Steele et al. (2026) Informing snow measurement site selection with remote sensing and local ecological knowledge: A case study in Oregon

Identification

• Journal: Remote Sensing Applications Society and Environment
• Year: 2026
• Date: 2026-01-01
• Authors: Hannah Steele, Kelsey Emard, Mark S. Raleigh
• DOI: 10.1016/j.rsase.2026.101912

Research Groups

College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, USA

Short Summary

This study developed and demonstrated a novel method for informing optimal site selection for snow measurement stations by integrating satellite remote sensing data and local ecological knowledge, using the Chewaucan Basin in Oregon as a case study.

Objective

• To develop and demonstrate a method for informing optimal site selection for snow measurement stations by integrating satellite remote sensing data and local ecological knowledge.

Study Configuration

• Spatial Scale: Chewaucan Basin, Oregon, with a 500 meter resolution spatial map.
• Temporal Scale: A 23-year record of daily snow cover mapping.

Methodology and Data

• Models used: Geographic Information System (GIS) model.
• Data sources: Moderate Resolution Imaging Spectroradiometer (MODIS) satellite remote sensing data, local ecological knowledge gathered from water users, and geospatial data representing landscape and infrastructure variables.

Main Results

• A 500 meter resolution spatial map was derived, showing correlations between annual snow disappearance date (from 23 years of MODIS data) and summer streamflow volume.
• This correlation map, along with landscape and infrastructure variables, served as input to a GIS model to identify potential locations for an automated snow measurement system.
• Feedback from local water users on local conditions was integrated with the modeled suitability analysis.
• A final site recommendation was produced, reflecting the synthesis of remote sensing-based modeling and local ecological knowledge.

Contributions

• Developed a novel, integrated methodology for snow measurement site selection that combines satellite remote sensing data and local ecological knowledge.
• Demonstrated the practical application of this method in a specific basin to improve the quality and relevance of snowpack data for local water planning.
• Highlighted the value of participatory methods in scientific site selection processes by incorporating local ecological knowledge.

Funding

Not specified in the provided text.

Citation

@article{Steele2026Informing,
  author = {Steele, Hannah and Emard, Kelsey and Raleigh, Mark S.},
  title = {Informing snow measurement site selection with remote sensing and local ecological knowledge: A case study in Oregon},
  journal = {Remote Sensing Applications Society and Environment},
  year = {2026},
  doi = {10.1016/j.rsase.2026.101912},
  url = {https://doi.org/10.1016/j.rsase.2026.101912}
}