I am working on identification of breakpoints in Landsat based NDVI time series (1990-2018). I am using The Breaks for Additive Seasonal and Trend (BFAST) algorithm which is a pixel based time series decomposition method to detect and characterise abrupt changes. I wonder would it be possible to apply it for a region of interest or study area as a whole instead of applying it on selected pixels?
ndvi_stack <- stack(ndvi_list) ndvi_ROI_1 <- crop(ndvi_stack, extent(ROI_1)) ndvi_ROI_1
So, ndvi_ROI_1 is a study area or region of interest. Now I select the pixel:
selected_pixel <- 100
I created an irregular time series for the selected pixel (100 in this case) using bfastts() from BFAST package.
(s <- bfastts(as.vector(ndvi_ROI_1[selected_pixel]), dates, type = c("irregular")))
The time series is converted to a regular time series using advice from https://philippgaertner.github.io/2018/04/bfast-preparation/.
I also tried not to select to a specific pixel and run bfastts() on whole study region and it seems to work (although I am not sure about the validity of results). I used the following code:
(s <- bfastts(as.vector(ndvi_ROI_1), dates, type = c("irregular")))
I am still not sure if this is technically right to apply bfast method to a whole study region instead of pixel by pixel basis? And if it is, is the coding correct or I have to introduce any other steps?
Looking forward to the kind advice.