EPA Hyperspectral Imagery Coastal Protection

Office of Research and Development
Full Name of Lab, Center, Office, Division or Staff goes here. <Go to View, Master, Slide Master to change>
National Health and Environmental Effects Research Laboratory/ Atlantic Ecology Division July 16, 2013
EPA/ORD/NHEERL/NERL
Naval Research Laboratory/Stennis
Space Center
ISS Hyperspectral Imager for the Coastal
Ocean (HICO): Application of Space-based
Hyperspectral Imagery for the Protection of
the Nation’s Coastal Resources
Jessica Aukamp USEPA/NHEERL/Gulf Ecology Division
Donald Cobb USEPA/NHEERL/Atlantic Ecology Division
Robyn Conmy USEPA/National Risk Management
Research Laboratory/Land Remediation
and Pollution Control
George Craven USEPA/NHEERL/Gulf Ecology Division
Richard Gould Naval Research Laboratory/ Bio-optical
Physical Processes and Remote Sensing
Section
James Hagy USEPA/NHEERL/Gulf Ecology Division
Darryl Keith* USEPA/NHEERL/Atlantic Ecology Division
John Lehrter USEPA/NHEERL/Gulf Ecology Division
Ross Lunetta USEPA/National Exposure Research
Laboratory/Environmental Services Division
Michael Murrell USEPA/NHEERL/Gulf Ecology Division
Kenneth Rocha USEPA/NHEERL/Atlantic Ecology Division
Blake Schaeffer USEPA/NHEERL/Gulf Ecology Division
*email: keith.darryl@epa.gov

National Health and Environmental Effects Research Laboratory/ Atlantic Ecology Division
1
The U.S. Environmental Protection
Agency’s mandate to protect human health
and the environment requires innovative
and sustainable solutions for addressing
the Nation’s environmental problems.
HICO offers EPA and the environmental
monitoring community an unprecedented
opportunity to observe changes in coastal
and estuarine water quality across a range
of spatial scales not possible with field-
based monitoring.

2
What is ocean/estuary color?
Rrs(0+,λ) = Lw (0+,λ)/ Es(0+,λ)
Rrs = remotely sensed reflectance (1/sr)
Lw (0+, λ) = water leaving radiance
measured above the air/water interface
(W m-2 sr-1),
Es ((0+, λ) = downwelling irradiance
measured above the air/water interface
(W m-2 sr-1)
Definition of Remotely Sensed
Reflectance (Rrs)
Remotely sensed
reflectance
Remotely sensed
reflectance

3
Use HICO imagery to develop a novel space-based
environmental monitoring system that provides
information for the sustainable management of
coastal ecosystems.
To demonstrate that water quality information
derived from HICO could be incorporated into a
prototype smart phone application to disseminate
data to managers in the EPA Office of Water.
Program Objectives
Water quality news reports may change the social and economic
dynamics for the Nation to not only be aware of its water quality
conditions but support sustainable practices to maintain or
improve conditions at their favorite recreational areas.

4
• HICO is intended as a pathfinder for follow-on sensors designed with better
resolution and for routine observations of coastal, riverine, and estuarine
waters (Lucke et al., 2011).
• Built on the legacy of the NRL Ocean Portable Hyperspectral Imager for Low-Light
Spectroscopy (Ocean PHILLS) airborne imagers and funded as an Innovative
Naval Prototype by the Office of Naval Research
• January, 2007: HICO selected to fly on the International Space Station (ISS)
• November, 2007: Construction began following the Critical Design Review
• September, 2008: Space-qualified instrument delivered to the DOD Space Test
Program for integration and spacecraft-level testing
• April, 2009: Shipped to Japan Aerospace Exploration Agency (JAXA) for launch
• September 10, 2009: HICO launched on JAXA H-II Transfer Vehicle (HTV)
• September 24, 2009: HICO installed on ISS Japanese Module Exposed Facility
Hyperspectral Imager for the Coastal
Ocean (HICO).... Intent and a bit of history

5
HICO Viewing Slit
spectrometer
Hyperspectral Imager for the Coastal Ocean (HICO)
1st spaceborne imaging spectrometer specifically made for the
environmental characterization of the coastal ocean from space
HICO is installed in the HICO-RAIDS experiment payload
(HREP) on the Japanese Experiment Module - Exposed Facility
camera

6
To increase scene access frequency+45 to -30 degCross-track pointing
Data volume and transmission constraints1 maximumScenes per orbit
Large enough to capture the scale of
coastal dynamics
Adequate for scale of selected coastal
ocean features
Sensor response to be insensitive to
polarization of light from scene
Provides adequate Signal to Noise Ratio
after atmospheric removal
Derived from Spectral Range and
Spectral Channel Width
Sufficient to resolve spectral features
All water-penetrating wavelengths plus
Near Infrared for atmospheric correction
Rationale
~100
Number of Spectral
Channels
~50 x 200 kmScene Size
~100 meters
Ground Sample
Distance at Nadir
< 5%Polarization Sensitivity
> 200 to 1
for 5% albedo scene
(10 nm spectral binning)
Signal-to-Noise Ratio
for water-penetrating
wavelengths
5.7 nmSpectral Channel Width
380 to 960 nmSpectral Range
PerformanceParameter
Arnone et al., (2009) HICO for NASA Gulf Workshop
HICO Tech Specs

7
Program Implementation
Collected 49 images from
four estuaries along NW
Florida during April 2010 to
May 2012 during ISS
Expeditions 24 - 31
Pensacola, Choctawhatchee,
and St. Andrew Bays are
shallow (~4.0 m), microtidal
(tidal range ~ 1.0 m) brackish
water estuaries. St. Joseph
Bay is slightly deeper ( ~8 m)
and not influenced by the
inflow of fresh water.
Pensacola Bay
Choctowhatchee
Bay
St. Andrew
Bay
St.
Joseph
Bay

Field Validation Program
Pensacola Bay
Choctawhatchee Bay
St. Joseph Bay
St. Andrew Bay
Sample
stations
Green = water
quality moorings
(chl a, turbidity,
and CDOM)
Yellow = above
water radiance,
temp, salinity, and
optical properties
Red = same as
yellow + discrete
water samples

Using small boat surveys within each estuary, collected and
processed water column profile and above-water
hyperspectral data (Rrs) and water quality samples (Chl a,
TSS, CDOM, salinity)
Field Validation Program – Part 1
Attempted to conduct sampling within 1-3 days of an ISS overflight
Laboratory analysisAbove-water radiometryWater column profiling

10
Field Validation Program – Part 2
Autonomous underwater vehicles (AUVs) were deployed concurrently with HICO
overpasses by the NRL Stennis Space Center Detachment (NRL/SSC) and the USEPA
Atlantic Ecology Division (AED)
NRL/SSC deployed a Slocum electric
glider off of Pensacola Bay along the 15-
30 m bathymetric contours which
recorded:
temperature
salinity (conductivity)
chlorophyll and CDOM florescence
Slocum
G2 Glider
Designed and
manufactured
by Webb Research
AED deployed a REMUS (Remote
Environmental Monitoring Unit) AUV in
Pensacola and Choctowhatchee Bays
which recorded:
temperature
salinity (conductivity)
chlorophyll and turbidity
at approximately one meter depth
Photo courtesy of Kongsberg Maritime

11
HICO Image Processing: Optical Components of a
Coastal Scene
Multiple light paths
• Scattering due to:
– atmosphere
– aerosols
– water surface
– suspended particles
– bottom
• Absorption due to:
– atmosphere
– aerosols
– suspended particles
– dissolved matter

12
HICO Image Processing Steps
Processing done with Excelis VIS ENVI 4.7 software
Open HICO Level 1b Image with calibrated TOA
at-sensor radiances
Recover true at-sensor radiance valuesStep 2
Step 7
Steps 8 -
9
Create GLT + Geolocate + Warp
Images
Step 10
Clip estuary shapefile to Warped
image
Step 11
Export clipped Rrs data to EXCEL
CDOMTurbidity
TSM Chl a
Step 3
Step 1
Sun glint correction
Cloud
removal (if
needed)
Step 5 Convert from W/m2/um/sr to
uW/cm2/nm/sr
Step 4
Step 6
Offshore pixel subtraction
Convert at-sensor Reflectance to
Remote sensing Reflectance
Convert at-sensor Radiance to
Reflectance
Determine Mean
Solar Irradiance
(F0)
Determine diffuse
transmittance from
sun to pixel (t0)

Spectral match-ups between HyperSAS (dotted
line) and HICO spectral signature (solid line).
iss2012016.0116.193730.L1B_PensacolaBay_des.v03.9170.20120117211554.100m.hico.bil
Step 1: Level 1b calibrated radiance Step 4:Offshore pixel subtraction (W/m2/um/sr)
Step 7: Remotely sensed Reflectance (1/sr)
0.000
0.002
0.004
0.006
0.008
0.010
405
428
451
474
497
520
543
565
588
611
634
657
680
703
726
Rrs(1/sr)
Wavelength (nm)
PB 18: Redfish Cove

14
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
405
439
474
508
543
577
611
646
680
714
Rrs(sr-1)
Wavelength (nm)
PB06: June 2, 2011
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
0.01
405
439
474
508
543
577
611
646
680
714
Rrs(sr-1)
Wavelength (nm)
PB 16: June 2, 2011
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
405
439
474
508
543
577
611
646
680
714
Rrs(sr-1)
Wavelength (nm)
PB 15: June 2, 2011
0
0.001
0.002
0.003
0.004
0.005
0.006
0.007
0.008
0.009
0.01
405
439
474
508
543
577
611
646
680
714
Rrs(sr-1)
Wavelength (nm)
PB04: June 2, 2011
HICO HYPERSAS
PB04
PB06
PB16
PB15
Spectral Match-ups
Pensacola Bay, FL

15
0
2
4
6
8
10
-0.200 -0.100 0.000 0.100 0.200
HICO[ (1/Rrs674-1/Rrs703)*Rrs726]
R2 = 0.68
0
2
4
6
8
10
12
0 2 4 6 8 10 12
Measuredchla(ug/L)
HICO predicted chl a (ug/L)
R2 = 0.82
RMSE = 1.7 ug/L
Chl a = 19.264 X [a] + 6.614
a = [1/Rrs(674) – 1/Rrs(703)]x Rrs(726)
approach of Gitelson et al., 2011
Chl a: indicator of phytoplankton abundance and eutrophication

16
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0.0 0.5 1.0 1.5 2.0 2.5
CTDNTU
HICO NTU
R2 = 0.67
RSME = 0.56 NTU
n = 14
Turbidity = 2*106 X [Rrs(646)2.7848]
R2 = 0.72
n = 18
0.10
1.00
10.00
0.003 0.005 0.007 0.009
Turbidity(NTU)
HICO Rrs(646)
approach of Chen et al., 2007
Turbidity is an indicator of the distribution of total
suspended matter in estuaries

17
Colored Dissolved Organic Matter Absorption: indicator of light
attenuation in estuaries
R² = 0.93
RMSE = 0.21 /m
n = 18
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0.0 1.0 2.0 3.0 4.0Meas.CDOMabsorption
HICO CDOM absorption
R² = 0.60
n = 17
0.0
0.5
1.0
1.5
2.0
2.5
0.0 0.5 1.0 1.5 2.0 2.5
ag(412)(1/m)
HICO Rrs(670)/Rrs(490)
ag412 (m-1) = 0.8426 x [Rrs(670)/Rrs(490)] – 0.032
approach of Bowers et al., 2004

HICO/MODIS Comparison
MODIS scene 19:00 GMT, 7 minutes before HICO
overpass
Adj R2 = 0.83
HICO scene
Pixels
common to
both
images and
used in the
match-up
October
28, 2011
HICO and
MODIS
image date
Dashed line =
HyperSAS Rrs
Dotted line = HICO
Rrs at MODIS
bandwidths
1:1

19
Using atmospherically corrected HICO imagery and a comprehensive
field validation program, regionally-tuned algorithms were developed
to estimate the spatial distribution of chlorophyll a, colored dissolved
organic matter, and turbidity for four estuaries along the northwest
coast of Florida from April 2010 – May 2012.
Program Summary
The HICO-derived water quality data from
this project have been uploaded to a
internal EPA HICO website for review and
use by the EPA Office of Water and a
prototype mobile application has been
completed.

20
Conclusions
HICO helped us to show that it is possible for a hyperspectral space-based
sensor to produce products that meet the needs of EPA.
While the potential benefits are many, there are several issues that must be
resolved before HICO images and data can be incorporated into routine
monitoring programs of EPA
• HICO is currently limited to only one image per orbit.
• ISS overpass times are difficult to precisely predict. These
uncertainties led to the rescheduling of planned image acquisitions which at
times impacted the effective deployment of crews for field validation activities.
HICO has the potential to be a valuable monitoring tool, if transitioned to a
constellation of sensors.

21
Special Thanks to:
Crews on ISS Expeditions 24 - 31
Naval Research Laboratory Remote Sensing Division
Oregon State University
NASA ISS Program
American Astronautical Society
and
EPA Office of Research and Development
EPA Pathfinder Innovation Program (Grant 2011)
EPA Safe and Sustainable Waters Research Program

EPA Hyperspectral Imagery Coastal Protection

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