bfast v1.5.7


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Breaks For Additive Season and Trend (BFAST)

BFAST integrates the decomposition of time series into trend, seasonal, and remainder components with methods for detecting and characterizing abrupt changes within the trend and seasonal components. BFAST can be used to analyze different types of satellite image time series and can be applied to other disciplines dealing with seasonal or non-seasonal time series, such as hydrology, climatology, and econometrics. The algorithm can be extended to label detected changes with information on the parameters of the fitted piecewise linear models. BFAST monitoring functionality is added based on a paper that has been submitted to Remote Sensing of Environment. BFAST monitor provides functionality to detect disturbance in near real-time based on BFAST-type models. BFAST approach is flexible approach that handles missing data without interpolation. Furthermore now different models can be used to fit the time series data and detect structural changes (breaks).

Functions in bfast

Name Description
bfast Break Detection in the Seasonal and Trend Component of a Univariate Time Series
modisraster A raster brick of 16-day satellite image NDVI time series for a small subset in south eastern Somalia.
bfast01classify Change type analysis of the bfast01 function
bfast01 Checking for one major break in the time series
bfastmonitor Near Real-Time Disturbance Detection Based on BFAST-Type Models
bfastpp Time Series Preprocessing for BFAST-Type Models
dates A vector with date information (a Datum type) to be linked with each NDVI layer within the modis raster brick (modisraster data set)
som Two 16-day NDVI time series from the south of Somalia
bfastts Create a regular time series object by combining data and date information
plot.bfast Methods for objects of class "bfast".
create16dayts A helper function to create time series
ndvi A random NDVI time series
bfast-package Breaks For Additive Season and Trend (BFAST)
simts Simulated seasonal 16-day NDVI time series
harvest 16-day NDVI time series for a Pinus radiata plantation.
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Date 2014-08-27
License GPL (>= 2)
LazyLoad yes
LazyData yes
Repository CRAN
Repository/R-Forge/Project bfast
Repository/R-Forge/Revision 464
Repository/R-Forge/DateTimeStamp 2014-08-27 18:49:54
Date/Publication 2014-08-28 00:00:24
Packaged 2014-08-27 20:15:07 UTC; rforge
NeedsCompilation no

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