Snow Property Inversion From Remote Sensing (SPIReS): A Generalized Multispectral Unmixing Approach With Examples From MODIS and Landsat 8 OLI

Bair, Edward H.; Stillinger, Timbo; Dozier, Jeff

doi:10.1109/tgrs.2020.3040328

i

Snow Property Inversion From Remote Sensing (SPIReS): A Generalized Multispectral Unmixing Approach With Examples From MODIS and Landsat 8 OLI

2021
By Bair, Edward H. ; Stillinger, Timbo ; Dozier, Jeff

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Journal Title:

IEEE Transactions on Geoscience and Remote Sensing
Personal Author:

Bair, Edward H. ; Stillinger, Timbo ; Dozier, Jeff
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research)
Description:

Spectral mixture analysis has a history in mapping snow, especially where mixed pixels prevail. Using multiple spectral bands rather than band ratios or band indices, retrievals of snow properties that affect its albedo lead to more accurate estimates than widely used age-based models of albedo evolution. Nevertheless, there is substantial room for improvement. We present the Snow Property Inversion from Remote Sensing (SPIReS) approach, offering the following improvements: 1) Solutions for grain size and concentrations of light absorbing particles are computed simultaneously; 2) Only snow and snow-free endmembers are employed; 3) Cloud-masking and smoothing are integrated; 4) Similar spectra are grouped together and interpolants are used to reduce computation time. The source codes are available in an open repository. Computation is fast enough that users can process imagery on demand. Validation of retrievals from Landsat 8 operational land imager (OLI) and moderate-resolution imaging spectroradiometer (MODIS) against WorldView-2/3 and the Airborne Snow Observatory shows accurate detection of snow and estimates of fractional snow cover. Validation of albedo shows low errors using terrain-corrected in situ measurements. We conclude by discussing the applicability of this approach to any airborne or spaceborne multispectral sensor and options to further improve retrievals.
Keywords:

Electrical And Electronic Engineering General Earth And Planetary Sciences Electrical And Electronic Engineering General Earth And Planetary Sciences Electrical And Electronic Engineering General Earth And Planetary Sciences
Source:

IEEE Transactions on Geoscience and Remote Sensing, 59(9), 7270-7284
DOI:

https://doi.org/10.1109/tgrs.2020.3040328
ISSN:

0196-2892 ; 1558-0644
Format:

PDF
Publisher:

Institute of Electrical and Electronics Engineers (IEEE)
Document Type:

Journal Article
Funding:

Grant no. NA18OAR4590380
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Library
Main Document Checksum:

urn:sha256:562825c6ef65191bc4b969782a714794cba80daf74f8184a4e4a0fedac901e1d
Download URL:

https://repository.library.noaa.gov/view/noaa/58955/noaa_58955_DS1.pdf
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[PDF - 5.21 MB ]

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