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Hello all, 

I am working on a time series dataset to detect deforestation over s1 time 
series (I am using grdh vv vh product) over all the french guyana. 

For time series over one area cover by one s1 data I am using the following 
processing chain which work well:
- calibration
- filtering
- Orthorectification
- clip all the data to have exactly the same area for all the data 
(projection, extent, cols, row...)
- Temporal filtering (python code using Quegan algorithm)
- Other thing  underdevelopment like threshold or classification of time 
serie statistic (stdev, median mean, quartile etc)

Now I want to apply this processing chain over all the data in French 
Guyana that is fully covered by 2 path, one with 3 consecutive data and one 
with 2.

So, at one time I need to overlay the 5 different data or do a mosaic.

My first idea was to process individually each data and then mosaic the 
data over the same path and so to my time series processing over one pathh 
and mosaic final result over the two pass.

However, as for Snap (but less), when I mosaic 2 consecutive orthorectified 
data over the same pass I have some time some gap as shown in the screen 
shot (gap are in white).

So I would like to know the best practices for this kind of task to don't 
have any gaps ?

In addition if you have tips for time series processing it's also 
interesting :)

Best and thank you in advance.

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