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ORSL » Ocean and Coastal Waters » Algorithms

Index of Ocean and Coastal Waters Algorithms

The purpose of the Ocean and Coastal ORS Lab is to monitor and investigate the optical properties of complex coastal areas as well as clear open ocean waters. This is accomplished with remotely-sensed data, received from operational and research satellites, observing platforms and in situ data.

PageAlgorithmsAuthorUpdate
  
  1  IOP Neural Network Inversion for Ocean Color: MODIS     Ioannis Ioannou          12/07/2012     
  2  IOP Neural Network Inversion for Ocean Color: VIIRS     Ioannis Ioannou          12/07/2012     
  3  IOP Neural Network Inversion for Ocean Color: SeaWIFS     Ioannis Ioannou          12/07/2012     
  4  IOP Neural Network Inversion for Ocean Color: HABS     Ahmed El-habashi          04/14/2016     

Note: The previously presented algorithm, Neural_Network_Algorithm, which applied to MODIS alone, has been significantly expanded into the three now presented above (1, 2, 3). Please see the references included with each. The fourth (4) is a specific impementation of VIIRS for HABS retrievals.



IOP Neural Network Inversion for Ocean Color: MODIS

This is an implemention of the MODIS Neural Network Ioannou et.al. 2011, Ioannis Ioannou, The City College of New York, NY, NY 10031. This is the driver program to invert Rrs into IOPs at 442nm. This code will be adjusted as more products become available. You will only need to change the input file and the coastal data in the included code. See the README.txt for instructions. A MODIS file is included for an example of processing.

Click here to download 7-zip compressed archive. (31.006 Mb)

Click here to download zip compressed archive. (41.433 Mb)

Click here to download rar compressed archive. (28.991 Mb)


When using this algorithm, please cite both references:

Ioannis Ioannou, Alexander Gilerson, Barry Gross, Fred Moshary, and Samir Ahmed, "Deriving ocean color products using neural networks" Remote Sensing of Environment, in press.

Ioannou, I., Gilerson, A., Gross, B., Moshary F., and Ahmed, S. ,"Neural network approach to retrieve the inherent optical properties of the ocean from the observations of MODIS", Appl. Opt. 50, 3168-3186 (2011)

I. Ioannou, "Retrieval of inherent optical properties from reflectance spectra in oceanic and coastal waters with neural network modeling", Ph.D. dissertation 2011 (Department of Electrical Engineering, The City College of the City University of New York, NY, NY, 10031).

IOP Neural Network Inversion for Ocean Color: VIIRS

This is an implemention of the Neural Network Ioannou et.al. 2011, Ioannis Ioannou, The City College of New York, NY, NY 10031. This is the driver program to invert Rrs into IOPs at 442nm and [Chl]. This code will be adjusted as more products become available. You will only need to change the input file and the coastal data in the included code. See the README.txt for instructions. A sample file is included for an example of processing.

Click here to download 7-zip compressed archive. (25.426 Mb)

Click here to download zip compressed archive. (34.550 Mb)

Click here to download rar compressed archive. (23.274 Mb)


When using this algorithm, please cite both references:

Ioannis Ioannou, Alexander Gilerson, Barry Gross, Fred Moshary, and Samir Ahmed, "Deriving ocean color products using neural networks" Remote Sensing of Environment, in press.

Ioannou, I., Gilerson, A., Gross, B., Moshary F., and Ahmed, S. ,"Neural network approach to retrieve the inherent optical properties of the ocean from the observations of MODIS", Appl. Opt. 50, 3168-3186 (2011)

I. Ioannou, "Retrieval of inherent optical properties from reflectance spectra in oceanic and coastal waters with neural network modeling", Ph.D. dissertation 2011 (Department of Electrical Engineering, The City College of the City University of New York, NY, NY, 10031).

IOP Neural Network Inversion for Ocean Color: SeaWIFS

This is an implemention of the Neural Network Ioannou et.al. 2011, Ioannis Ioannou, The City College of New York, NY, NY 10031. This is the driver program to invert Rrs into IOPs at 442nm and [Chl]. This code will be adjusted as more products become available. You will only need to change the input file and the coastal data in the included code. See the README.txt for instructions. A sample file is included for an example of processing.

Click here to download 7-zip compressed archive. (61.650 Mb)

Click here to download zip compressed archive. (88.272 Mb)

Click here to download rar compressed archive. (54.787 Mb)


When using this algorithm, please cite both references:

Ioannis Ioannou, Alexander Gilerson, Barry Gross, Fred Moshary, and Samir Ahmed, "Deriving ocean color products using neural networks" Remote Sensing of Environment, in press.

Ioannou, I., Gilerson, A., Gross, B., Moshary F., and Ahmed, S. ,"Neural network approach to retrieve the inherent optical properties of the ocean from the observations of MODIS", Appl. Opt. 50, 3168-3186 (2011)

I. Ioannou, "Retrieval of inherent optical properties from reflectance spectra in oceanic and coastal waters with neural network modeling", Ph.D. dissertation 2011 (Department of Electrical Engineering, The City College of the City University of New York, NY, NY, 10031).

IOP Neural Network Inversion for Ocean Color: VIIRS HABS

This is an HABS implemention of the VIIRS Neural Network of Ioannou et.al. 2011, Ahmed El-habashi and Ioannis Ioannou, The City College of New York, NY, NY 10031. This is the driver program to invert Rrs into aph at 443nm. This code will be adjusted as more products become available. You will only need to change the input file and the coastal data in the included code. See the README.txt for instructions. A sample file is included for an example of processing.

Click here to download 7-zip compressed archive. (61.650 Mb)

Click here to download zip compressed archive. (88.272 Mb)


When using this algorithm, please cite these references:

Ahmed El-habashi, Ioannis Ioannou, Michelle Tomlinson, Richard Stumpf, and Sam Ahmed, "Satellite retrievals of Karenia brevis harmful algal blooms in the West Florida Shelf using neural networks and comparisons with other techniques" Remote Sensing 5.2 (2016), in press.

Ioannis Ioannou, Alexander Gilerson, Michael Ondrusek, Soe Hlaing, Robert Foster, Ahmed El-Habashi, Kaveh Bastani, and Samir Ahmed, "Remote estimation of in water constituents in coastal waters using neural networks" Proc. of SPIE, 2014, 9240.

I. Ioannou, "Retrieval of inherent optical properties from reflectance spectra in oceanic and coastal waters with neural network modeling", Ph.D. dissertation 2011 (Department of Electrical Engineering, The City College of the City University of New York, NY, NY, 10031).

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Program Code Copyright © Thomas Legbandt 2010 - 2016


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