Get documents about "Ocean Color Remote Sensing for Coastal Regions STAR NOAA
Shared by: benbenzhou
-
Stats
- views:
- 0
- posted:
- 12/11/2012
- language:
- English
- pages:
- 11
Document Sample
Ocean Color Remote Sensing for
Coastal Regions
Presented by
Menghua Wang
Center for Satellite Applications and Research (STAR) Review Image:
MODIS Land Group,
09 – 11 March 2010
NASA GSFC
March 2000
Requirement, Science, and Benefit
Requirement/Objective
• Ecosystems
– Protect, restore and manage the use of coastal and ocean resources through ecosystem-
based management
• Healthy and productive coastal and marine ecosystems that benefit society
• Advancing understanding of ecosystems to improve resource management
• A well informed public that acts as a steward of coastal and marine ecosystems
• Weather and Water
– Serve society’s needs for weather and water information
• Better, quicker, and more valuable weather and water information to support improved decisions
• Increase lead time and accuracy for weather and water warnings and forecasts
• Improve predictability of the onset, duration, and impact of hazardous and high-impact severe
weather and water events
Science
• How to provide accurate water optical, biological, and biogeochemical property data
in coastal and inland regions from satellite measurements?
Benefit
• Protect and monitor our ocean resource
• Improve water resources forecasting capabilities
• Protect and monitor water resources
• Understand the effect of environmental factors on human health and well-being
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 2
Satellite Ocean Color
Remote Sensing
Ocean Color Remote Sensing: Case 1, C = 0.1 mg/m 3
Derive the ocean water-leaving radiance Case 2, Sediment Dominated
Case 2, Yellow Substance
TOA Reflectance t()
spectra by accurately removing the 10-1
atmospheric and surface effects.
Ocean properties can then be derived
from the ocean water-leaving radiance
spectra. (a)
M80 model, a(865) = 0.1
= 60 o, = 45 o, = 90 o
At satellite altitude usually ~90% of 10-2
sensor-measured signal over 400 500 600 700 800 900
ocean comes from the atmosphere 50
Wavelength (nm)
& surface Case 1, C = 0.1 mg/m 3
– It is crucial to have accurate 40
Case-2, Sediment Dominated
Case-2, Yellow Substance
atmospheric correction and sensor
% of TOA tw()
calibration. 30 M80 model, a(865) = 0.1
– 0.5% error in atmospheric correction = 60 o, = 45 o, = 90 o
or calibration corresponds to possible 20
of ~5% in the derived ocean water-
leaving radiance. 10
– We need ~0.1% sensor calibration
accuracy. 0
400 500 600 700 800 900
Wavelength (nm)
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 3
SeaWiFS/MODIS Algorithm
SeaWiFS Chlorophyll-a Concentration
Routine Global Ocean Color Product (October 1997-December 2003)
Data from SeaWiFS/MODIS Using:
– Gordon and Wang (1994) atmospheric
correction algorithm.
– Assuming:
• Ocean is black at the near-infrared
(NIR) wavelengths.
• Aerosols are non- or weakly absorbing.
SeaWiFS/MODIS Experiences Show:
4
– High quality ocean color products for global [Lw()]N Unit: (mW/cm2 m sr)
open oceans (Case-1 waters). Slope = 0.9924, Intercept = 0.0536, R = 0.9478
3
– Significant efforts are needed for
[L ()] (SeaWiFS)
improvements of water color products in the
2
coastal and inland water regions: 555 nm
• Turbid waters: Violation of the NIR N
w 412 nm
443 nm
1
black ocean assumption 490 nm
510 nm
555 nm
• Strongly-absorbing aerosols:
510 nm
0
Violation of non- or weakly absorbing 0 1 2 3 4
aerosols [L ()] (In situ Data)
w N
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 4
Atmospheric Correction: SWIR Bands
(Wang & Shi, 2005; Wang, 2007)
At the shortwave IR (SWIR) wavelengths 103
(>~1000 nm), ocean water has much 102
(a) 1640 nm
Water Absorption (1/cm)
strongly absorption and ocean contributions 101
1240 nm
are significantly less. Thus, atmospheric 1000 nm
10 0 2130 nm
correction can be carried out for coastal
regions without using the bio-optical 10-1
model. 10-2
Water absorption for 869 nm, 1240 nm, 1640 10 -3 865 nm
Hale & Querry (1973)
Segelstein (1981)
Kou et al. (1993)
nm, and 2130 nm are 5 m-1, 88 m-1, 498 m-1,
10-4
and 2200 m-1, respectively. 400 600 800 1000 1200 1400 1600 1800 2000 2200
Wavelength (nm)
Examples using the MODIS Aqua 1240 and 2130 nm data to derive the ocean color
products are provided.
We use the SWIR band (1240 nm) for the cloud masking. This is necessary for
coastal region waters.
Require sufficient SNR characteristics for the SWIR bands and the SWIR
atmospheric correction has slight larger noises at the short visible bands (compared
with those from the NIR algorithm).
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 5
Results from SWIR Algorithm
(U.S. East Coast)
Chlorophyll-a
April 2002-2007
In Situ In Situ
MODIS (NIR) MODIS
(NIR-SWIR)
Chlorophyll-a Comparison
Results in Chesapeake Bay
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 6
Results from SWIR Algorithm
(China East Coast)
100
March 22, 2003 (a) April 5, 2003 (b)
o o o o
(120.5 E, 36.0 N) (123.0 E, 33.0 N)
Time Diff: 4.2 hrs Time Diff: 2.5 hrs
Reflectance [w()]N
o o
o
= 36.7 , = 35.5
o
= 31.2 , = 1.7
10-1 0 0
10-2
In Situ Data
MODIS-Aqua China East Coast
-3
10
400 500 600 700 800 500 600 700 800 900
Wavelength (nm)
100
September 25, 2003 (c) September 23, 2003 (d)
o o o o
(122.3 E, 31.5 N) (122.2 E, 30.5 N)
Time Diff: 2.2 hrs Time Diff: -0.4 hrs
Reflectance [w()]N
o o
= 33.8 , = 54.7 o
= 33.1 , = 43.8
o
-1 0 0
10
10-2
In Situ Data
MODIS-Aqua China East Coast
-3
10
400 500 600 700 800 500 600 700 800 900
Wavelength (nm)
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 7
New Ocean Color Processing
SWIR-based
Global Ocean
Color Data
Processing at
NOAA/STAR
July, 2005
Standard Data Processing
Old
Chlorophyll-a
0.01-10 (mg/m3)
(Log scale)
New
11 peer-reviewed
papers about July, 2005
NIR-SWIR Data Processing
algorithms &
validations since 2005
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 8
Diffuse Attenuation Coefficient for
Turbid Conditions
Development of New Water
Diffuse Attenuation
Coefficient Kd(490) Algorithm
for the Chesapeake Bay and
Turbid Coastal Waters Using
the MODIS Data
July, 2005 Standard Data Processing
Old Old
Wang, M., S. Son, and L. W. Harding Jr., “Retrieval of
diffuse attenuation coefficient in the Chesapeake
Bay and turbid ocean regions for satellite ocean
color applications,” J. Geophys. Res., 114,
C10011, doi:10.1029/2009JC005286, 2009.
New New
Validation Results
July, 2005
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 9
Current Research and
Development Activities
Transition of Research to Operational for the SWIR-Based Algorithms:
Working with the NOAA data operational partners, we have been working on implementing the
SWIR-based ocean color data processing system into the NOAA operational data processing
system.
Near real time ocean color products will be produced using the SWIR-based algorithms for the U.S.
coastal regions in the NOAA CoastWatch Program.
Improved ocean color data, e.g., new Kd(490) product for turbid waters, will be generated.
NPOESS (NPP)-VIIRS Ocean Color Cal/Val:
On-orbit Vicarious Calibration for the VIIRS ocean color products.
NOAA VIIRS ocean color data processing.
VIIRS ocean color product validation.
Algorithm Development and Ocean Color Data Applications:
Algorithms development (e.g., for dealing with the absorbing aerosols in coastal region) and
refinement for ocean coastal and inland waters.
Various ocean color data applications for ocean coastal and inland waters.
Future Ocean Color Satellite Missions:
NASA Aerosol, Cloud, and Ecosystem (ACE) Mission.
NASA Geostationary Coastal and Air Pollution Events (GEO-CAPE) Mission.
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 10
Challenges and Path Forward
• Science challenges
– Accurate remote sensing of the water properties is still
challenges for:
• (a) complex coastal and inland waters and
• (b) strongly absorbing aerosols.
• Next steps
– Continue efforts for improving the remote sensing data
products for coastal and inland waters.
• Transition Path
– We have been working on transition of research to
operational for the SWIR-based algorithms.
– The SWIR-based data processing will be operational this
year.
Center for Satellite Applications and Research (STAR) Review
09 – 11 March 2010 11
