1. Shallow Water Bathymetry of Singapore’s Highly Turbid Coastal Waters: A Comparative Approach James F. Bramante, Durairaju Kumaran Raju, Sin Tsai Min Tropical Marine Science Institute, National University of Singapore

2. Purpose Determine effectiveness of multispectral algorithms in Singapore Determine how extra 4 bands may help Develop high resolution shallow-water bathymetric map Coral/Benthic Surveys Interface into more complicated IOP models Determine possible new benthic habitats

3. Study Area

4. Study Area (cont.)

5. Marine Environment Study Area (cont.) Wild Singapore Seagrass-watch Pulau Hantu

6. Obstacles High turbidity Sediment plumes Few bathymetric data points in shallow waters

7. Obstacles (cont.) High shipping traffic Abundant clouds Mixed aerosols from city and ocean

8. Atmospheric Correction Stock image (no concurrent field measurements) Access to atmospheric information limited Clear boundaries for cloud, shadowed, and deep ocean pixels

9. Atmospheric Correction (cont.) Cloud-shadow empirical algorithm Reinersman et al. (1998) and Lee et al. (2005) Fig. 1 taken from Reinersman et al. (1998)

10. Atmospheric Correction (cont.) General Equation: Cloud-Shadow Eq: Assumptions: Lee et al. simplification:

11. Atmospheric Correction (cont.) Path radiance: Reflectance: Water-air boundary correction:

12. Atmospheric Correction (cont.) Band 2 (Blue) Average Radiance Band 2 Atmospherically Corrected Reflectance

13. Bathymetry Algorithms LUT Classification Linear Ratio Algorithm (Stumpf et al. 2003) Linear Band Algorithm (Lyzenga et al. 2006) Compared results using conventional 4 bands and Worldview-2’s 8 bands

14. Bathymetry Algorithms (cont.) LUT Classification LUT Library n = 53 for 0 < depth ≤ 2 m Least squares comparison Attempted ratio classification 8-band4-band

15. Bathymetry Algorithms (cont.) Linear Ratio Based off of Beer’s law: Stumpf et al. 2003 :

16. Bathymetry Algorithms (cont.) Linear Band Lyzenga et al. 2006 : Non-real results when L WCj > L j

17. Results Lyzenga et al. AlgorithmBand Classification

18. Results (cont.) Lyzenga et al. AlgorithmBand Classification

19. Results – Platform Comparison

20. Results – Faulty Relationships

21. Conclusions With more validation, Lyzenga et al. model and band classifications may prove useful in turbid waters Assumed relationship between band absorption and depth must be re-examined in extremely turbid waters

22. Further Investigations Evaluated cloud-shadow atmospheric correction model against RT Model; former was validated and did not affect results much Attempting to use water-column index to adjust for water mass variation in Lyzenga algorithm Using spectroradiometer to modify semi- analytical models for Singapore