Hi,
I am new using Seadas. I've been trying to do 8 days averages using L2bin followed by L3mapgen.
I am not sure if I am using the right combination of settings in the L2bin processor since I add strange outcomes by using different settings.
First I just did the resolve=1 and the prodtype=8-day and the image was okay
After I saw that I should put the suite=SST since with sst is supposed to use only the LAND and HISOLZEN flags. In the end the image was almost white.
After I tried put the resolve=1, prodtype=8-day, suite=SST, flaguse automatically sets the LAND and HISOLZEN flags, qual_prod=flags_sst and I changed the qual_max from 2 to 0. I got a image with a lot more pixels but more noisy and with colder temperatures than the first one.
Can you please help me with this problem? Each settings should I chose for binning L2 Modis sst images?
Thank you!
MODIS SST L2bin
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OB.DAACx - SeanBailey
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MODIS SST L2bin
If you save the parameter file from your binning process, and attach it to a post, we may be better able to help. That said, if you are trying to replicate the standard SST binning (at higher resolution), then you have done what you need to do by setting suite=SST.
You don't need to change the qual_max value, as the binner uses a "best quality" approach (for example, if a bin previously filled with data of quality 2 would subsequently get a quality 0 pixel, only the quality 0 data is kept).
However, binning at 1km can result in a sparse output due to the way the binner functions. You can mitigate that a bit by using the "
Sean
You don't need to change the qual_max value, as the binner uses a "best quality" approach (for example, if a bin previously filled with data of quality 2 would subsequently get a quality 0 pixel, only the quality 0 data is kept).
However, binning at 1km can result in a sparse output due to the way the binner functions. You can mitigate that a bit by using the "
interp=area" option in l3mapgen.Sean
MODIS SST L2bin
Thank you for your insights!
I am analyzing images from a small region (95x61km) and I am retrieving data from some sampling points. I want to be conservative enough that I have confidence in the outputs of my 8-days binned images but not so conservative that I have no data at all.
I am uploading the images and the respective L2bin parameter file in here.attachment 1
I am analyzing images from a small region (95x61km) and I am retrieving data from some sampling points. I want to be conservative enough that I have confidence in the outputs of my 8-days binned images but not so conservative that I have no data at all.
I am uploading the images and the respective L2bin parameter file in here.attachment 1
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OB.DAACx - SeanBailey
- Posts: 1519
- Joined: Wed Sep 18, 2019 6:15 pm America/New_York
- Been thanked: 9 times
MODIS SST L2bin
OK, couple of points.
1)
2)
The defaults are fairly conservative. If you want to restrict to the higher quality data, you can do so at after the l3mapgen step, as the SMI file created will include a flag field that allows you to choose the quality you display.
Sean
1)
night should be set or left alone (suite=SST is for daytime, NSST is for nighttime and the suite will define night appropriately)2)
qual_prod needs to be a quality product, not a flag product. If you're using the suite, there is no need to redefine qual_prod as it will be properly set. This is quite likely the source of the oddities you are seeing.The defaults are fairly conservative. If you want to restrict to the higher quality data, you can do so at after the l3mapgen step, as the SMI file created will include a flag field that allows you to choose the quality you display.
Sean