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Breakpoint detection of Landsat pixel time series via BFAST-based algorithms, provided as a Shiny app
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README.md

BFAST Explorer v0.0.3

Description

BFAST Explorer is a Shiny app, developed using R and Python, designed for the analysis of Landsat Surface Reflectance time series pixel data.

Three change detection algorithms - bfastmonitor, bfast01 and bfast - are used in order to investigate temporal changes in trend and seasonal components, via breakpoint detection.

If you encounter any bugs, please create an issue.

Usage

Currently, this tool only supports UNIX-like systems (no Windows OS) due to the integration between R and Python.

In order to successfully run this tool, apart from having R and Python installed, you need the following:

Citation

To cite BFAST Explorer in publications, please use

Alexandre Almeida, Nathalia Menini, Jan Verbesselt, Ricardo Torres (2018). BFAST Explorer: An Effective Tool for Time Series Analysis. In: 2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 22-27 July 2018. Valencia, Spain. DOI: 10.1109/IGARSS.2018.8517877.

or, alternatively, the corresponding BibTeX entry

@inproceedings{,
   author = {Alexandre Almeida and Nathalia Menini and Jan Verbesselt and Ricardo Torres},
   title = {BFAST Explorer: An Effective Tool for Time Series Analysis},
   booktitle = {2018 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)},
   location = {Valencia, Spain},
   eventdate = {2018-07-22/2018-07-27},
   doi = {10.1109/IGARSS.2018.8517877}
}
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