The desired values can be found in the xml file of the L1C product.
However, there is one weird thing that I encountered during processing.
It is associated with the presence data whose values exceed QUANTIFICATION_VALUE.
For example, data for 2016 QUANTIFICATION_VALUE in the scene with the snow coverage is 10,000!
But, most of the values in this scene exceeds QUANTIFICATION_VALUE. While my question is how to be in this case – the answer is no.
I have two questions about reflectance to radiance conversion and physical gains in L1C products metadata.
first of all, for some images (recently acquired) there are only 12 values for physical gains instead of 13 and I haven’t found yet any explanation about their meaning. Are they useful in some way for reflectance to radiance conversion? Which bands do they refer to?
A second question concerning the expression for conversion:
in this topic Distance of Earth-Sun roTOA is both multiplied and divided by U factor in 2 different posts and in this own topic is multiplied.
Which is the correct expression?
L = (UrToaESUNcos(theta))/PI
L = (rToaESUNcos(theta))/(PIU)
thanks a lot
Not sure if you got my email. Anyway, Sentinel-2A images are in JP2000 format. When importing in a GIS or matrix laboratory, divide each band by the scaling factor (10,000) to retrieve TOA reflectance (rTOA as I have posted in the formula above). Use rTOA to retrieve TOA Radiance in the equation above. Hope this helps. Sorry it took me a while to reply.
Thank you for the information. Actually, I am bit confused on the radiometric convertion and sen2cor. Since I need the reflectance value for the fusion between S2 and L8. I wonder which is more practical to be used ( radiometric convertion and sen2cor) and whether it is the same process or can be integrated.
For example L8, I have already process up to atmospheric correction and convert it to reflectance value using band math. Is it the same process for S2?
sen2cor is a plugin designed for transforming Sentinel-2 MSI data on L1C (Top-of-atmosphere (TOA) reflectance) to L2A (Bottom-of-atmosphere (BOA) reflectance). So, when you want to perform atmospheric correction to the Sentinel-2 data in sen2cor, you don’t have to transform it to TOA radiance first. So, basically, you just have to input the image file and let the plugin works.
A different steps is required when you want to perform atmospheric correction with another algorithm (e.g. FLAASH, which is built-in in commercial software such as ENVI). As the algorithm needs TOA radiance data as the input, you have to tranform the data first, which is from TOA reflectance to TOA radiance, using equation given by Igor above (also see Distance of Earth-Sun). Performing atmospheric correction (e.g. FLAASH) allows you to have Surface reflectance data as the output.