Mapping surface hoar from near-infrared texture in a laboratory
Surface hoar crystals are snow grains that form when water vapor deposits on the snow surface. Once buried, surface hoar creates a weak layer in the snowpack that can later cause large avalanches to occur. The formation and persistence of surface hoar are highly spatiotemporally variable, making its...
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ftdoajarticles:oai:doaj.org/article:ecb5091a02224535a98859fccc389267 2024-09-15T18:38:59+00:00 Mapping surface hoar from near-infrared texture in a laboratory J. Dillon C. Donahue E. Schehrer K. Birkeland K. Hammonds 2024-05-01T00:00:00Z https://doi.org/10.5194/tc-18-2557-2024 https://doaj.org/article/ecb5091a02224535a98859fccc389267 EN eng Copernicus Publications https://tc.copernicus.org/articles/18/2557/2024/tc-18-2557-2024.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-18-2557-2024 1994-0416 1994-0424 https://doaj.org/article/ecb5091a02224535a98859fccc389267 The Cryosphere, Vol 18, Pp 2557-2582 (2024) Environmental sciences GE1-350 Geology QE1-996.5 article 2024 ftdoajarticles https://doi.org/10.5194/tc-18-2557-2024 2024-08-05T17:49:21Z Surface hoar crystals are snow grains that form when water vapor deposits on the snow surface. Once buried, surface hoar creates a weak layer in the snowpack that can later cause large avalanches to occur. The formation and persistence of surface hoar are highly spatiotemporally variable, making its detection difficult. Remote-sensing technology capable of detecting the presence and spatial distribution of surface hoar would be beneficial for avalanche forecasting, but this capability has yet to be developed. Here, we hypothesize that near-infrared (NIR) texture, defined as the spatial variability of reflectance magnitude, may produce an optical signature unique to surface hoar due to the distinct shape and orientation of the grains. We tested this hypothesis by performing reflectance experiments in a controlled cold laboratory environment to evaluate the potential and accuracy of surface hoar mapping from NIR texture using a near-infrared hyperspectral imager (NIR-HSI) and a lidar operating at 1064 nm . We analyzed 41 snow samples, three of which were surface hoar and 38 of which consisted of other grain morphologies. When using NIR-HSI under direct and diffuse illumination, we found that surface hoar displayed higher NIR texture relative to all other grain shapes across numerous spectral bands and a wide range of spatial resolutions (0.5–50 mm ). Due to the large number of spectral- and spatial-resolution combinations, we conducted a detailed samplewise case study at 1324 nm spectral and 10 mm spatial resolution. The case study resulted in the median texture of surface hoar being 1.3 to 8.6 times greater than that of the 38 other samples under direct and diffuse illumination ( p < 0.05 in all cases). Using lidar, surface hoar also exhibited significantly increased NIR texture in 30 out of 38 samples, but only at select (5–25 mm ) spatial resolutions. Leveraging these results, we propose a simple binary classification algorithm to map the extent of surface hoar on a pixelwise basis using both the NIR-HSI and ... Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles The Cryosphere 18 5 2557 2582 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
spellingShingle |
Environmental sciences GE1-350 Geology QE1-996.5 J. Dillon C. Donahue E. Schehrer K. Birkeland K. Hammonds Mapping surface hoar from near-infrared texture in a laboratory |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
Surface hoar crystals are snow grains that form when water vapor deposits on the snow surface. Once buried, surface hoar creates a weak layer in the snowpack that can later cause large avalanches to occur. The formation and persistence of surface hoar are highly spatiotemporally variable, making its detection difficult. Remote-sensing technology capable of detecting the presence and spatial distribution of surface hoar would be beneficial for avalanche forecasting, but this capability has yet to be developed. Here, we hypothesize that near-infrared (NIR) texture, defined as the spatial variability of reflectance magnitude, may produce an optical signature unique to surface hoar due to the distinct shape and orientation of the grains. We tested this hypothesis by performing reflectance experiments in a controlled cold laboratory environment to evaluate the potential and accuracy of surface hoar mapping from NIR texture using a near-infrared hyperspectral imager (NIR-HSI) and a lidar operating at 1064 nm . We analyzed 41 snow samples, three of which were surface hoar and 38 of which consisted of other grain morphologies. When using NIR-HSI under direct and diffuse illumination, we found that surface hoar displayed higher NIR texture relative to all other grain shapes across numerous spectral bands and a wide range of spatial resolutions (0.5–50 mm ). Due to the large number of spectral- and spatial-resolution combinations, we conducted a detailed samplewise case study at 1324 nm spectral and 10 mm spatial resolution. The case study resulted in the median texture of surface hoar being 1.3 to 8.6 times greater than that of the 38 other samples under direct and diffuse illumination ( p < 0.05 in all cases). Using lidar, surface hoar also exhibited significantly increased NIR texture in 30 out of 38 samples, but only at select (5–25 mm ) spatial resolutions. Leveraging these results, we propose a simple binary classification algorithm to map the extent of surface hoar on a pixelwise basis using both the NIR-HSI and ... |
format |
Article in Journal/Newspaper |
author |
J. Dillon C. Donahue E. Schehrer K. Birkeland K. Hammonds |
author_facet |
J. Dillon C. Donahue E. Schehrer K. Birkeland K. Hammonds |
author_sort |
J. Dillon |
title |
Mapping surface hoar from near-infrared texture in a laboratory |
title_short |
Mapping surface hoar from near-infrared texture in a laboratory |
title_full |
Mapping surface hoar from near-infrared texture in a laboratory |
title_fullStr |
Mapping surface hoar from near-infrared texture in a laboratory |
title_full_unstemmed |
Mapping surface hoar from near-infrared texture in a laboratory |
title_sort |
mapping surface hoar from near-infrared texture in a laboratory |
publisher |
Copernicus Publications |
publishDate |
2024 |
url |
https://doi.org/10.5194/tc-18-2557-2024 https://doaj.org/article/ecb5091a02224535a98859fccc389267 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 18, Pp 2557-2582 (2024) |
op_relation |
https://tc.copernicus.org/articles/18/2557/2024/tc-18-2557-2024.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-18-2557-2024 1994-0416 1994-0424 https://doaj.org/article/ecb5091a02224535a98859fccc389267 |
op_doi |
https://doi.org/10.5194/tc-18-2557-2024 |
container_title |
The Cryosphere |
container_volume |
18 |
container_issue |
5 |
container_start_page |
2557 |
op_container_end_page |
2582 |
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