Recent advances in the remote sensing of alpine snow: a review

Awasthi, Shubham; Varade, Divyesh

doi:10.1080/15481603.2021.1946938

Cited by 26 publications

(11 citation statements)

References 209 publications

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“…However, ground-based deformation measurement using GPS surveying and LIDAR based methods is very challenging for continuous monitoring due to the highly rugged terrain and extreme weather conditions in the higher Himalayas 17 , 18 . During most of the year, these locations are inaccessible due to high snow cover 19 . The GPS sensor network has continuous data procurement, connectivity, and consistency issues.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Joshimath’s sinking: causes, consequences, and future prospects with remote sensing techniques

Awasthi,

Jain,

Sahoo

et al. 2024

Sci Rep

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The Himalayas are highly susceptible to various natural disasters, such as the tectonically induced land deformation, earthquakes, landslides, and extreme climatic events. Recently, the Joshimath town witnessed a significantly large land subsidence activity. The phenomenon resulted in the development of large cracks in roads and in over 868 civil structures, posing a significant risk to inhabitants and infrastructure of the area. This study uses a time-series synthetic aperture radar (SAR) interferometry-based PSInSAR approach to monitor land deformation utilizing multi-temporal Sentinel-1 datasets. The line of sight (LOS) land deformation velocity for the Joshimath region, calculated for the year 2022–2023 using a PSInSAR-based approach, varies from − 89.326 to + 94.46 mm/year. The + ve sign indicates the LOS velocity/displacement away from the SAR sensor, whereas − ve sign signifies the earth's movement towards the SAR sensor in the direction of LOS. In addition, the study investigates feature tracking land displacement analysis using multi-temporal high-resolution Planet datasets. The result of this analysis is consistent with the PSInSAR results. The study also estimated the land deformation for the periods 2016–2017, 2018–2019, and 2020–2021 separately. Our results show that the Joshimath region experienced the highest land deformation during the year 2022–2023. During this period, the maximum land subsidence was observed in the north-western part of the town. The maximum LOS land deformation velocity + 60.45 mm/year to + 94.46 mm/year (2022–2023), occurred around Singhdwar, whereas the north and central region of the Joshimath town experienced moderate to high subsidence of the order of + 10.45 mm/year to + 60.45 mm/year (2022–2023), whereas the south-west part experienced an expansion of the order of 84.65 mm/year to − 13.13 mm/year (2022–2023). Towards the south-east, the town experienced rapid land subsidence, − 13.13 mm/year to − 5 mm/year (2022–2023). The study analyzes the causative factors of the observed land deformation in the region. Furthermore, this work assesses the ground conditions of the Joshimath region using UAV datasets acquired in the most critically affected areas such as Singhdhaar, Hotel Mountain View, Malhari Hotel, and Manoharbagh. Finally, the study provides recommendations and future prospects for the development policies that need to be adopted in the critical Himalayan regions susceptible to land deformation. The study suggests that land deformation in the region is primarily attributed to uncontrolled anthropogenic activities, infrastructural development, along with inadequate drainage systems.

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Section: Introductionmentioning

confidence: 99%

Analyzing Joshimath’s sinking: causes, consequences, and future prospects with remote sensing techniques

Awasthi,

Jain,

Sahoo

et al. 2024

Sci Rep

Self Cite

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“…Regarding snow and backscatter interaction, radar backscatter over wet snow (wet snow is often defined as either above 1% volume water content or above 0 • C) decreases greatly due to the liquid water content altering the dielectric properties of the snowpack [53,54]. While different radar wavelengths will each interact with snowpack differently, the radar penetration depth of all microwave radiation will drastically decrease in wet snow.…”

Section: Impact Of Snow On Asar-isro Data and Resultsmentioning

confidence: 99%

Characterizing and Mapping Volcanic Flow Deposits on Mount St. Helens via Dual-Band SAR Imagery

Rogic,

Charbonnier,

Garin

et al. 2023

Remote Sensing

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Mapping volcanic flow deposits can be achieved by considering backscattering characteristics as a metric of surface roughness. In this study, we developed an approach to extract a measure of surface roughness from dual-band airborne Synthetic Aperture Radar (ASAR) backscattering data to characterize and map various volcanic flow deposits—namely, debris avalanches, lahars, lava flows, and pyroclastic density currents. We employed ASAR and Indian Space Research Organization (ISRO) airborne SAR datasets, from a joint project (ASAR-ISRO), acquired in December 2019 at 2 m spatial resolution, to assess the role and importance of incorporating dual-band data, i.e., L-band and S-band, into surface roughness models. Additionally, we derived and analyzed surface roughness from a digital surface model (DSM) generated from unoccupied aircraft systems (UAS) acquisitions using Structure from Motion (SfM) photogrammetry techniques. These UAS-derived surface roughness outputs served as meter-scale calibration products to validate the radar roughness data over targeted areas. Herein, we applied our method to a region in the United States over the Mount St. Helens volcano in the Cascade Range of Washington state. Our results showed that dual-band systems can be utilized to characterize different types of volcanic deposits and range of terrain roughness. Importantly, we found that a combination of radar wavelengths (i.e., 9 and 24 cm), in tandem with high-spatial-resolution backscatter measurements, yields improved surface roughness maps, compared to single-band, satellite-based approaches at coarser resolution. The L-band (24 cm) can effectively differentiate small, medium, and large-scale structures, namely, blocks/boulders from fine-grained lahar deposits and hummocks from debris avalanche deposits. Additionally, variation in the roughness estimates of lahar and debris avalanche deposits can be identified and quantified individually. In contrast, the S-band (9 cm) can distinguish different soil moisture conditions across variable terrain; for example, identify wet active channels. In principle, this dual-band approach can also be employed with time series of various other SAR data of higher coherence (such as satellite SAR), using different wavelengths and polarizations, encompassing a wider range of surface roughness, and ultimately enabling additional applications at other volcanoes worldwide and even beyond volcanology.

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“…( 2). The two main scattering processes occurring in snow are surface scattering (from the air-snow boundary, snow-ground boundary, or internal layers such as melt-freeze crusts), and volume scattering occurring throughout the snow volume [44]. Dihedral scattering can also occur from one or several of these boundaries.…”

Section: Scattering Characteristics Of Snowmentioning

confidence: 99%

Polarimetric Analysis of Biseasonal Monostatic and Bistatic Radar Observations of a Glacier Accumulation Zone at Ku-Band

Stefko,

Bernhard,

Frey

et al. 2024

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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We present ground-based Ku-band radar observations of the snow cover on top of the Great Aletsch Glacier carried out over two observation periods, in August 2021 and in March 2022. The observations were carried out with the combined mono/bistatic version of KAPRI, a full-polarimetric radar system, and revealed substantial differences between the scattering behaviour of the snow cover between the two seasons. We analyze the spatial and temporal behaviour of parameters including temporal decorrelation, the scattering entropy, the mean polarimetric alpha angle, and the co-and cross-polarized phase differences. The results indicate that snow cover decorrelates at Ku-band on the timescales of 4-12 hours in winter and summer, which has implications for repeat-pass methods with long temporal baselines. The analysis of the co-polarized phase difference in winter indicates that the parameter is prone to phase wrapping. In summer, its value exhibits smooth spatial trend and a strong sensitivity to changes in incidence angle and liquid water content. The bistatic cross-polarized phase difference also acquires a non-zero value, indicating the presence of non-reciprocal scattering, which has implications for possible calibration procedures of bistatic systems. The presented results aim to serve as a reference for snow scattering behaviour at Ku-band, which can aid planning of future data acquisition campaigns and satellite missions.

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Recent advances in the remote sensing of alpine snow: a review

Cited by 26 publications

References 209 publications

Analyzing Joshimath’s sinking: causes, consequences, and future prospects with remote sensing techniques

Analyzing Joshimath’s sinking: causes, consequences, and future prospects with remote sensing techniques

Characterizing and Mapping Volcanic Flow Deposits on Mount St. Helens via Dual-Band SAR Imagery

Polarimetric Analysis of Biseasonal Monostatic and Bistatic Radar Observations of a Glacier Accumulation Zone at Ku-Band

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