In my case it’s available, but check up the SNAP update. I thin band extractor already comes within SMAP.
Hello Forum
I run the Chlr processor using the C2X-Nets. As I run of a river I set the salinity to 0.1 and the temp to 25C
All the rest of the parameters are default with the exception of the “No uncertainties”; the processor
works well to separate the water body but the detected chlr, is way lower than a local sampling done (at lease 1 magnitude of volume). Any suggestion?
Thanks
GIancarlo
Dear sir thank you for your all Kind reply, But since I have not clear with how the C2RCC processer work if u don’t mind can u simplify me?
Thank You
Can you please specify your question? The general framework of the processor is described in the Help section of SNAP
You input Sentinel-2 (L1C) products and adjust the parameters in the second tab and then run it.
The chlorophyll and suspended matter concentrations are then stored in the conc folder:
In S2 C2RCC is common for all case 2 water for retrive chlorophyll or it may vary based on the region?
as long as you adjust the temperature and salinity value of the water and maybe some atmospheric parameters, you can apply it to different regions.
The quality can be different for different regions. You should have insitu data to compare the results with real data.
As @ABraun said, you.can provide salinity and temperature to improve the results.
Also the factors and exponen for tsm and chl computation can be adapted to match your region.
You have to find out which values are best.
When opening the properties for the band you can edit the values.
Once you found good values you can provide them to the processing.
You can find the equations in the properties
conc\_chl = iop\_apig^{1.04} \times 21.0
What C2RCC compuites is actually chlorophyll_a, so yes you can compare them.
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Hello mr.
I do not want to use Snap processors to estimate chlorophyll-a.
I would like to estimate chlorophyll-A in MATLAB software.
Does for input the Sentinel-2 L1C (TOA) data in MATLAB software require the atmospheric correction of Sentinel-2 L1C (TOA)?
Thank you Mr.
Yes, this would improve the accuracy of your results. There are some where the AC in negligible, but most computations benefit from an atmospheric correction. You could use the Sentinel-2 L2A data.
I have the Sentinel-2L1C image of April 4, 2019 from my case study.
But, the Sentinel-2L2A image of April 4, 2019 is not available in the database of the ESA (https://scihub.copernicus.eu/). please guide me.
If it is not available, you would need an atmospheric correction software. The common choice would be Sen2Cor plugin to SNAP (also possible to use stand-alone on command line). This should create the same product you would download from SciHub. Download here
https://step.esa.int/main/third-party-plugins-2/sen2cor/
and make sure you read the documentation. In case you run into problems, search this forum for Sen2Cor, because here is wast number of problem solving discussions - narrow the search also to version you use.
There are also alternative ways to do atmospheric correction, and the second obvious choice to try is iCOR-sentinel2-sta if you use SNAP, as it is available through “Tools/Manage external tools” menu in SNAP. I did not try iCOR yet, Sen2Cor works, but may not be that obvious to operate properly at first.
Without C2RCC processer For sentinel-2 chlorophyll-a and TSM estimation anyother mathod available by using SNAP?
I am not aware of other tool specifically for computing chl-a or TSM in SNAP, but you can of course use the Band maths tool in to try any algorithm based on band math published in scientific papers. In most cases you need L2A product (downloaded or created in SNAP from L1C), need to make sure all bands in the algorithm are rescaled to common resolution, then apply the formula from the paper.
Actually, if you are working on inland water bodies with chl-a content mostly in range 0-60(100) ug/l, you can even try my own algorithm for chl-a from article:
Brunclík, T., Danquah, K. a. B., 2018. Relativní radiometrická normalizace pro monitoring chlorofylu-a ve vodách pomocí družice Sentinel-2. Chemické listy 112, 866–869. (http://www.chemicke-listy.cz/ojs3/index.php/chemicke-listy/article/download/3244/3215/)
The article is in Czech, unfortunately.
The formula is: chl_a = 59.1770 * (B05/B04)^2 - 77.2041 * (B05/B04) + 23.2527 , where B05 and B04 are bands 5 and 4 of Sentinel-2 L2A image
and I would be curious if it gives reasonable results outside the area it was developed on. I additionally use a relative radiometric normalization on the L2A image, but for clean imagery (minimal cloud cover, no uncorrected residual haze) the algorithm works with satisfying precision without it for me.
I personally use GRASS GIS or QGIS for the computation, where it is is possible to mask out non-water areas or avoid them simply by dividing the whole formula by a water mask band, where water is 1 and land 0. Division by zero produces no-data value in QGIS, effectively limiting the computation results to water areas only. Not sure if that would work in SNAP, but you can use multiplying by the mask if it does not, getting zero instead of no-data outside water areas.
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How do i choose the correct CHL exponent and CHL Factor value for study area
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You would need to compare the processing results with in-situ data and then adapt the factors until they fit. Just usual research.
Or @abruescas do you have another suggestion?
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How to produce seasonal image from S2-C2RCC processed image
Thank You
With the Mosaicking or the Level-3 Binning tool.
Both to be found in the menu at Raster / Geometric Operations
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After mosaicking i tried C2RCC processor but my case it show someError like this.
- Another one query sir How to remove my cloud in my study area -please kindly mention procedure
Is it an option to run C2RCC on all subsets and then create the mosaic?