Data · collection · 2016
UAS based snow depth maps Brämabüel, Davos, CH
Listed in NASA Earthdata CMR
This snow depth map was generated 14 January 2015, close to peak of winter accumulation, applying Unmanned Aerial System digital surface models with a spatial resolution of 10 cm.
Description
The covered area is 285'000 m2 at the top of Brämabüel, 2490 m a.s.l. covering all expositions. Coordinate system: CH1903LV03.
A detailed description is given here: Bühler, Y., Adams, M. S., Bösch, R., and Stoffel, A.: Mapping snow depth in alpine terrain with unmanned aerial systems (UASs): potential and limitations, The Cryosphere, 10, 1075-1088, 10.5194/tc-10-1075-2016, 2016.
Read the rest (6 more)
Abstract
Detailed information on the spatial and temporal distribution, and variability of snow depth (HS) is a crucial input for numerous applications in hydrology, climatology, ecology and avalanche research. Nowadays, snow depth distribution is usually estimated by combining point measurements from weather stations or observers in the field with spatial interpolation algorithms. However, even a dense measurement network is not able to capture the large spatial variability of snow depth in alpine terrain.
Remote sensing methods, such as laser scanning or digital photogrammetry, have recently been successfully applied to map snow depth variability at local and regional scales. However, such data acquisition is costly, if manned airplanes are involved. The effectiveness of ground-based measurements on the other hand, is often hindered by occlusions, due to the complex terrain or acute viewing angles.
In this paper, we investigate the application of unmanned aerial systems (UAS), in combination with structure-from-motion photogrammetry, to map snow depth distribution. Such systems have the advantage that they are comparatively cost-effective and can be applied very flexibly to cover also otherwise inaccessible terrain. In this study we map snow depth at two different locations: a) a sheltered location at the bottom of the Flüela valley (1900 m a.s.l.) and b) an exposed location (2500 m a.s.l.) on a peak in the ski resort Jakobshorn, both in the vicinity of Davos, Switzerland.
At the first test site, we monitor the ablation on three different dates. We validate the photogrammetric snow depth maps using simultaneously acquired manual snow depth measurements. The resulting snow depth values have a root mean square error (RMSE) better than 0.07 to 0.15 m on meadows and rocks and a RMSE better than 0.30 m on sections covered by bushes or tall grass.
This new measurement technology opens the door for efficient, flexible, repeatable and cost effective snow depth monitoring for various applications, investigating the worlds cryosphere.
Links
Where it is published
- DOI doi.org/10.16904/envidat.31 ↗
DOI / persistent id · from NASA CMR
Documentation and papers
- VIEW RELATED INFORMATION envidat.ch/dataset/uas-based-snow-depth-maps-bramabuel-davos-ch ↗
documentation · from NASA CMR
- GET RELATED VISUALIZATION envidat.ch/envidat_thumbnail.png ↗
preview image · from NASA CMR
Catalogue records · 2
- CMR UMM-JSON cmr.earthdata.nasa.gov/search/concepts/C2789817199-ENVIDAT.umm_json ↗
metadata API · from NASA CMR
- CMR record cmr.earthdata.nasa.gov/search/concepts/C2789817199-ENVIDAT.html ↗
catalogue entry · from NASA CMR
Topics
- Stated by source
- Land Surface Agriculture Indicators · Not provided
- Inferred from text
- Physical geography and environmental geoscience 71% · Satellite remote sensing 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NASA Earthdata CMR | C2789817199-ENVIDAT | 13 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NASA CMR | connector:nasa_cmr@1.0.0 | |
| concepts[field].anzsrc:group:3709 | enrichment · NASA CMR | taxonomy-embedding@1.1.0 | title+keywords+description (71%) |
| concepts[measured_variable].gcmd:earth-science/climate-indicators/land-surface-agriculture-indicators | source · NASA CMR | connector:nasa_cmr@1.0.0 | |
| concepts[modality].local:modality:remote-sensing | enrichment · NASA CMR | keyword-concept-rules@1.0.0 | title+description (65%) |
| concepts[platform].gcmd_platform:not-provided | source · NASA CMR | connector:nasa_cmr@1.0.0 | |
| created_date | source · NASA CMR | connector:nasa_cmr@1.0.0 | |
| description | source · NASA CMR | connector:nasa_cmr@1.0.0 | /umm/Abstract |
| license_text | source · NASA CMR | connector:nasa_cmr@1.0.0 | |
| publication_date | source · NASA CMR | connector:nasa_cmr@1.0.0 | |
| spatial | source · NASA CMR | connector:nasa_cmr@1.0.0 | /umm/SpatialExtent |
| title | source · NASA CMR | connector:nasa_cmr@1.0.0 | /umm/EntryTitle |
| updated_date | source · NASA CMR | connector:nasa_cmr@1.0.0 | |
| version_label | source · NASA CMR | connector:nasa_cmr@1.0.0 |