Tailored Algorithms for Ocean Colour applications at regional scales: geographic and optical approaches

Mark Dowellmark.dowell@jrc.it

&

Stewart Bernardsbernard@csir.co.za

Rationale• There is necessity to describe a considerable

amount of variability in Inherent Optical Property (IOP) subcomponent models.

• This is particularly true, if inversion algorithms are to be applicable at global scale yet remain quantitatively accurate in coastal & shelf seas.

• This is unlikely to be achieved in the foreseeable future, with a single representation of IOP subcomponents.– BEAM – Case2R

• The proposed approach is an algorithm framework more than a specific algorithm.

Defintitons

• Geographic

• Class-based

Regional vs. Class-Basedmake table!

Regional• Advantages

– Explicitly link to locally measured in-situ data

– May be “simpler”

– Accounts for physiological differences

• Disadvantages– Explicitly link to locally

measured in-situ data – not generalized

– May result in regional discontinuities

Class-based• Advantages

– Generic, “global”, can be generalized

– Can be used as a tool to identify “black holes”

– Seamless transitions

– Continuous improvements through additional on in-situ data

• Disadvantages– More complicated to

implement

– Computational more expensive – not much!

Stewart’s regional algorithmBackground

Figure 7. Satellite-derived images of 1-km resolution from the Medium Resolution Imaging Spectrometer (MERIS) sensor, detailing the development of the Gonyaulax polygramma bloom in the False Bay area in February–March 2007 and its transport along the shelf edge of the West Coast. The simultaneous development of a bloom dominated by the toxic Alexandrium catenella in the St. Helena Bay region is also evident. Chlorophyll a (Chl) products were calculated using merged data from the standard MERIS Algal 1 algorithm for Chl < 25 mg m-3 and a locally derived red-band empirical algorithm for Chl > 25 mg m-3. No flags were applied to the data so as to allow bloom transport to be observed in images where absolute Chl is relatively less important (except where high sun glint caused the failure of the Algal 1 product). [Pitcher et al 2008]

The Southern BenguelaA highly productive upwelling system, frequently suffering from harmful algal blooms, with considerable atmospheric variability. Both empirical and analytical algorithms have been developed for these high biomass waters, with buoy based validation of water leaving radiances. The next few years should see more buoy – and AERONET based validation of ocean and atmospheric algorithms

MERIS Sample ProductsMozambique Channel

27th October 2008

Algal 1 Chlorophyll aCase 1 algorithm

Algal 2 Chlorophyll aCase 2 algorithm

Yellow SubstanceCase 2 algorithm

Total Suspended MatterCase 2 algorithm

South African East Coast: Natal and Delagoa Bights, Sofala BanksDynamic coastal systems subject to extensive riverine influence and the oceanic influence of the Agulhas current; these are extremely good subjects regional algorithms dealing with high Case 2 variability. The next few years should see extensive radiometric and geophysical validation efforts, focusing initially on the Natal Bight.

Stewart’s regional algorithmExample Products

What to parameterize?

• Variance and Co-variance of Optically Active Constituents

• Parameterising IOP subcomponent models (or fit coefficients – for empirical algorithms)

• Different OWT different inversions method

• Avenue to spatial uncertainty estimates

• Regional value-added products

0 10 20 30

Forest

Wetland

Water

Reflectance Band 1

Ref

lect

ance

Ban

d 2

Mean class vector

Unknown measurement vector

Traditional minimum-distance criteria

Hard

0 10 20 30

Forest

Wetland

Water

Reflectance Band 1

Ref

lect

ance

Ban

d 2

Fuzzy graded membership

Water = 0.05Wetland = 0.65Forest = 0.30

Fuzzy

The approach undertaken adopts fuzzy logic to define and identify, in radiance space, distinct bio-optical provinces that implicitly reduce the

variance in the IOP subcomponent models.

In-situ Database

Rrs()

c

Cluster analysis

c

Sgd, aph*,…….

c Station data sorted by class

c Class based relationships

8 classes

Class Mi, i

Satellite Measurements c

Individual classderived products

Merged Product

c

c c

Calculatemembership

Rrs()

Advantages of fuzzy logic defined provinces

• They allow for dynamics both seasonal and inter-annual in the optical properties of a given region.

• They address the issue of transitions at the boundaries of provinces (through the fuzzy membership function of each class) thus resulting finally in the seamless reconstruction of a single geophysical product.

8 objectively identified classes in radiance space

Class 1 Class 2 Class 3 Class 4 Class 5 Class 6 Class 7 Class 8

May 2004 MERIS Global Composite

Benguela exampleI’m using the 2006 MODIS image

(A2006082123500.L2_LAC) it would be good to have your regional algorithm for the same

product and a RGB image

Benguela exampleMark’s image of classified optical water types+

membership maps

MERIS October 8th 2008

Relation to current understandingturbid water flag

After Morel and Bélanger 2006

Relation to current understandingturbid water flag

Class 1 Class 2 Class 3 Class 4 Class 5 Class 6 Class 7 Class 8

Class persistence36 month Time-series

Class 5 Class 6

Class 7 & 8

0 1

Class Persistencedistribution of classes dominant for more than 70%

of observations

Class 1 Class 2 Class 3 Class 4 Class 5 Class 6 Class 7 Class 8

Spatial Uncertainty Analysisderived from class based assessment of OC3M with NOMAD2

Why Not !?

Class –based GSM Class –based QAASgd varies based on class[0.0175,0.0164,0.0139,0.0147,0.0153,0.0128,0.0138,0.0121]aph*() varies dependent on class (i.e. slope of bbp) using Carder’s relationship

Sgd variable based on classat(443) versus rrs(443)/rrs(555) class basedat(555) versus at(443) class basedaph(443) versus Chl class based aph*(443)

One could imagine applying a tuning algorithm (e.g. simulatedannealing) to each class to determine optimimal class based model coefficients.

Amoeba - NLO Spectral Unmixing

Conclusions

Future initiatives• MERIS specific class-based model

parameterization

• Investigate feasibility of implementing BEAM module for class distribution– Eventual link to Regional C2R processor

• Consider the possibility of a proposal to G-POD to systematically process class distribution at basin and global scales.

• GSFC to implement code for mapping of Optical Water Type distributions in SEADAS

Proposed ROI WG• Initial proposal for a Regional bio-Optical algorithm

Initiative (ROI) presented at 2008 IOCCG meeting

• Establish central portal for information on regional OC algorithms, main focus:

– Capacity building

– Maps of water types

– Geographically located bibliography

– Protocols

– Round robin

• Expected to start some time in 2009

• If interested contact Mark Dowell (mark.dowell@jrc.it) or Stewart Bernard (sbernard@csir.co.za) to be added to mailing list

ChloroGIN• ChloroGIN is the Chlorophyll Globally

Integrated Network

• Conceived during a IOC/GOOS/POGO/GEO sponsored workshop in Plymouth, Sept 2006

• Addresses GEO task EC-06-07

– “Build upon existing initiatives e.g. ANTARES in South America … to develop a global network of organization-networks for ecosystems, and coordinate activities to strengthen observing capacity in developing countries. “

• ChloroGIN aims to promote in situ measurement of chlorophyll in combination with satellite derived estimates and associated products.