<div dir="ltr">Ciao Luca, <div><br></div><div>Just following the example in t.rast.aggregate.ds manual page, I added a section for seasonal aggregation [0] to the "Temporal data processing" wiki, showing how to get astro_seasonal aggregation from a daily time series. I guess you already solved the problem, but at least it is there for future reference :)</div><div><br></div><div>It would be awesome, anyway, to have astro_season as a predefined granularity!! Way more simple!!! </div><div><br></div><div>Cheers, </div><div>Vero</div><div><br></div><div>[0] <a href="https://grasswiki.osgeo.org/wiki/Temporal_data_processing/seasonal_aggregation">https://grasswiki.osgeo.org/wiki/Temporal_data_processing/seasonal_aggregation</a></div></div><div class="gmail_extra"><br><div class="gmail_quote">2015-08-19 10:46 GMT-03:00 Sören Gebbert <span dir="ltr"><<a href="mailto:soerengebbert@googlemail.com" target="_blank">soerengebbert@googlemail.com</a>></span>:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><p dir="ltr">Hi Luca,</p><div><div class="h5">
<p dir="ltr">Am 19.08.2015 12:01 schrieb "Luca Delucchi" <<a href="mailto:lucadeluge@gmail.com" target="_blank">lucadeluge@gmail.com</a>>:<br>
><br>
> On 14 August 2015 at 00:35, Sören Gebbert <<a href="mailto:soerengebbert@googlemail.com" target="_blank">soerengebbert@googlemail.com</a>> wrote:<br>
> > Hi,<br>
><br>
> Hi,<br>
><br>
> > to reduce a bit of confusion. You can apply a time interval of<br>
> > arbitrary size to a map layer. Use the input file option of t.register<br>
> > and specify the interval size in the input file:<br>
> ><br>
><br>
> yes in t.register there aren't problems...<br>
><br>
> > name|start_time|end_time<br>
> > map_1|2001-03-22 00:00:00|2001-06-21 00:00:00<br>
> > map_2|2001-06-21 00:00:00|2001-09-24 00:00:00<br>
> > map_3|2001-09-24 00:00:00|2001-12-21 00:00:00<br>
> > map_4|2001-12-21 00:00:00|2002-03-22 00:00:00<br>
> > ...<br>
> ><br>
> > Be aware that time intervals in the temporal framework are left<br>
> > closed, right open intervals. Hence, the end time is not part of the<br>
> > interval, but the start time of a potential successor.<br>
> > This assures gap free creation of temporal topological correct time series.<br>
> ><br>
> > The computed granularity of the resulting space-time dataset (STDS)<br>
> > will be 1 day, since 1 day is the greatest common divider of all the<br>
> > seasonal time intervals in the STDS.<br>
> > IMHO, there is no urgent need to support a user defined granularity in<br>
> > the temporal framework. The Gregorian Calendar hierarchy is almost<br>
> > sufficient.<br>
> ><br>
><br>
> for the aggregation I think this is needed...<br>
> how can I calculate average seasonal temperature starting from a daily<br>
> temperatures temporal dataset?</p>
</div></div><p dir="ltr">Use t.rast.aggregate.ds, the input is the daily strds, the sampling stds should have seasonal intervals. Then use average as method. The output will have seasonal aggregated temperatures.</p>
<p dir="ltr">Best regards<br>
Soeren</p><div class="HOEnZb"><div class="h5">
<p dir="ltr">><br>
> > Best regards<br>
> > Soeren<br>
> ><br>
><br>
><br>
> --<br>
> ciao<br>
> Luca<br>
><br>
> <a href="http://gis.cri.fmach.it/delucchi/" target="_blank">http://gis.cri.fmach.it/delucchi/</a><br>
> <a href="http://www.lucadelu.org" target="_blank">www.lucadelu.org</a><br>
</p>
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