Multitemporal image

Can I create color optical - RGB synthesis of multi-season images for vegitation and abandoned land analysis in SNAP?
For example, to create a pic, like this:

Can Sen2Three help in this? If “yes”, where to find an extended guide how to use it?

Refer to this thread to understand how it is done: Creating RGB image

Yes, it is possible to create virtual image of true color or pseudo color, to use the specific terms you could create multi-spectral band combinations, as it is explained in this video,

multi-spectral band combinations

Basically, in case of creating multi spectral combination, we should take the following points in our consideration, in case of Sentinel -2 bands scenario

1- The wavelength range of each band and it’s use, for example,

Source

2- The goal of this combination,

Band Selection in Sentinel-2 Satellite for Agriculture Applications

This is also good example,

Band Selection in Sentinel-2 Satellite for Agriculture Applications

It’s possible to use each band from different dates, also it’s possible to apply an index such as NDVI, and then create band combination, of different three dates of NDVI,

Technically you could use band math in SNAP, or in single image you could right click on the image name and create RGB, by selecting the bands represents of RGB, respectively,

Here also explains how to create a virtual bands from different products,

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Thank you very much! I did not notice that in the bandmaths possible to use different time products.

Special thanks for the hint with different NDVI data :blush:

Similar procedure could be done using any other index, for example MNDWI, Modified Normalized Difference Water Index, Or any other according to the goals of study,

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@falahfakhri how we can create a map of Avg vertical displacement rates(mm/yr) derived from sentinel-1 image ??? Also , the values are already in mm unit with approx one year tempral diff.

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this requires a combination of SNAP, python, matlab and StaMPS. It is carefully documented and discussed here: About the STaMPS category