Intercomparison of photogrammetric platforms for spatially continuous snow depth mapping
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Published:2021-01-05
Issue:1
Volume:15
Page:69-94
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ISSN:1994-0424
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Container-title:The Cryosphere
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language:en
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Short-container-title:The Cryosphere
Author:
Eberhard Lucie A.ORCID, Sirguey PascalORCID, Miller AubreyORCID, Marty Mauro, Schindler Konrad, Stoffel Andreas, Bühler YvesORCID
Abstract
Abstract. Snow depth has traditionally been estimated based on
point measurements collected either manually or at automated weather
stations. Point measurements, though, do not represent the high spatial
variability in snow depths present in alpine terrain. Photogrammetric
mapping techniques have progressed in recent years and are capable of
accurately mapping snow depth in a spatially continuous manner, over larger
areas and at various spatial resolutions. However, the strengths and
weaknesses associated with specific platforms and photogrammetric
techniques as well as the accuracy of the photogrammetric performance on
snow surfaces have not yet been sufficiently investigated. Therefore,
industry-standard photogrammetric platforms, including high-resolution
satellite (Pléiades), airplane (Ultracam Eagle M3), unmanned aerial
system (eBee+ RTK with SenseFly S.O.D.A. camera) and terrestrial (single lens reflex
camera, Canon EOS 750D) platforms, were tested for snow depth mapping in the alpine
Dischma valley (Switzerland) in spring 2018. Imagery was acquired with
airborne and space-borne platforms over the entire valley, while unmanned
aerial system (UAS) and terrestrial photogrammetric imagery was acquired
over a subset of the valley. For independent validation of the
photogrammetric products, snow depth was measured by probing as well as
by using remote observations of fixed snow poles. When comparing snow depth maps with manual and snow pole measurements, the
root mean square error (RMSE) values and the normalized median absolute deviation (NMAD) values were 0.52 and 0.47 m, respectively, for the satellite snow
depth map, 0.17 and 0.17 m for the airplane snow depth map, and 0.16 and
0.11 m for the UAS snow depth map. The area covered by the terrestrial snow
depth map only intersected with four manual measurements and did not generate
statistically relevant measurements. When using the UAS snow depth map as a
reference surface, the RMSE and NMAD values were 0.44 and 0.38 m for the
satellite snow depth map, 0.12 and 0.11 m for the airplane snow depth map,
and 0.21 and 0.19 m for the terrestrial snow depth map. When compared to the
airplane dataset over a large part of the Dischma valley (40 km2), the
snow depth map from the satellite yielded an RMSE value of 0.92 m and an NMAD
value of 0.65 m. This study provides comparative measurements between
photogrammetric platforms to evaluate their specific advantages and
disadvantages for operational, spatially continuous snow depth mapping in
alpine terrain over both small and large geographic areas.
Publisher
Copernicus GmbH
Subject
Earth-Surface Processes,Water Science and Technology
Reference75 articles.
1. Agisoft LLC: Agisoft Metashape User Manual Professional Edition, 1.5, availabe at: https://www.agisoft.com/pdf/photoscan-pro_1_4_en.pdf (last access: 25 October 2019), 2019. 2. Avanzi, F., Bianchi, A., Cina, A., De Michele, C., Maschio, P., Pagliari,
D., Passoni, D., Pinto, L., Piras, M., and Rossi, L.: Centimetric Accuracy
in Snow Depth Using Unmanned Aerial System Photogrammetry and a
MultiStation, Remote Sens.-Basel, 10, 5,
https://doi.org/10.3390/rs10050765, 2018. 3. Baggi, S. and Schweizer, J.: Characteristics of wet-snow avalanche
activity: 20 years of observations from a high alpine valley (Dischma,
Switzerland), Nat. Hazards, 50, 97–108,
https://doi.org/10.1007/s11069-008-9322-7, 2008. 4. Bartelt, P., Buser, O., Vera Valero, C., and Bühler, Y.: Configurational
energy and the formation of mixed flowing/powder snow and ice avalanches,
Ann. Glaciol., 57, 179–188,
https://doi.org/10.3189/2016AoG71A464, 2016. 5. Basnet, K., Muste, M., Constantinescu, G., Ho, H., and Xu, H.: Close range
photogrammetry for dynamically tracking drifted snow deposition, Cold Reg.
Sci. Technol., 121, 141–153,
https://doi.org/10.1016/j.coldregions.2015.08.013, 2016.
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