing the hyperspectral reflectance of some glacial lakes in Nepal as observed by the EO-1 Hyperion hyperspectral imager. The inverse modeling approach, when supported up by validated forward modeling, offers a means for remote sensing characterization of suspended sediment load in glacial lakes and rivers and hence, use of suspended sediment as a proxy for glacial activity; and many other potential applications in other thematic areas.
NoteOpen access journal
VersionFinal published version
SponsorsNASANational Aeronautics & Space Administration (NASA) [NNX16AQ62G, 80NSSC19K0653]