Soil Moisture, Snow, and Vegetation Sensing

Using GPS ReceiversKristine M. Larson

Department of Aerospace Engineering SciencesUniversity of Colorado

Eric Small (CU), John Braun (UCAR), Valery Zavorotny (NOAA), Mark Williams (CU), Felipe Nievinski (CU)

Outline

• Multipath in geodetic applications• Multipath signature in geodetic data• Multipath results using geodetic

receivers:– Soil Moisture– Snow Depth – Vegetation Water Content

235˚ 240˚ 245˚ 250˚ 255˚ 260˚ 265˚ 270˚ 275˚ 280˚ 285˚ 290˚25˚

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Continuously-Operating Geodetic GPS Receivers ~2 years ago

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.

152004 2008200720062005 20102009

source: PBO website

Results for plate motions: no multipath modeling

Larson, Bilich, and Axelrad, Improving high-rate GPS precision, JGR. 2007

but if you look at higher temporal sampling

use “yesterday” to correct “today”

Choi et al., Geophysical Research Letters, 2004.

but is yesterday really like today?

the question:

• Data collected from geodetic-quality GPS receivers are clearly sensitive to reflected signals.

• Can those same GPS receivers be used to measure soil moisture, snow, and vegetation changes?

9

Figures courtesy of Felipe Nievinski

Right-Hand Circularly Polarized Left-Hand Circularly Polarized

the difficulty

11 12 13 14 15 1630

35

40

45

50

55Observed Composite Signal

dBH

z

hours (UTC)

instead of pseudorange or carrier phase observables (or residuals), use Signal Power (SNR)

0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.550

40

30

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0

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50Observed Multipath Signal

sine(elevation angle)

SNR

(V)

the “reflected” signal

Changes in these oscillations (frequency, amplitude) are related to changes in the ground.

three scientific applications

vegetationsnowsoil moisture

• We buried 10 time domain reflectometers - 5 at 2.5cm and 5 at 7.5 cm

• And collected GPS SNR data from L2C satellites using a Trimble NetRS (geodetic) receiver and choke-ring antenna.

soil moisture

0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.550

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30

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10

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50Observed Multipath Signal

sine(elevation angle)

SNR

(V)

GPS data TDR data

SNR: fixed frequency; estimated amplitude and phase

offset

We later demonstrated that “reflector height” also corresponds well with VWC

initial results

Larson, Small, Gutmann, Braun, Zavorotny, and Bilich, Use of GPS receivers as a soil moisture network for water cycle studies, Geophys. Res. Lett., 2008

GPS Snow Sensing

0.1 0.2 0.3 0.460

30

0

30

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sin(elevation angle)

B.

volts

/vol

ts

Modeled GPS SNR Data

0.1 0.2 0.3 0.460

30

0

30

60Observed GPS SNR Data

volts

/vol

ts

A. no snow

35 cm ofnew snow

Larson, Gutmann, Braun, Zavorotny, Williams, and Nievinski, Can we measure snow depth with GPS receivers?, Geophys. Res. Lett., 2009

295 297 299 301 303 305 307 3095

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50hand measurements

GPS satellitesultrasonic snow sensors

day of year (2009)

snow

dep

th (c

m)

Plate Boundary Observatory Site P041

Plate Boundary Observatory Site P360

2009.8 2009.9 2010 2010.1 2010.2 2010.3 2010.40.2

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dep

th (m

)

PBO site P360

SNOTEL is 15 km from GPS siteGPS 1858 mSNOTEL 1917 m

100 50 0 50 100 150 2000.2

0

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days since Jan 1, 2010

snow

dep

th

met

ers

Niwot Ridge GPS Snow Experiment

SS GPS tracks

avggpspole16pole06pole05laser

GPS Vegetation Sensing

PBO site in Parkfield, CA

in addition to SNR data, multipath can also be observed in the geodetic observables - i.e. MP1

2007 2007.5 2008 2008.5 20090.2

0.25

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years

cmMP1 P070

how do geodesists typically use mean RMS

Foothill, Idaho P422

2007 2008 2009 2010

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MP1

(cm

)p422

2007 2008 2009 20100.1

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ND

VI

Small, Larson, and Braun, Sensing Vegetation Growth With Reflected GPS Signals, Geophys. Res. Lett., 2010.

Battle Mountain, Nevada P085

58

54

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MP1

(cm

)

p085

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ND

VI

2007 2008 2009 20100

50

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perc

ent

average

annual accumulated precipitation

year

Munson Farm Experiment

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45

40cm

MP1 (low elevation only)

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kg/m

/m

Vegetation Water Content

day of year

comparison with in situ data

Small et al., 2010.

Conclusions

• expand the use of an existing GPS network to new communities (hydrology, ecology, atmospheric sciences, cryosphere, water management)

• provide data products to improve weather prediction and climate studies

• potential validation network for new environmental satellite missions, especially SMOS, SMAP, Desdyni.

Acknowledgements

• NSF AGS and EAR (0740515 and 0935725)• CU Seed Grants• Andria Bilich, Penina Axelrad, and Bob Munson • Plate Boundary Observatory• UNAVCO, esp. Mike Jackson, Fred Blume, Chuck

Meertens, Jim Normandeau, Dave Maggert, Lou Estey, and Sarah Doelger.

11 12 13 14 15 160

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250

300

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400Observable S2 Linear Scale

SNR

(V)

hours (UTC)

SNR - Linear Scale

What can we compare MP1 variations to?

ratio of spectral reflectance in the near-infrared and red regions, i.e. how green it is.

NDVI: Normalized Difference Vegetation Index

NDVI MODIS: every 16 days, 250 m by 250 m pixel

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Agnew and Larson, Finding the Repeat Times of the GPS Constellation, GPS Solutions, 2007

1-hz time series with multipath removed

Water Content Reflectometers GPS

Larson, Small, Gutmann, Braun, Zavorotny, and Bilich, GPS Multipath and Its Relation to Near-Surface Soil Moisture Content, IEEE J-STARS, 2010