Recent advances in the remote sensing of alpine snow: a review. Issue 6 (18th August 2021)

• Record Type: Journal Article
• Authors: Awasthi, Shubham; Varade, Divyesh
• Is Part Of: GIScience & remote sensing. Volume 58:Issue 6(2021)
• Page Start: 852
• Page End: 888
• Publication Date: 2021-08-18
• Subjects: Snow -- remote sensing -- liquid water content -- snow density -- snow depth; Geodesy -- Periodicals; Cartography -- Periodicals; Aerial photogrammetry -- Periodicals; Remote sensing -- Periodicals; 526.05
• DOI: 10.1080/15481603.2021.1946938
• Languages: English
• ISSNs: 1548-1603

Abstract

ABSTRACT: Seasonal alpine snow contributes significantly to the water resource. It plays a crucial role in regulating the environmental feedback and from the perspective of socio-economic sustainability in the alpine regions. While most nations are pursuing renewable energy sources, hydropower generated from snowmelt runoff is one of the primary sources. Additionally, alpine regions with snow cover are major tourist destinations that are often affected by natural disasters such as avalanches. The snowmelt runoff and early avalanche warning require timely information on the spatio-temporal aspects of the snow geophysical parameters. In this regard, advances in remote sensing of snow have been observed to be significant. Recent developments in remote sensing technology in the visible, infrared, and microwave spectrum have significantly improved our understanding of snow geophysical processes. This paper provides a review concerning the qualitative and quantitative studies of alpine snow. The electromagnetic characteristics of the alpine snow are largely dependent upon its inherent geophysical structure and the properties of the snow. Snow behaves differently with respect to the wavelength of the incident radiation. In this paper, we provide a categorical review of the remote sensing techniques for estimating the snow geophysical properties, inclusive of permittivity, density, and wetness corresponding to the wavelength used in the remotely sensed data: (1) visible-infrared spectrum including multispectral/hyperspectral, (2) active and passive microwave spectrums. We also discuss the recent advancements in the remote sensing techniques for approximating the volumetric snowpack parameters such as the snow depth and the snow water equivalent based on active and passive microwave remote sensing. This review further discusses the limitations of the techniques reviewed and future prospects for the retrieval of snow geophysical parameters (SGP) corresponding to the recent progress in remote sensing technology. In summary, the recent advances have laid down a foundation for rigorous assessment of seasonal snow using spaceborne remote sensing, particularly at a regional scale. Yet, the scope for improvements in the methods and payload design exists.