Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2000. / Includes bibliographical references (leaves 93-94). / The use of remotely sensed oceanographic data would be greatly benefited by being able to detect circulation features automatically through edge detection. In the Black Sea, the use of edge detection to identify fronts can be used to study the effects of river input on circulation patterns and biological and physical interactions. The use of edge detection on remotely sensed chlorophyll data is limited by noisy data, inaccurate measurements, temporal and spatial gaps in data, and limitations on computational power. The algorithm described in this thesis utilizes image processing techniques to create an edge detection process that shows the effects of the Danube river input on Black Sea circulation patterns with little computational complexity. / by Ashwini G. Deshpande. / S.M.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/58165 |
| Date | January 2000 |
| Creators | Deshpande, Ashwini G. (Ashwini Ganesh), 1977- |
| Contributors | Paola Malanotte-Rizzoli., Massachusetts Institute of Technology. Dept. of Earth, Atmospheric, and Planetary Sciences., Massachusetts Institute of Technology. Dept. of Earth, Atmospheric, and Planetary Sciences. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 94 leaves, application/pdf |
| Rights | M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission., http://dspace.mit.edu/handle/1721.1/7582 |
Page generated in 0.0021 seconds