@article{Ghiasi-2024-Potential,
title = "Potential of GNSS-R for the Monitoring of Lake Ice Phenology",
author = "Ghiasi, Yusof and
Duguay, Claude and
Murfitt, Justin and
Asgarimehr, Milad and
Wu, Yuhao",
journal = "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume 17",
volume = "17",
year = "2024",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
url = "https://gwf-uwaterloo.github.io/gwf-publications/G24-20001",
doi = "10.1109/jstars.2023.3330745",
pages = "660--673",
abstract = "This study introduces the first use of Global Navigation Satellite System Reflectometry (GNSS-R) for monitoring lake ice phenology. This is demonstrated using Qinghai Lake, Tibetan Plateau, as a case study. Signal-to-Noise Ratio (SNR) values obtained from the Cyclone GNSS (CYGNSS) constellation over four ice seasons (2018 to 2022) were used to examine the impact of lake surface conditions on reflected GNSS signals during open water and ice cover seasons. A moving t-test algorithm was applied to time-varying SNR values allowing for the detection of lake ice at daily temporal resolution. Good agreement was achieved between ice phenology records derived from CYGNSS data and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The CYGNSS timings for freeze-up, i.e., the period starting with the first appearance of ice on the lake (freeze-up start; FUS) until the lake becomes fully ice covered (freeze-up end; FUE), as well as those for breakup, i.e., the period beginning with the first pixel of open water (breakup start; BUS) and ending when the whole lake becomes ice-free (breakup end; BUE), were validated against the phenology dates derived from MODIS images. Mean absolute errors are 7, 5, 10, 4 and 5 days for FUS, FUE, BUS, BUE and ice cover duration, respectively. Observations revealed the sensitivity of GNSS reflected signals to surface melt prior to the appearance of open water conditions as determined from MODIS, which explains the larger difference of 10 days for BUS.",
}
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<abstract>This study introduces the first use of Global Navigation Satellite System Reflectometry (GNSS-R) for monitoring lake ice phenology. This is demonstrated using Qinghai Lake, Tibetan Plateau, as a case study. Signal-to-Noise Ratio (SNR) values obtained from the Cyclone GNSS (CYGNSS) constellation over four ice seasons (2018 to 2022) were used to examine the impact of lake surface conditions on reflected GNSS signals during open water and ice cover seasons. A moving t-test algorithm was applied to time-varying SNR values allowing for the detection of lake ice at daily temporal resolution. Good agreement was achieved between ice phenology records derived from CYGNSS data and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The CYGNSS timings for freeze-up, i.e., the period starting with the first appearance of ice on the lake (freeze-up start; FUS) until the lake becomes fully ice covered (freeze-up end; FUE), as well as those for breakup, i.e., the period beginning with the first pixel of open water (breakup start; BUS) and ending when the whole lake becomes ice-free (breakup end; BUE), were validated against the phenology dates derived from MODIS images. Mean absolute errors are 7, 5, 10, 4 and 5 days for FUS, FUE, BUS, BUE and ice cover duration, respectively. Observations revealed the sensitivity of GNSS reflected signals to surface melt prior to the appearance of open water conditions as determined from MODIS, which explains the larger difference of 10 days for BUS.</abstract>
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%0 Journal Article
%T Potential of GNSS-R for the Monitoring of Lake Ice Phenology
%A Ghiasi, Yusof
%A Duguay, Claude
%A Murfitt, Justin
%A Asgarimehr, Milad
%A Wu, Yuhao
%J IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume 17
%D 2024
%V 17
%I Institute of Electrical and Electronics Engineers (IEEE)
%F Ghiasi-2024-Potential
%X This study introduces the first use of Global Navigation Satellite System Reflectometry (GNSS-R) for monitoring lake ice phenology. This is demonstrated using Qinghai Lake, Tibetan Plateau, as a case study. Signal-to-Noise Ratio (SNR) values obtained from the Cyclone GNSS (CYGNSS) constellation over four ice seasons (2018 to 2022) were used to examine the impact of lake surface conditions on reflected GNSS signals during open water and ice cover seasons. A moving t-test algorithm was applied to time-varying SNR values allowing for the detection of lake ice at daily temporal resolution. Good agreement was achieved between ice phenology records derived from CYGNSS data and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The CYGNSS timings for freeze-up, i.e., the period starting with the first appearance of ice on the lake (freeze-up start; FUS) until the lake becomes fully ice covered (freeze-up end; FUE), as well as those for breakup, i.e., the period beginning with the first pixel of open water (breakup start; BUS) and ending when the whole lake becomes ice-free (breakup end; BUE), were validated against the phenology dates derived from MODIS images. Mean absolute errors are 7, 5, 10, 4 and 5 days for FUS, FUE, BUS, BUE and ice cover duration, respectively. Observations revealed the sensitivity of GNSS reflected signals to surface melt prior to the appearance of open water conditions as determined from MODIS, which explains the larger difference of 10 days for BUS.
%R 10.1109/jstars.2023.3330745
%U https://gwf-uwaterloo.github.io/gwf-publications/G24-20001
%U https://doi.org/10.1109/jstars.2023.3330745
%P 660-673
Markdown (Informal)
[Potential of GNSS-R for the Monitoring of Lake Ice Phenology](https://gwf-uwaterloo.github.io/gwf-publications/G24-20001) (Ghiasi et al., GWF 2024)
ACL
- Yusof Ghiasi, Claude Duguay, Justin Murfitt, Milad Asgarimehr, and Yuhao Wu. 2024. Potential of GNSS-R for the Monitoring of Lake Ice Phenology. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Volume 17, 17:660–673.
