Hello!,
I have been using BEAST to detect change points in Sensor data,
specifically indices such as NDVI, NDWI, NDBI, and surface temperature.
The data is seasonal from 1987-2022. Aprox 130 obs.
Contrary to what I expected,
the algorithm do not detect more than one breakpoint. For more of the indices, it detects 0 or 1 changepoints
This do not occurred with the temperature index, where at least 2 or 3 points are detected.
Does this has something to do with the input parameters?
We even convert dates to fractional dates.
- NDVI, NDWI, NDBI are normalized indices, [-1;1] does this affect the results?
- Is it possible to obtain the direction of the slope? Due to BEAST ouyput non-linear trends?
o = rb.beast(Y = our_ts, start=start_time_frac, deltat=our_delta, period=1, season=have_season,tcp_minmax=[0, 10], print_options=True, print_progress=False, quiet=False)
Thank you in advance!
Hello!,
I have been using BEAST to detect change points in Sensor data,
specifically indices such as NDVI, NDWI, NDBI, and surface temperature.
The data is seasonal from 1987-2022. Aprox 130 obs.
Contrary to what I expected,
the algorithm do not detect more than one breakpoint. For more of the indices, it detects 0 or 1 changepoints
This do not occurred with the temperature index, where at least 2 or 3 points are detected.
Does this has something to do with the input parameters?
We even convert dates to fractional dates.
- Is it possible to obtain the direction of the slope? Due to BEAST ouyput non-linear trends?
Thank you in advance!