EGU24-1915, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-1915
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Evaluating MODIS snow products using an extensive wildlife camera network

Catherine Breen1, Carrie Vuyovich2, John Odden, Dorothy Hall, and Laura Prugh1
Catherine Breen et al.
  • 1University of Washington, School of Environmental and Forest Sciences, United States of America (cbreen@uw.edu)
  • 2Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA (carrie.m.vuyovich@nasa.gov)

Snow covers a maximum of 47 million km2 of Earth ’s northern hemisphere each winter and is an important component of the planet ’s energy balance, hydrology cycles, and ecosystems. Monitoring regional and global snow cover has increased in urgency in recent years due to warming temperatures and declines in snow cover extent. Optical satellite instruments provide large-scale observations of snow cover, but cloud cover and dense forest canopy can reduce accuracy in mapping snow cover. Remote camera networks deployed for wildlife monitoring operate below cloud cover and in forests, representing a virtually untapped source of snow cover observations to supplement satellite observations. Using images from 1181 wildlife cameras deployed by the Norwegian Institute for Nature Research (NINA), we compared snow cover extracted from camera images to Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products during winter months of 2018–2020. Ordinal snow classifications (scale = 0–4) from cameras were closely related to normalized difference snow index (NDSI) values from the MODIS Terra Snow Cover Daily L3 Global 500 m (MOD10A1) Collection 6 product (R2 = 0.70). Tree canopy cover, the normalized difference vegetation index (NDVI), and image color mode influenced agreement between camera images and MOD10A1 NDSI values. For MOD10A1F, MOD10A1’s corresponding cloud-gap filled product, agreement with cloud-gap filled values decreased from 78.5% to 56.4% in the first three days of cloudy periods and stabilized thereafter. Using our camera data as validation, we derived a threshold to create daily binary maps of snow cover from the MOD10A1 product. The threshold corresponding to snow presence was an NDSI value of 40.50, which closely matched a previously defined global binary threshold of 40 using the MOD10A2 8-day product. These analyses demonstrate the utility of camera trap networks for validation of snow cover products from satellite remote sensing, as well as their potential to identify sources of inaccuracy.

How to cite: Breen, C., Vuyovich, C., Odden, J., Hall, D., and Prugh, L.: Evaluating MODIS snow products using an extensive wildlife camera network, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1915, https://doi.org/10.5194/egusphere-egu24-1915, 2024.

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