<div dir="ltr">That's right, Ivan!<div>End of year mental death, sorry for the noise...<div><br></div><div>Vero</div></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">El vie, 29 dic 2023 a las 15:34, Ivan Marchesini (<<a href="mailto:ivan.marchesini@gmail.com">ivan.marchesini@gmail.com</a>>) escribió:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><u></u>
<div>
<p>Hi veronica<br>
</p>
<blockquote type="cite">
<div dir="ltr">
<div><br>
</div>
<div>I see what you did with creating the days time series. In
that way you acknowledge irregular gaps, right? </div>
</div>
</blockquote>
yes this is the reason<br>
<blockquote type="cite">
<div dir="ltr">
<div><br>
</div>
<div>However, why do you multiply by days strds? From my
understanding, detrending by subtracting the results of a
model obbeys this rule: value(t) = observed(t) - predicted(t).
Then, this mystrds-(regression_offset+regression_slope*days)
should be
mystrds-(regression_offset+regression_slope*mystrds).</div>
</div>
</blockquote>
<p>hmm <br>
</p>
<p>may be I'm wrong but I used r.regression.series to assess a
relationship between mystrds values and time (days)<br>
</p>
<p>As a consequence the offset and slope maps I obtain are b and a
in the following linear equation</p>
<p>y=ax+b</p>
<p>i.e.<br>
</p>
<p>predicted_mystrds=slope*days+offset</p>
<p>This is why I suppose that for detrending I need to do:<br>
</p>
<p>mystrds-(predicted_mystrds)</p>
<p>i.e.<br>
</p>
<p></p>
<p>mystrds-(slope*days+offset)</p>
<p><br>
</p>
<p>I'm I wrong?</p>
<p>thank you</p>
<p>Ivan<br>
</p>
<p><br>
</p>
<p><br>
</p>
<blockquote type="cite">
<div dir="ltr">
<div><br>
</div>
<div>Best,</div>
<div>Vero</div>
</div>
<br>
<div class="gmail_quote">
<div dir="ltr" class="gmail_attr">El jue, 28 dic 2023 a las
8:14, Ivan Marchesini (<<a href="mailto:ivan.marchesini@gmail.com" target="_blank">ivan.marchesini@gmail.com</a>>)
escribió:<br>
</div>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">
<div>
<p>Dear Veronica</p>
<p>I think I found a simple solution using temporal raster
modules. Here is an example:</p>
<p>#evaluating info of the strds<br>
eval `<a href="http://t.info" target="_blank">t.info</a> mystrds -g`</p>
<p>#getting the starting day (of the year, 0-365) of my
strds<br>
startday=$(date -d "$start_time" "+%j")<br>
</p>
<p>#Creating a new strds where each pixel has the value of
the count of the days starting from the start_day of my
strds (the start day in my dataset is in 2016)<br>
t.rast.mapcalc inputs=mystrds
expression="(start_year()-2016)*365-${startday}
+start_doy()" output=days basename=days nprocs=xxx --o<br>
</p>
<p>#fitting the trend equation<br>
r.regression.series xseries="`t.rast.list in=days
columns=name sep=, format=line`" yseries="` t.rast.list
in=mystrds columns=name sep=, format=line`"
out=regression_offset,regression_slope,regression_rsq,regression_t
meth=offset,slope,rsq,t<br>
</p>
<p>#detrending<br>
t.rast.mapcalc input=mystrds,days
expression="mystrds_detrend
= mystrds-(regression_offset+regression_slope*days)"
output=mystrds_detrend basename=mystrds_detrend nprocs=xxx
method=start --o<br>
</p>
<p><br>
</p>
<p>Best</p>
<p>Ivan<br>
</p>
<p><br>
</p>
<p><br>
</p>
<p><br>
</p>
<div>On 23/12/23 14:53, Ivan Marchesini wrote:<br>
</div>
<blockquote type="cite">
<p>Hi Veronica</p>
<p>Thank you. It goes in the direction of my idea evn if
my problem is exactly trying to take into account the
correct gaps between that data <br>
</p>
<p>I have another idea.</p>
<p>if it works I will come back here to explain how I did</p>
<p>thank you again</p>
<p>Ivan<br>
</p>
<p><br>
</p>
<div>On 22/12/23 13:45, Veronica Andreo wrote:<br>
</div>
<blockquote type="cite">
<div dir="ltr">Hello Ivan,
<div><br>
</div>
<div>AFAIU you could use the slope and offset maps
from t.rast.series within t.rast.algebra to detrend
the values of the maps within the strds, something
like "detrended_strds = trend_strds -
(trend_strds*map(slope) + map(offset))". Others
suggest, to detrend by subtracting the previous
value, i.e. that would imply using the temporal
algebra with the temporal index, something like
"detrended_strds = trend_strds[1] -
trend_strds[0]". </div>
<div><br>
</div>
<div>I haven't tested any of these, just a couple of
ideas ;-) However, I do not know how this might
interact with seasonality within data, or irregular
gaps. </div>
<div><br>
</div>
<div>hth somehow</div>
<div>Vero</div>
</div>
<br>
<div class="gmail_quote">
<div dir="ltr" class="gmail_attr">El vie, 22 dic 2023
a las 5:10, Ivan Marchesini via grass-user (<<a href="mailto:grass-user@lists.osgeo.org" target="_blank">grass-user@lists.osgeo.org</a>>)
escribió:<br>
</div>
<blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">Dear
colleagues<br>
<br>
I would like to the advantage of the t.* modules for
detrending a strd.<br>
<br>
In the strd I have earth observation data
irregularly sampled (2 or 3 <br>
times per month), in the period November-February,
for 7 years. They are <br>
not equally spaced (i.e gaps have different
duration)<br>
<br>
A simple t.rast.series analysis (opion=slope,offset)
highlights that <br>
probably there is a descending trend when
considering the maps ordered <br>
by id.<br>
<br>
I would like to fit a proper time depending fitting
curve for each pixel <br>
and then subtract the function from the real data.<br>
<br>
any hints on how I can do this task exploiting the
GRASS GIS modules or <br>
some simple bash/python scripting?<br>
<br>
thank you<br>
<br>
Ivan<br>
<br>
<br>
<br>
<br>
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</blockquote>
</div>
</blockquote>
</blockquote>
</div>
</blockquote>
</div>
</blockquote>
</div>
</blockquote></div>