ORIGINAL RESEARCH article

Front. Remote Sens.

Sec. Multi- and Hyper-Spectral Imaging

Volume 6 - 2025 | doi: 10.3389/frsen.2025.1572973

This article is part of the Research TopicAdvancing Earth Observations from Small SatellitesView all 3 articles

How Commercial SmallSats are Revolutionizing the Remote Detection and Mapping of Snow Algae

Provisionally accepted
  • Western Washington University, Bellingham, United States

The final, formatted version of the article will be published soon.

Snow algae play an important role in reducing the surface albedo of snow surfaces worldwide and contributing to enhanced melt through a bio-albedo feedback loop. Traditional remote sensing approaches have relied on government-operated satellite platforms, such as Landsat and Sentinel-2, which provide freely available data but are limited by their coarse spatial resolution. Recent advancements in commercial satellite technologies, particularly SmallSats, offer higher spatial and temporal resolutions, enabling more precise detection and mapping of snow algae. This study evaluates the capabilities of commercial satellites, including SkySat, PlanetScope, BlackSky, and WorldView, for snow algae mapping on Mt. Baker, Washington, USA. Leveraging data from NASA’s Commercial SmallSat Data Acquisition (CSDA) program, we apply spectral indices to classify snow algae. Our findings highlight the advantages and limitations of commercial SmallSats compared to traditional government-operated satellites, emphasizing their potential for improving snow algae mapping in ecological and climate studies. The results of this study provide insights into the role of high spatial resolution commercial satellite imagery in advancing our understanding of snow algae distribution and its broader implications for climate feedback mechanisms.

Keywords: remote sensing, Satellites, SmallSats, Earth Observation, Snow algae, albedo, snowmelt, cryosphere

Received: 08 Feb 2025; Accepted: 09 Apr 2025.

Copyright: © 2025 Rand and Khan. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: Alia L Khan, Western Washington University, Bellingham, United States

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