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Big Data Analysis for Permafrost Research€¦ · n tics tion dynamic data reduction event...

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• Matterhorn Hörnligrat 3500m a.s.l. • Multisensor eld experiment • Seismometer (SM) • Accelerometer (AM) • Acoustic sensor (AS) • Crackmeter (CR) • Rock temperature • L1-DGPS (WGPS) • High-resolution camera • Weather station • High data throughput: ~7 GB/day ~ 2.5 TB/year 1 0 m e t e r s 10 meters AS low AS high AM SM scarp SM ridge CR 02 CR 20 CR 06 WGPS Wireless Sensor Network Data Management and DB Architecture From Field to Screen • Demanding processing and storage requirements • Strongly heterogeneous data Long-Term Storage Raw Data (SM, AM, AS) GSN Database Event Database Event Waveforms Webcam Images Data Fusion Analytics Visualization dynamic data reduction event parametrization temporary data retrieve archive convert/copy • Web front-end • Multi-year content • Server-side pre-computed waveforms • Responsive interaction (zoom,pan,...) • Data statistics • Single event characterization Spectrogram Full-resolution waveform Feature extraction Visualization Analysis Continuous Data Visualization • Finding visual correlations and patterns • Identifying periods of strong activity Event Characterization • Temporal dependencies • Feature clustering 0 40 20 Amplitude [counts] Seismometer Manual Event Detection • Event/eldwork labeling • Catalog for event classication http://data.permasense.ch/ Amplitude [counts] 120 0 60 0 -15k 15k Seismometer Weather station Wind speed [km/h] -4k 4k Time [days] Time [days] Time [s] Time [days] Image Start Image End Maximum Amplitude [V] Acoustic Sensor Duration [s] Amplitude [V] -1 1 What happened? Precipitation? Mountaineer? Frost cracking? Data Storage Data Management Wireless Sensor Network Visualization Rupture? Large data quantities Content-aware data reduction Data Fusion Data Processing Big Data Analysis for Permafrost Research Visualization of heterogeneous data from always-on eld experiments - Matthias Meyer, Samuel Weber, Jan Beutel
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Page 1: Big Data Analysis for Permafrost Research€¦ · n tics tion dynamic data reduction event parametrization etrieve y chive convert/copy • Web front-end • Multi-year content •

• Matterhorn Hörnligrat 3500m a.s.l. • Multisensor field experiment • Seismometer (SM) • Accelerometer (AM) • Acoustic sensor (AS) • Crackmeter (CR) • Rock temperature • L1-DGPS (WGPS) • High-resolution camera • Weather station

• High data throughput: ~7 GB/day ~ 2.5 TB/year

Matterhorn, 4478 m

10 meters10 meters

ASlow AShigh

AMSMscarp

SMridge

CR02

CR20

CR06

WGPS

Wireless Sensor Network

Data Management and DB Architecture

From Field to Screen

• Demanding processing and storage requirements• Strongly heterogeneous data

Long-Term Storage

Raw Data(SM, AM, AS)

GSN Database

Event Database

Event Waveforms

Webcam Images

Data

Fu

sio

n

An

aly

tics

Vis

ualizati

on

dynamic datareduction

eventparametrization

temporary

data retrieve

archive

convert/copy

• Web front-end• Multi-year content• Server-side pre-computed waveforms• Responsive interaction (zoom,pan,...) • Data statistics• Single event characterization • Spectrogram • Full-resolution waveform • Feature extraction

Visualization

Analysis

Continuous Data Visualization• Finding visual correlations and patterns• Identifying periods of strong activity

Event Characterization• Temporal dependencies• Feature clustering

0

40

20

Am

plit

ud

e [

cou

nts

] Seismometer

Manual Event Detection• Event/fieldwork labeling• Catalog for event classification

http://data.permasense.ch/

Am

plit

ud

e [

cou

nts

]

120

0

60

0

-15k

15k

Seismometer

Weather station

Win

d s

peed

[km

/h]

-4k

4k

Time [days]

Time [days]

Time [s]

Time [days]

Image Start Image End

Maximum Amplitude [V]

Acoustic Sensor

Dura

tion [

s]A

mp

litud

e [

V]

-1

1

What happened?

Precipitation?

Mountaineer?Frost cracking?

Data Storage

Data

Man

ag

em

en

tW

irele

ss S

en

sor

Netw

ork

Vis

ualizati

on

Rupture?

Large data quantities

Content-aware data reduction

Data Fusion

Data Processing

Big Data Analysis for Permafrost ResearchVisualization of heterogeneous data from always-on field experiments-

Matthias Meyer, Samuel Weber, Jan Beutel

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