EO-1 Hyperion Time Series for Vegetative and Calibration Studies
Petya K. E. Campbell*, David Lagomasino☺Elizabeth Middleton**, Kurtis J. Thome**, Bill Cook**, K. Fred
Huemmrich*, Larry Corp***, Yen-Ben Cheng+ Lawrence Ong++, Nathan Pollack++, Stuart Fry and David Landis***
* Joint Center for Earth Systems Technology (JCET), University of Maryland Baltimore County, Catonsville, MD
☺GSFC Summer Student Intern, Florida International University, Miami, FL** NASA Goddard Space Flight Center, Greenbelt, MD
*** Sigma Space, Greenbelt, MD+ERT, ++SSAI, +++SGT
BackgroundIt has become critical to understand the land cover dynamics as ecosystems cycle through seasonal changes and respond to variable environmental conditions such as water, temperature, light and nutrient availability.
Remote sensing offers an unique opportunity to monitor the changes in land cover, through multiple spectral observations and understanding of the land cover spectral responses.
Multi-date monitoring of the terrestrial environment, requires adequate radiometric calibration in order to carry out biophysical and geophysical parameter surveys that are of sufficient sensitivity and are reproducible over time.
• How do vegetation spectral, environmental and functional characteristics change in concert, under the effects of seasonal dynamics and varying environmental factors?
• How well can Hyperion monitor the spectral response and stability/cycles of major natural land covers or vegetation types?
> By assembling an initial dataset of spectroscopy images for FLUX sites, we hope to contribute toward the understanding of how do natural ecosystems respond to impinging environmental changes, particularly to climate and land cover change and the increasing impacts of urbanization?
Science Questions
1. Assess the spectral properties and variability of EO-1 Hyperion spectra at three calibration sites, namely: Frenchman Flat, Ivanpah Playa and Railroad Valley, located in North America along a similar longitude but at a varying latitude and elevation.
2. At three vastly different vegetative sites (the FLUX sites Mongu, Duke and Konza), seek common spectral trends associated with vegetation function, induced by the seasonal effects/variation of temperature, moisture and humidity.
Research Objectives
EO-1 Observations MSO Sites CEOS Sites Volcanoes > 10 Observations
The EO-1 Time Series
Hyperion DataSite Name Free of Clouds Images
[total used]Analyzed Scenes by Acquisition Date
[Julian date/year]
1. Railroad Valley Playa 16 (2001-2009)
12/2006, 41/2006, 120/2007, 135/2007, 165/2001, 174/2004, 176/2008, 181/2001, 197/2001, 209/2007, 234/2006, 272/2005,
284/2005, 288/2007
2. Ivanpah Playa 10 (2002-2005) 68/2003, 81/2002, 148/2003, 169/2005, 180/2003, 244/2003
3. Frenchman Flat 7 (2003-2008) 12/2009, 178/2003, 199/2008, 219/2007, 222/2008, 270/2007, 337/2008
1. Mongu 25 (2008)22, 40, 107, 115, 141, 145, 158, 163, 171, 173, 176, 181, 191, 194, 199, 201, 204, 225, 230,
253, 284, 291, 296, 302, 365
2. Duke Loblolly Pine 7 (2008-2009) 6/2009, 34/2009, 162/2008, 180/2008, 203/2008, 290/2008, 300/2008
3. Konza Prarie 7 (2008-2009) 13/2009, 28/2009, 202/2008, 205/2008, 261/2008, 266/2008, 302/2008
Data Processing
Level 1R Hyperion data was atmospherically corrected using the Atmosphere CORrection Now (ACORN) model and subsequently, the spectral reflectance data was extracted in the vicinity of existing flux towers. Spectral sensitivity analysis was conducted to determine spectral trends and spectral bio-indicators were computed.
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ACO
RN
ATREM
corn (r = 0.95)
forest (r = 0.98)
water (r = 0.92)
bright target (r = 0.97)
lichens (r = 0.98)
ice (r = 0.99)
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450 700 950 1200 1450 1700 1950 2200 2450
Re
fle
cta
nce
(%)
Wavelength (nm)
ice AC ice ATbright target AC bright target ATcorn AC corn ATlichens AC lichens ATforest AC fores ATwater AC water AT
CEOS Calibration Sites
Site NameCenter
LatitudeCenter
Longitude
Elevation(m asl)
Frenchman Flat, NV 36.80928 -115.93479 940
Ivanpah Playa, CA 35.5692 -115.3976 813
Railroad Valley, NV 38.50 -115.69 1435
0
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450 700 950 1200 1450 1700 1950 2200 2450
Frenchmen Flat
Ivanpah Playa
Railroad Valley
Wavelength (nm)
Refle
ctan
ce (%
)Re
flect
ance
(%)
ρ(%
, mea
ns a
nd st
anda
rt de
viat
ions
)
CEOS Sites
Temporal profile of Hyperion at Railroad Valley Playa
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10
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100
12 41 120 135 165 174 176 181 197 209 229 234 272 284 288
2006 2006 2007 2007 2001 2004 2008 2001 2001 2007 2001 2007 2005 2005 2007
Blue447 Green549 Red651
NIR854 FR1003 FR1679
FR2204
Acquisition (Julian day)
ρ(m
eans
at s
elec
t ban
ds,%
)
EO-1 Hyperion Spectral Bands
Year
Jul. day
-25-20-15-10
-505
10152025
450 700 950 1200 1450 1700 1950 2200 2450
Wavelength (nm)
ρ-m
ean(ρ)
Julian days 41-28812/2006
4 km-1 -0.5 0 0.5 +1
N
N
+ +
Left: Natural color composite (RGB: 651, 549, 447)
Right: Getis Gi* statistics (band 549) calculated for 197 Jul day image. The Gi statistics calculated for G, R, NIR, SWIR bands produced similar results.
-1 -0.5 0 0.5 +14 km
N
++
Left: Natural color composite (RGB: 651, 549, 447)
Right: Getis Gi* statistics (band 549) calculated for 197 Jul day image. The Gi statistics calculated for G, R, NIR, SWIR bands produced similar results.
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70
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90
100
68 81 148 169 180 244
2003 2002 2003 2005 2003 2003
Blue447 Green549Red651 NIR854FR1003 FR1679FR2204
Acquisition (DOY)
Spectral Bands
ρ(%
, mea
ns a
nd st
anda
rd
devi
atio
ns)
-25-20-15-10
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10152025
450 700 950 1200 1450 1700 1950 2200 2450
68 81 148 169180 244 average
Wavelength
DOYρ-m
ean(ρ)
Temporal Profile at Ivanpah Playa
-1 -0.5 0 0.5 +1
N
4 km
+ +
Left: Natural color composite (RGB: 651, 549, 447)
Right: Getis Gi* statistics (band 549) calculated for 197 DOY day image. The Gi statistics calculated for G, R, NIR, SWIR bands produced similar results.
This is the site of the LED Spectrometer (LSpec) autonomous calibration facility (http://lspec.jpl.nasa.gov)
Temporal Profile at Frenchman Flat (FMF)
Vegetative Study Sites
FLUX Site Name Location Climate Vegetation
1. Mongu Zambia Temperate/ warm summer
Kalahari/ MiomboWoodland
2. Duke Loblolly Pine, Hardwoods
NorhtCarolina, US
Temperate/ no dry season/ hot summer
Mixed forest/ Evergreen
3. Konza Prarie Kanzas, US Cold/ no dry season/ hot summer
Grassland
1.
2.3.
MSO Sites
Vegetative Study Sites•The seasonal dynamics in spectral properties are assessed at three vegetative FLUX sites: Mongu (Zambia, Africa), Konza Prairie (Kansas, USA), and Duke Forest (North Carolina, USA). •Each vegetative site represents a distinct vegetative ecosystem type; hardwood forest, grassland, evergreen forest, respectively. •Flux tower data (e.g., CO2 flux, soil heat flux) from each site is compared to spectral information for the same locations.
Mongu, Zambia
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Pre
cipi
tati
on, C
O2
Flu
x, A
lbed
o
Hyp
erio
n S
pect
ral B
io-In
dica
tor
(Dm
ax)
Temporal profile of Hyperion’s Spectral Bio-indicators at Mongu
The temporal profile in the derivative spectral bio-indicator Dmaxcaptures the dynamics in vegetation phenology at Mongu, Zambia
Dmax (x10) Precipitation (cm) CO2 flux (umol m -2 s-2 -1) Albedo (x10)
Day of the Year (2008)
Day of the Year (2008)
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Prec
ipita
tion,
CO
2Fl
ux, A
lbed
o
Hype
rion
Spe
ctra
l Bio
-Indi
cato
r Ch
lorop
hyll,
G32
= (R
750-
R445
)/((R
700-
R445
)
Spectral Bio-indicator CO2 flux (umol m -2 s-2 -1) Precipitation (cm) Albedo (x10)
The temporal profile a spectral bio-indicator associated with chlorophyll content (G32, green line) captured best the dynamics in vegetation phenology
at the flux site Mongu, Zambia.
Prec
ipit
atio
n, C
O2
Flux
, Alb
edo
Spec
tral
Bio
-indi
cato
rCh
lorop
hyll,
G32 =
(R75
0-R4
45)/(
R700
-R44
5)Hyperion’s Spectral Bio-indicators at Mongu
Duke Pine Site, NC
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Ref
lect
ance
(%)
DOY
518 549 651 854 1054 1649 2204 precip (cm) CO2 flux
Prec
ipita
tion,
CO
2flu
x , A
lbed
o
Seasonal Spectral Dynamics at Duke Pine Site
-50510152025
-0.2-0.18-0.16-0.14-0.12
-0.1-0.08-0.06-0.04-0.02
0
0 50 100 150 200 250 300 350Spec
tral
Bio
-indi
cato
r PR
I =
(570
-531
)/(57
0+53
1)
DOY
PRI1 precip (cm) CO2 flux
Prec
ipita
tion,
CO
2flu
x , A
lbed
o-50510152025
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Spec
tral
Bio
-indi
cato
r
DOY
RFG precip (cm) CO2 flux albedo
Prec
ipita
tion,
CO
2flu
x , A
lbed
o
Seasonal Spectral Dynamics at Konza
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Prec
ipita
tion,
CO
2Fl
ux, A
lbed
o
Ref
lect
ance
(%)
DOY
518 549 651 854 1054 1649 2204 precip (cm) CO2_flux_2008
Temporal Spectral Dynamics at Konza
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100
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Spec
tral
Bio
-indi
cato
rP
hys.
Fun
ctio
n,
RFf
r= (R
730-
R65
0)/(R
685+
R65
0 )
DOY
Prec
ipita
tion,
CO
2Fl
ux,
Albe
do
precip (cm) CO2_flux_2008 albedo RFfr
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Prec
ipita
tion,
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2Fl
ux,
Albe
do
DOY
Spec
tral
Bio
-Indi
cato
r D
max
, Veg
. Phy
siol
ogy,
Can
opy
Inde
pend
ent
precip (cm) CO2_flux_2008 albedo Dmax
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Spec
tral
bio
-indi
cato
rC
hlor
ophy
ll, G
94 =
(R80
0-R
700)
/(R80
0+R
700)
DOY
Prec
ipita
tion,
CO
2Fl
ux, A
lbed
o
precip (cm) CO2_flux_2008 G94 albedo
Temporal profile of Hyperion’s Spectral Bio-indicators at Konza
Multiple Flux SitesKonza (K) 1yr burn & 4 year burn, Mongu (M), Duke (D) pine & hardwoods
y = -0.0024x2 - 1.4794x + 17.814R² = 0.75
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30
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-40 -30 -20 -10 0 10
Spec
tral
Bio
-indi
cato
r (D
max
)
CO2 flux (µmol/m2/s)
K1DK4BMDDuke HWhw
p
At a number of sites with vastly different vegetation type, the derivative spectral bio-indicator (Dmax) reflected vegetation dynamics and was negatively correlated with CO2 flux.
Correlation coefficients for the top 5 (based on R values) biophysical indices
Spectral Bio-indicator
FormulaCO2 flux
CO2Respiration
ResSoil Heat Flux
G
Dmax Max. derivative in the 690-730 - 0.82 0.69 0.90
G32, G94 R(750-445)/(700-445), R(800-700)/(800-700) - 0.79 0.67 0.87
RFfr R(650-730)/(730-650) - 0.78 0.62 0.85
Transformed Chl Abs R index
R700, R600, R550 - 0.78 0.25 0.94
NDWI R(870-1240)/R(870-1240) - 0.77 0.29 0.83
• Biophysical spectral indices correlate well with G and CO2 flux measurements from 3 vastly different vegetation types
• Unique seasonal R dynamics corresponded with each site specific phenology
• Highly correlated spectral bio-indicators required continuous spectra, and were using a number of wavelengths near the “red edge”, and
• High spectral resolution imaging is useful for detecting parameters related to CO2 flux and G
Preliminary Findings
Future Directions• expand and refine the spectral datasets and the spectral bio-indicators (add
other locations and vegetation types, and consider BRDF effects)• test the established Canopy Chemistry equations for the sites with time series• use the datasets in pre-launch product simulations of sensors such as EnMAP
and HyspIRI• characterize basic ecological patterns in anthropogenic ecosystems related to
differences in ecosystem function.
! Overlapping satellite observations and land cover records, with 1 to 2 year overlap periods are required for the generation of long term data records for environmental monitoring and climate change assessments.
Project Collaborators• Hank Margolis, Laval University , Quebec, Canada• Jose F. Moreno, Department of Earth Physics and
Thermodynamics, University of Valencia, Spain• Nicholas Coops, University of British Columbia, Vancouver, CA• Caroline J Nichol, School of GeoSciences, University of
Edinburgh, Edinburgh, UK• Valérie Demarez, CESBIO, Toulouse, France• Frederic Baret, CNES, Avignon, France
AcknowledgmentsDr. Brunsell and the KNZ-LTER supplied flux data for the Konza Prairie. The School of the Environment at Duke University supplied flux data for the Duke Forest sites.
The project provided research experience for graduate and undergraduate students, which participate through established programs, assisting with data processing, analysis and preparation of reports.
Thank You
Temporal variations in the spectral characteristics of the Frenchman Flat site (reflectance means and standard deviations for selected Hyperion bands). The spectral characteristics are significantly by the presence of various proportion of clouds (cloud cover expressed in percent of imaged area covered by clouds) in the atmosphere adjacent to the site, as is evident for Julian days 54, 82, 107, 166, 214, 217 and 278.
EO-1 Hyperion:
RGB 752, 609, 508 nm
30 m pixels Reflectance
1 km 1 km
EO-1 Hyperion:
RGB 752, 609, 508 nm
30 m pixels Reflectance
July 13, 2008 August 18, 2008 October 2, 2008
forest
forestcorn
water
forest
forestcorn
water water
forest
forestcorn
1 km
EO-1 Hyperion:
RGB 752, 609, 508 nm
30 m pixels Reflectance
Seasonal Spectral Changes at OPE3
Cover Type Hyperion, 2008 V1 PRI REIP Dmax WBI Albedo Corn 13-Jun 1.03 -0.04 712 0.36 0.96 0.461
18-Aug 1.81 -0.06 722 0.75 1.09 0.197 3-Oct 1.15 0.04 721 0.51 0.98 0.155
Forest 13-Jun 1.12 -0.06 712 0.89 1.00 0.257 18-Aug 1.56 -0.03 722 0.51 1.01 0.140 3-Oct 1.61 -0.10 712 0.42 0.94 0.127
Water 13-Jun 0.15 0.01 712 0.16 1.23 0.058 18-Aug 0.52 0.02 712 0.10 1.46 0.031 3-Oct 0.62 -0.07 712 0.08 0.93 0.036
Seasonal Spectral Dynamics in Land Cover at OPE3
Spring Summer Fall17-Apr 13-Jun 20-Jul 18-Aug 4-Oct
EO-1 Hyperion True color
RGB Color Composite Bands 752, 609, 508 nm
1 km
60 m pixels Reflectance
forest
corn
water
RGB Color Composite Bands 752, 609, 508 nm
1 km
60 m pixels Reflectance
forest
corn
RGB Color Composite Bands 752, 609, 508 nm
1 kmRGB Color Composite
Bands 752, 609, 508 nm
1 km1 km
60 mpixelsReflectance
forestforest
corncorn
waterwater
RGB Color Composite Bands 752, 609, 508 nm
1 km
60 m pixels Reflectance
forest
corn
RGB Color Composite Bands 752, 609, 508 nm
1 kmRGB Color Composite
Bands 752, 609, 508 nm
1 km1 km
60 m pixels Reflectance
forestforest
corncorn
waterwater
RGB Color Composite Bands 752, 609, 508 nm
1 kmRGB Color Composite
Bands 752, 609, 508 nm
1 km1 km
60 m pixels Reflectance
forestforest
corncorn
RGB Color Composite Bands 752, 609, 508 nm
1 km1 kmRGB Color Composite
Bands 752, 609, 508 nm
1 km1 km
60 mpixelsReflectance
forestforest
corncorn
waterwater
USDA/BARC Beltsville, MD
18-August, 2008
Water Stress Index (ρ1600/ ρ 820)
c
Bio-physical parameter Spectral bio-indicators (examples) References
VSWIR indicators Chlorophyll in crops (RNIR/ R-1
720-730) - 1 Gitelson et al., 2005
Canopy greenness LRCRCRRR
GEVIblueredNIR
redNIR
+−+−
=21
* Huete et al. 2002
Chlorophyll concentration estimation
)16.0/()(*)16.01()]/(*)(*2.0)[(*3/
670800700800
670700550700670700
++−+−−−
=RRRR
RRRRRROSAVITCARI Haboudane et al. 2002, Zarco-Tejada
et al. 2004 Efficiency of photosynthesis PRI=(R570-R531)/(R570+R531) Gamon et al., 1992,
Suarez et al. 2008 Canopy foliar water content 1240
1240
RRRR
NDWINIR
NIR
+−
= Gao, 1996
Canopy foliar water content 1640
1640
RRRR
SIWINIR
NIR
+−
= Fensholt and Sandholt, 2003
Vegetation stress Average (R675…. R705) Vogelman, 1993 Veg. structure and foliar biomass NDVI = (R800-R670)/(R800+R670) Deering, 1978
Stress/Chlorophyll D714/D705, where D is product of first derivative transformation of R Entcheva, 2004
Stress/ Chlorophyll Dmax/D705, where Dmax is the maximum of D in the 670-730nm region Entcheva, 2004
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