[GRASS-user] curve sketching

[Martin Wegmann]

Hello,

On Wednesday 06 June 2007 20:31:56 Jose Gomez-Dans wrote:
> Hi Martin,
>
> On 6/5/07, Martin Wegmann <wegmann at biozentrum.uni-wuerzburg.de> wrote:
> > - point of global maximum (already in r.series -> max_raster)
> > - point of global minimum (already in r.series -> min_raster)
> > - turning point  (Wendepunkt)
> > - point of max./min. slope (e.g. growing season, senescence)
> > - information about unimodal/bimodal etc. phenology (no idea how to add
> > this)
>
> I work with similar time series data (it looks as if you're interested
> in monitoring phenology, probably based on some veg. index or some
> other satellite derived biophysical variable). The problem with these
> series (and I guess with many other data of this kind) is that the
> data is very noisy (changes in solar illumination, sensor geometry,
> atmospheric effects...). If you filter out the noise, you could do
> away with temporal resolution. Over homogenous regions, you can filter
> spatially, thus reducing your spatial resolution. Either way,
> resolution degradation. You can also fit curves to your time series
> (double logistic functions and so on), and use the fit parameters to
> infer onset of senescence, budburst dates, etc.

yes, indeed, masking the noise/bad pixels and interpolating it, has to be done 
beforehand - we use an "in-house" development TiSEG, which analysis MODIS 
time-series Quality, masks and interpolates them (plus harmonic analysis if 
you want) - but after this procedure I would like to extract informations 
about the phenology.

BTW MODIS time-series processing (Quality assessment, interpolation) would be 
very handy to have inside GRASS. I think using the "new" r.mapcalc 
modificaiton for the quality analysis of MODIS is feasible but having a tool 
which offers solely the quality levels for masking pixels out would be 
easier. 

> What I am trying to get at is that this very application and data
> source dependent. It would be very hard to code something which is
> generally useful. What I do is to export the time series into Python,
> and process them further there. The results so far are very good for
> crop phenology monitoring using MODIS data. The scipy python module
> has a lot of very useful functionality to do any of the stuff I
> mentioned above.

yes, there are many measures to use and none can be applied generally - you 
wrote an analysis in Python for phenology analysis? Which analysis did you 
use? And is this code freely available? Would it be possible to add it to 
GRASS functionality?

regards, Martin