SARPROZ ©

1. 20 images is a relatively low number. so, you have to be careful in choosing things properly
2. using the coherence as a weight means using the spatial coherence to keep coherent data and discard not coherent one. if you use the STAR graph, you should not expect high coherence, because of STAR graph long baselines. it means discarding data. it…[Read more]

1. 20 images is a relatively low number. so, you have to be careful in choosing things properly
2. using the coherence as a weight means using the spatial coherence to keep coherent data and discard not coherent one. if you use the STAR graph, you should not expect high coherence, because of STAR graph long baselines. it means discarding data. it…[Read more]

1. 20 images is a relatively low number. so, you have to be careful in choosing things properly
2. using the coherence as a weight means using the spatial coherence to keep coherent data and discard not coherent one. if you use the STAR graph, you should not expect high coherence, because of STAR graph long baselines. it means discarding data. it…[Read more]

1. 20 images is a relatively low number. so, you have to be careful in choosing things properly
2. using the coherence as a weight means using the spatial coherence to keep coherent data and discard not coherent one. if you use the STAR graph, you should not expect high coherence, because of STAR graph long baselines. it means discarding data. it…[Read more]

1. 20 images is a relatively low number. so, you have to be careful in choosing things properly
2. using the coherence as a weight means using the spatial coherence to keep coherent data and discard not coherent one. if you use the STAR graph, you should not expect high coherence, because of STAR graph long baselines. it means discarding data. it…[Read more]

I apologise for the delayed thank you.
We appreciate the help. The results, with carefully consideration of the above suggestions, were found really close to the expectation we had.
Thank you again and always congrats on the work being done.

Hi Jaroslav,
surely, you can undo/recover lots of things in Sarproz (in fact, almost all operations).
In particular, you can undo “Residual fringes estimation and removal” by clicking on “reset flat/height constants”.
best

About a. b. and c. just go with a. The other options are still experimental.
About thresholds, use the suggested ones as starting point. If you are not happy, try to rise the minimum value for being more restrictive.

Thank you for the super fast response.
we are running now the data with what you suggested.

Regarding the graph analysis and refinement, we have looked at it, but we do not understand the parameters exactly what they exactly they are for. Checking the manual it doesn’t really go in depth:
(from manual)
3. press the button “go” in the “clusters…[Read more]

The result looks reasonable.
To check if the APS was well estimated, you the final “test” function. If the final coherence is high and evenly distributed, you are done. You can also plot the APS one by one to check for issues.
To understand if the height estimation range is correct, check the histogram of the connections residual height. You can…[Read more]

I also added this image.

Hi Dan,
I have tried killing everything, installing Matlab locally (rather than the University Matlab requiring network) and still have the same issue. When would be a good time for us to look at it via remote connection next week?

Thanks!
Estelle

You should follow the instructions:
“you need to send an email to licensing@sarproz.com attaching the file license.key ”
best

By looking at your images I have to make the following comments:
1. I am not sure if 0.7 ampl stab is a good threshold with 26 images. it would be useful to see the reflectivity map and the ampl stab map to have a better idea.
2. the range of height you are trying to estimate is too big. consider that you are processing connections (nearby…[Read more]