Data · collection · 2024
Distributed Acoustic Sensing Brienz
Listed in NASA Earthdata CMR
This dataset contains the Distributed Acoustic Sensing (DAS), radar detection data used for training and result analysis in the GRL paper titled `Automatic Monitoring of Rock-Slope Failures Using Distributed Acoustic Sensing and Semi-Supervised Learning`.
Description
The DAS dataset (both waveform and cross-spectral density matrices), extracted features, labeled dataset, two trained models (feature extraction model and xgboost classification model), scripts to reproduce the whole training and classification processes, and a notebook to replicate the result analysis part are provided under the MIT license.
To provide a reasonable data size, we chunked the raw data to a few hundred channels which we used in our project.
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Abstract
Effective use of the wealth of information provided by Distributed Acoustic Sensing (DAS) for mass movement monitoring remains a challenge. We propose a semi-supervised neural network tailored to screen DAS data related to a series of rock collapses leading to a major failure of approximately 1.2 million cubic meters on 15 June 2023 in Brienz, Eastern Switzerland. Besides DAS, the dataset from 16 May to 30 June 2023 includes Doppler radar data for partially ground-truth labeling.
The proposed algorithm is capable of distinguishing between rock-slope failures and background noise, including road and train traffic, with a detection precision of over 95%. It identifies hundreds of precursory failures and shows sustained detection hours before and during the major collapse. Event size and signal-to-noise ratio (SNR) are the key performance dependencies.
As a critical part of our algorithm operates unsupervised, we suggest that it is suitable for general monitoring of natural hazards.
Links
Where it is published
- DOI doi.org/10.16904/envidat.541 ↗
DOI / persistent id · from NASA CMR
Documentation and papers
- VIEW RELATED INFORMATION envidat.ch/dataset/distributed-acoustic-sensing-brienz ↗
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/C3383774879-ENVIDAT.umm_json ↗
metadata API · from NASA CMR
- CMR record cmr.earthdata.nasa.gov/search/concepts/C3383774879-ENVIDAT.html ↗
catalogue entry · from NASA CMR
Topics
- Stated by source
- Not provided · Surface Water
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| NASA Earthdata CMR | C3383774879-ENVIDAT | 14 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · NASA CMR | connector:nasa_cmr@1.0.0 | |
| concepts[measured_variable].gcmd:earth-science/terrestrial-hydrosphere/surface-water | source · NASA CMR | connector:nasa_cmr@1.0.0 | |
| 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 |