Subject: Marine Geospatial Ecology Tools (MGET) help
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| From: | "Jason Roberts" <> |
|---|---|
| To: | "'Nicolas HOEPFFNER'" <> |
| Cc: | <> |
| Subject: | RE: [mget-help] front detection |
| Date: | Mon, 22 Nov 2010 09:35:48 -0500 |
Dear Nicholas, I’m glad to hear you are having some success applying the tool to MODIS L3 SST. Our group has not used it on chlorophyll images so I cannot advise you on the best configuration of the parameters. But I recall that the following paper applied the Cayula-Cornillon algorithm to SeaWiFS images: Bontempi, P. S. and J. A. Yoder (2004) Spatial variability in SeaWiFS imagery of the South Atlantic bight as evidenced by gradients (fronts) in chlorophyll a and water-leaving radiance. Deep-Sea Research II 51(2004): 1019-1032. I believe those images were MODIS level 2, not level 3. The level 2 data provide a higher resolution but can be more difficult to work with, as they are swaths rather than global grids. The SeaDAS tool from NASA is the best tool to manipulate these. When I last used it, it only ran on LINUX but was packaged in a virtual machine that you could run inside of Windows. If you are skilled with operating systems, it should not be too much trouble to use SeaDAS to produce rasters in ArcGIS-readable format and then apply the MGET tool to them. Because chlorophyll occurs in such concentrated patches, I wondered whether it would be appropriate to log transform the values prior to identifying fronts. This would produce a better distribution of values for the histogramming part of the algorithm to work with. On the other hand, it might not be ecologically appropriate, depending on your original reason for wanting to identify chlorophyll fronts. Finally, Igor Belkin () is an active researcher in the area of fronts. He recently coordinated a special issue on fronts for the Journal of Marine Systems (see here) which included a new front-detection algorithm for SST and chlorophyll. Those articles might be useful to you. I’m sure he can advise you on how well the Cayula-Cornillon algorithm works with chlorophyll, and may be able to point you to additional sources of information. We hope to incorporate Igor’s algorithm in to MGET at some point, but it is not a priority at this time. I hope that helps, Jason From: Nicolas HOEPFFNER [mailto:] Dear Sir, As part of our research activities, we are using the front detection tool that we have extracted from MGET software. So far we have run the tool successfully with SST images (MODIS 4km data), optimizing the parameters to detect major fronts in our study area. However, we have some problem to use the code with Chlorophyll images (level 3 MODIS data). Would you know about any reference publications from scientists having used this algorithm with chlorophyll data and the way to optimize the parameters within the code ? any help on this matter would be very much appreciated thanking you nicolas Nicolas Hoepffner European Commission - Joint Research Centre |