Select Points // Export StaMPS csv file

Hey guys, i have a Q related with the StaMPS export to csv file when i ejecuted the code:

load parms.mat;
ps_plot(‘v-do’, -1);
load ps_plot_v-do.mat;
lon2_str = cellstr(num2str(lon2));
lat2_str = cellstr(num2str(lat2));
lonlat2_str = strcat(lon2_str, lat2_str);
lonlat_str = strcat(cellstr(num2str(lonlat(:,1))), cellstr(num2str(lonlat(:,2))));
ind = ismember(lonlat_str, lonlat2_str);
disp = ph_disp(ind);
disp_ts = ph_mm(ind,:);
export_res = [lon2 lat2 disp disp_ts];
metarow = [ref_centre_lonlat NaN transpose(day)-1];
k = 0;
export_res = [export_res(1:k,:); metarow; export_res(k+1:end,:)];
export_res = table(export_res);
writetable(export_res,‘stamps_tsexport.csv’)

My question is How can select the export point, because this only show me 14 points. Before that i run ps_plot(‘v-do’, ‘ts’) and select random points in the graph.

Regards!

You define the radius around your selected point in the matlab window. 100 m is set by default, if you want more points exported you have to increase the radius and select an area with high ps density

Yes, i need select the radius and pin the graph, thanks a lot! The csv file can be exported to qgis directly?

If the csv contains latitude and longitude and an average displacement, you can import it into QGIS as a text file.

Maybe you can share the csv here so we can try.

stamps_tsexport.csv (15.8 KB)
Yes please, feel free to try. Now im installing Qgis.

I’m not 100% sure about the meaning of the columns, but at least the coordinates should be in the first two of them. This is how you can load it

You should consider using more images to get a denser set of points with more reliable predictions. Your points look rather random. Or did you just share a subset of your points?

Yes (subset). Short story: My first sucess analisys (Ángel Mellado Vasquez on LinkedIn: #PersistentScatterers #radar #Insar) was in Concepcion CIty im recently graduated from Chile, not big deal.

But somebody call me and ask if can set an analisys in a hill (3 points red togheter in the image). But in hills with trees cant reflect well. But for practice and test are good. I set 20 images and after 24 and compare the result. In 24 images i have less points (or less noise i think, 3 points red disapears). I try to change the parameters for landslide tested by [Höser 2018]:

|scla_deramp |'y'| |unwrap_time_win |24|
|unwrap_grid_size ||10| |unwrap_gold_n_win |8|
|`scn_time_win |50|

But matlab give me and error related with error using /matrix dimensions. In the forum says maybe change for a bigger area (i set a perimeter 46km and an area of 126km2). So only can run with the default parameters. Wherever, noting of these can be possible with you support. Here are the ps for 24 and 20 images, feel free to check!. Thanks a lot

ps_24.kml (1.9 MB)

ps_20.kml (2.8 MB)

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Yes, in rural areas, more images can lead to less identified ps, but in the end their information is more reliable.
Good job on integrating the values reported by Thorsten Höser!

unfortunatly i cant integrate the values by Thorsten because the matlab error /matrix dimensions. But if i can solve i post in this thread.

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