Hi Veronica
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
I have another idea.
if it works I will come back here to explain how I did
thank you again
Ivan
On 22/12/23 13:45, Veronica Andreo wrote:
Hello Ivan,
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]".
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.
hth somehow
Vero
El vie, 22 dic 2023 a las 5:10, Ivan Marchesini via grass-user
(<[email protected]>) escribió:
Dear colleagues
I would like to the advantage of the t.* modules for detrending a
strd.
In the strd I have earth observation data irregularly sampled (2 or 3
times per month), in the period November-February, for 7 years.
They are
not equally spaced (i.e gaps have different duration)
A simple t.rast.series analysis (opion=slope,offset) highlights that
probably there is a descending trend when considering the maps
ordered
by id.
I would like to fit a proper time depending fitting curve for each
pixel
and then subtract the function from the real data.
any hints on how I can do this task exploiting the GRASS GIS
modules or
some simple bash/python scripting?
thank you
Ivan
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