Change detection within unequally spaced and non-stationary time series is crucial in various applications, such as environmental monitoring and satellite navigation. The jumps upon spectrum and trend (JUST) is developed to detect potential jumps within the trend component of time series segments. JUST can simultaneously estimate the trend and seasonal components of any equally or unequally spaced time series by considering the observational uncertainties or measurement errors. JUST and its modules can also be applied to monitor vegetation time series in near-real-time. Herein, the details of the open-source software package for JUST, developed in both MATLAB and Python, are presented.

JUST: MATLAB and python software for change detection and time series analysis / Ghaderpour, E.. - In: GPS SOLUTIONS. - ISSN 1080-5370. - 25:3(2021), pp. 1-7. [10.1007/s10291-021-01118-x]

JUST: MATLAB and python software for change detection and time series analysis

Ghaderpour E.
Primo
2021

Abstract

Change detection within unequally spaced and non-stationary time series is crucial in various applications, such as environmental monitoring and satellite navigation. The jumps upon spectrum and trend (JUST) is developed to detect potential jumps within the trend component of time series segments. JUST can simultaneously estimate the trend and seasonal components of any equally or unequally spaced time series by considering the observational uncertainties or measurement errors. JUST and its modules can also be applied to monitor vegetation time series in near-real-time. Herein, the details of the open-source software package for JUST, developed in both MATLAB and Python, are presented.
2021
MATLAB; Open-source software; Python; Spectral-trend analysis; Time series
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JUST: MATLAB and python software for change detection and time series analysis / Ghaderpour, E.. - In: GPS SOLUTIONS. - ISSN 1080-5370. - 25:3(2021), pp. 1-7. [10.1007/s10291-021-01118-x]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1655290
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