Time series and spectral indice management for Remote Sensing Sensors
MuseoPheno aims to be a phenology toolbox for Satellite Image Time Series. The documentation is hosted on readthedocs.
What does MuseoPheno do today ?
MuseoPheno globally eases the way to smooth or compute index for time series from raster or vector.
It has a special feature to compute Sentinel2 level 2A time series by providing a command line to produce a Sentinel2 raster time series :
museopheno.computeS2SITS -S2dir /tmp/S2_2018/ -unzip True -out /mnt/SITS_2018.tif
Don't manage temporal information, MuseoPheno do it for you
Let's suppose you want to compute the NDVI, and you know how your bands are ordered in your raster. Just define your band order (it supposes your bands are stacked in the following order : band1, band2... for date 1, then band1, band2 for date 2 and so on...) then give MuseoPheno the expression "(B8-B4)/(B8+B4)", and the library will generate the NDVI for each date.
So it takes only a few lines to go from your time series to a temporal spectral index. It is also as fast to produce the indice raster.
You can see the demo here with Leaf Chlorophyll Content.
Your index is not listed ? It is very easy to add a new sensor or to add new index. Just follow the simple documentation.
Temporal resampling and smoothing
How do I install it ?
A package is available on pip :
python3 -m pip install museopheno --user
Alternatively, you can install museopheno directly from the git :
python3 -m pip install git+https://github.com/nkarasiak/MuseoPheno.git --user
Feel free to remove the
--user if you like to install the library for every user on the machine.
What is planning to do MuseoPheno ?
- More temporal signal smoothing (double logistic, Whittaker...)
- Computation and mapping of phenology metrics (start of season, end of season)
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