New Scientific Applications with Existing CGPS Capabilities Earthquakes, Soil Moisture, and Environmental Imaging Andria Bilich Geosciences Research Division.

New Scientific Applications with Existing CGPS Capabilities

Earthquakes, Soil Moisture, and Environmental Imaging

Andria BilichGeosciences Research DivisionNational Geodetic Survey

Overview

New uses of existing geodetic networks and stations (CORS, IGS, etc.)

Earthquakes / seismograms High-rate GPS Example: 2002 Denali Fault event

Soil moisture Near-field multipath Example: Uzbekistan

Environmental imaging Near- and far-field multipath Examples: Mauna Kea and Canada

Earthquakes withHigh-Rate GPS GPS/GNSS positioning

No upper limit to amplitude No preset ‘frequency response’ Positions can be computed at every data

epoch, independently Precise and accurate displacements Well-defined reference frame

Earthquakes Static and transient deformations Potentially large magnitude Frequencies = seconds to hours

GPS Data Rates and Analysis Strategies

Traditional Traditional Geodetic GPSGeodetic GPS

High-rate GPSHigh-rate GPS

Long period

(days to years)Signal

Short period

(seconds to days)

30 seconds Sample rate 1 Hz or higher

5 minutes Decimation None

1 per dayPosition

estimatesEvery sample

28+ satellitesSatellites in

solution6-8 satellites

Denali Earthquake2002 November 3

USGS fact sheet

USGS fact sheet

Long strike-slip rupture

Magnitude 7.9

Shallow SE directivity Large

surface waves

Clipped Seismometers+ 1-Hz GPS

Many broadbands in western North America went off scale…

… and high-rateGPS fills in the gaps

Denali GPS Seismograms

25 GPS stations

1 sample per second

Different azimuths and distances

GPS-Seismometer Comparison

Take-home lessons:High-rate GPS/GNSS GPS and seismometers have

complementary strengths/weaknessesNoisy GPSOff-scale seismometers

Possible only through GNSS technology advances: data storage, chipsets, firmware, etc.

Existing HR GPS networks expanding…

And now for something completely different…

Multipath Background

What is multipath? Site-specific Time-varying Sensitive to

environmental changes How can we measure

multipath? Pseudorange data

combination Solution residuals Signal-to-noise ratio

Signal-to-Noise Ratio (SNR)

Measure of signal strength Total SNR = direct plus reflected signal(s)

Direct amplitude = dominant trend Multipath signal = superimposed on direct

Soil Moisture from Near-Field Multipath

Existing GPS stations! Ground reflections

Amplitude attenuation at ground

Soil moisture affects attenuation (reflection coefficient)

Method = monitor SNR amplitude changes over time

Larson et al., GPS Solutions, 2007.

Take-home lessons:Soil Moisture Possible to use existing CGPS monuments

and receivers SNR always computed, sometimes reported S1,S2 = archived in RINEX

Challenges and issues: SNR data quality Antenna gain pattern effects Satellite power Vegetation, temperature effects Sensing depth and footprint

Environmental Imaging with Near- & Far-field Multipath Extension of soil moisture principles…

SNR data Reflection strength from multipath amplitude

… plus frequency content of SNR Satellite motion creates time-varying

signature h (fast = far; slow = close)

Power spectral maps Frequency and amplitude with respect to

satellite position (elevation/azimuth) Projected onto map of antenna environment

Mauna Kea (MKEA), Hawaii

MKEA Power Maps

Long periods at low satellite elevation angles

Shorter periods at high elevation angles

High power returns from cinder cones

60-90s 30-60s 10-30s

Dual-FrequencyPower Spectral Maps

S1 S2

Reflection from distant object (building?)

Reflection from nearby object (rock outcrops?)

Churchill (CHUR),

Manitoba, Canada

Take-home lessons:Environmental Imaging Assess multipath environment

Frequency: distance to object Amplitude: magnitude of errors due to object Consider position errors at different

frequencies (think high-rate GPS positioning) No new equipment

SNR routinely recorded … but need precise and accurate SNR

related to multipath model (not always possible)

Summary

Existing CGPS networks extended to unforeseen science applications Sensing soil moisture Understanding reflections and potential

sources of error Measuring displacements from short-period,

transient phenomena