Soil Moisture, Snow, and Vegetation Sensing Using GPS...
Transcript of Soil Moisture, Snow, and Vegetation Sensing Using GPS...
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˚
30˚
35˚
40˚
45˚
50˚
0 500
km
Continuously-Operating Geodetic GPS Receivers ~2 years ago
180˚
180˚
240˚
240˚
300˚
300˚
0˚
0˚
60˚
60˚
120˚
120˚
180˚
180˚
80˚ 80˚60˚ 60˚
40˚ 40˚
20˚ 20˚
0˚ 0˚
20˚ 20˚
40˚ 40˚
60˚ 60˚80˚ 80˚
.
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
20
10
0
10
20
30
40
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
40
30
20
10
0
10
20
30
40
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
60
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
0
5
10
15
20
25
30
35
40
45
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
0
0.2
0.4
0.6
0.8
1
1.2
snow
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
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
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
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
years
cmMP1 P070
how do geodesists typically use mean RMS
Foothill, Idaho P422
2007 2008 2009 2010
44
40
36
32
28
MP1
(cm
)p422
2007 2008 2009 20100.1
0.3
0.5
0.7
0.9
ND
VI
Small, Larson, and Braun, Sensing Vegetation Growth With Reflected GPS Signals, Geophys. Res. Lett., 2010.
Battle Mountain, Nevada P085
58
54
50
46
42
38
MP1
(cm
)
p085
0.1
0.3
0.5
ND
VI
2007 2008 2009 20100
50
100
perc
ent
average
annual accumulated precipitation
year
Munson Farm Experiment
50
45
40cm
MP1 (low elevation only)
140 160 180 200 220 2400
1
2
3
4
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
50
100
150
200
250
300
350
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
!! !" !# $ # " !!"
!#
$
#
"
%&'()*&+,()-./)'&+01(*
,'
2344)35&6&+78)29*&1&9+)-*1&'71(*)!):951;
Larson, unpublished 1-Hz GPS records from the Parkfield earthquake
example:
!! !" !# $ # " !!"
!#
$
#
"
%&'()*&+,()-./)'&+01(*
,'
2344)456&7&(6)8&6(9(:;;<)=&;1(9(6)>?:&+)!)@591A
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