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Satellite and Airborne Remote Sensing for Snow Observation

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: 30 July 2024 | Viewed by 956

Special Issue Editor

Finnish Meteorological Institute, Helsinki, Finland
Interests: development of remote sensing algorithms of snow and other parameters; application of satellite data in climate change research; development of satellite services

Special Issue Information

Dear Colleagues,

Snow is a vital parameter of the cryosphere in terms of both climate and hydrology. Changes in the snow extent can provide insights into how the snow cover changes due to climate changes. Snow water equivalent (SWE) describes the water content of the snowpack. It also can be used as an indicator of climate change and used as an input for water discharge models. Fractional snow-covered area parameters derived from optical instruments, together with, for example, passive microwave-radiometer-derived snow melt estimates can be used to determine changes in the carbon balance in the atmosphere.

Obtaining frequent, accurate, and spatially and temporally well-covered information about snow requires the use of remote sensing and Earth observation methods. Spaceborne data can be used to map large regions and continents, whereas airborne measured data can give more accurate insight at a regional scale. In addition, the airborne measurements can augment spaceborne-derived estimates as an independent information and a source of validation. In particular, the development of unmanned aerial vehicles (UAVs) has been rapid in recent years.

The purpose of this Special Issue is to present the state of the art of the remote sensing of snow using both satellite methods and airborne measurements. The utilization of UAVs is of special interest. In addition, the submission of papers using airborne measured data to improve and validate spaceborne-derived snow estimates is encouraged.

Dr. Matias Takala
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • snow extent
  • snow melt
  • snow water equivalent
  • hydrology
  • UAV
  • passive microwave
  • data assimilation

Published Papers (1 paper)

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Review

37 pages, 16435 KiB  
Review
Snow Water Equivalent Monitoring—A Review of Large-Scale Remote Sensing Applications
by Samuel Schilling, Andreas Dietz and Claudia Kuenzer
Remote Sens. 2024, 16(6), 1085; https://doi.org/10.3390/rs16061085 - 20 Mar 2024
Viewed by 656
Abstract
Snow plays a crucial role in the global water cycle, providing water to over 20% of the world’s population and serving as a vital component for flora, fauna, and climate regulation. Changes in snow patterns due to global warming have far-reaching impacts on [...] Read more.
Snow plays a crucial role in the global water cycle, providing water to over 20% of the world’s population and serving as a vital component for flora, fauna, and climate regulation. Changes in snow patterns due to global warming have far-reaching impacts on water management, agriculture, and other economic sectors such as winter tourism. Additionally, they have implications for environmental stability, prompting migration and cultural shifts in snow-dependent communities. Accurate information on snow and its variables is, thus, essential for both scientific understanding and societal planning. This review explores the potential of remote sensing in monitoring snow water equivalent (SWE) on a large scale, analyzing 164 selected publications from 2000 to 2023. Categorized by methodology and content, the analysis reveals a growing interest in the topic, with a concentration of research in North America and China. Methodologically, there is a shift from passive microwave (PMW) inversion algorithms to artificial intelligence (AI), particularly the Random Forest (RF) and neural network (NN) approaches. A majority of studies integrate PMW data with auxiliary information, focusing thematically on remote sensing and snow research, with limited incorporation into broader environmental contexts. Long-term studies (>30 years) suggest a general decrease in SWE in the Northern Hemisphere, though regional and seasonal variations exist. Finally, the review suggests potential future SWE research directions such as addressing PMW data issues, downsampling for detailed analyses, conducting interdisciplinary studies, and incorporating forecasting to enable more widespread applications. Full article
(This article belongs to the Special Issue Satellite and Airborne Remote Sensing for Snow Observation)
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