1. Morphological Interpretation of Seamounts in Tutuila, American Samoa: Inferring Probable Genesis Through Shape and Distribution Analysis Morphological Interpretation of Seamounts in Tutuila, American Samoa: Inferring Probable Genesis Through Shape and Distribution Analysis Jed Roberts GEO 580 Project 6/7/2006 Jed Roberts GEO 580 Project 6/7/2006

2. Image produced by the National Park Service Study Area

3. Tutuila, American Samoa Image produced by the National Park Service

5. Multibeam Bathymetry Grid 200 meter resolution Depth range from sea level to 5300 meters below sea level Collected in 2002 by Revelle Research Vessel Numerous volcanic seamounts

6. Define Seamounts 300 meters or more above average baseline Identify characteristic cross-sections Avoid bathymetric influence of nearby islands –Cross-sections typically parallel to bathymetric gradient Avoid incomplete cross-sections due to data gaps

7. Shape Statistics Diagrams from Smith 1988 Basal Diameter Summit Diameter Height Average Slope Flatness (ratio of summit to base)

8. Shape Statistic Associations Basal Diameter as control of Height

9. Shape Statistic Associations Height as control of Average Slope

10. Shape Statistic Associations Height as control of Flatness

11. Create Point Feature Class 12 seamounts met criteria Height range: 380 to 680 meters Populate feature class with shape statistics Export.CSV file for distribution analysis

12. Geographically Weighted Regression Creates weighted regression model for each point and averages intercepts Accounts for spatial variability

13. GWR Results Basal Diameter as control of Height

14. GWR Results Height as control of Average Slope

15. GWR Results Height as control of Flatness

16. Identifying Spatial Variability Comparison of GWR model to global regression model reveals that spatial variability is a factor in this “association” No apparent correlation Too few observations for statistical significance

17. Morphological Interpretation Basal diameter and height association coincides with observations by Smith (1988) of larger seamounts (500 to 3800 meters) Height as control of slope (Smith 1988) not as strong with smaller seamounts Isolated seamounts more characteristic of point source magma intrusions Cause of asymmetrical elongation in seamounts unclear –Too few observations of elongation –Lithospheric fractures? –Point source magma flowing down island slope?

18. Uncertainty One seamount, or two?

19. Conclusions and Improvements Need more observations! –Reduce arbitrary height cut-off –Expand study area (thesis!) Use multiple cross-sections for each seamount –Help to account for elongation GWR reveals spatial variability, but not significantly with any correlatable variables Additional shape statistics –Volume –Maximum slope

20. References Fotheringham, A. S., Charlton, M. E., and Brunsdon C. 1998. Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis. Environment and Planning A. 30: 1905-27. Smith, D. K. 1988. Shape analysis of Pacific seamounts. Earth and Planetary Science Letters. 90: 457-66.