I’m studying Sentinel 2 images. I have two problems: the first one, the results from SNAP are completly black images and I don’t what is happening or how can I resolve this; second one, I’m studying specific coordinates in ACOLITE, but when I analize the result on SNAP, I found out different coordinates, and as the first problem, I don’t khow what to do. Any suggestion will be really useful.
Regards, Natalya from Colombia
First off - I’m no expert either.
The Acolite user manual
states on page 6:
Sentinel-2 Provide the full path to the extracted .SAFE file. Make sure you have a L1C TOA bundle, not a L2 SR bundle.
When you open SNAP what do you import?
- your output of Acolite?
- original L1C?
- or L2A produced by ESA?
I was wondering if why I cannot ask a question. Please Admins fix my problems.
You just posted here …so … which is the problem you encounter? Create a topic?
Yes, I cannot ask my own questions.
In order to be able to post your own question you need to try to search about the issue you are having, see (read) similar topics, in order to gain some forum activity and to increase your trust level. It’s good that you mentioned this, it was a recent change made by ESA and now we know it’s working.
So just try to visit some topics related with your issue/activity.
Do you mean by browsing the questions, I can ask my issues?
One more thing, since I gave you good news, let me know how I can calculate soil moisture by Sentinel 1 and 2 in Google Earth Engine? I mean, which methods or ways?
Yes, try to search and read some related topics, e.g. some “soil moisture” topics:
This is a SNAP Forum, not a Google Earth Engine Forum, so the details you will find here about soil moisture are SNAP related.
I did try to search. But I was wondering if we can use both Sentinel 1 and 2 in SNAP to retrieve soil moisture. I know some methods like water cloud model and change detection method. Please put me on a right track to get it done.
I work in ocean remote sensing, but in general, when you want to retrieve geophysical quantities you should start with books and articles that deal with methods to derive the variables you are interested in, then look for sensors with appropriate characteristics. In the early days, with few sensors available, your only choice would be the sensor used to develop the methods. Now there are many sensors with overlapping capabilities, so you need a good understanding of the theory to know if a particular sensor will be useful for the geophysical variables of interest, the characteristics of your region, and the problems you want to solve. Soil moisture has many applications (crop modelling, hydrology, etc.).
The availability “ground truth” data is an important consideration – some algorithms are turned for a particular region, others aim for “global” coverage but with reduced accuracy or constraints on meterorlogical conditions. It is useful to know what has worked for others, but you need to consider how your needs differ from those of previous efforts.