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.
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- ALLSSA:
-
Anti-leakage least-squares spectral analysis
- CCDC:
-
Continuous change detection and classification
- CWT:
-
Continuous wavelet transform
- DBEST:
-
Detecting breakpoints and estimating segments in trend
- EVI:
-
Enhanced vegetation index
- EWMACD:
-
Exponentially weighted moving average change detection
- GPS:
-
Global Positioning System
- JUST:
-
Jumps upon spectrum and trend
- LSSA:
-
Least-squares spectral analysis
- LSWAVE:
-
Least-squares wavelet
- LSWA:
-
Least-squares wavelet analysis
- NDVI:
-
Normalized difference vegetation index
- OLS:
-
Ordinary least-squares
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The GPS Tool Box is a column dedicated to highlighting algorithms and source code utilized by GPS engineers and scientists. If you have an interesting program or software package you would like to share with our readers, please pass it along; e-mail it to us at gpstoolbox@ngs.noaa.gov. To comment on any of the source code discussed here, or to download source code, visit our website at http://www.ngs.noaa.gov/gps-toolbox. This column is edited by Stephen Hilla, National Geodetic Survey, NOAA, Silver Spring, Maryland, and Mike Craymer, Geodetic Survey Division, Natural Resources Canada, Ottawa, Ontario, Canada.
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Ghaderpour, E. JUST: MATLAB and python software for change detection and time series analysis. GPS Solut 25, 85 (2021). https://doi.org/10.1007/s10291-021-01118-x
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DOI: https://doi.org/10.1007/s10291-021-01118-x