ee.Algorithms.TemporalSegmentation.Ewmacd

Exponentially Weighted Moving Average Change Detection. This algorithm computes a harmonic model for the 'training' portion of the input data and subtracts that from the original results. The residuals are then subjected to Shewhart X-bar charts and an exponentially weighted moving average. Disturbed pixels are indicated when the charts signal a deviation from the given control limits.

 The output is a 5 band image containining the bands:

    ewma: a 1D array of the EWMA score for each input image. Negative values represent disturbance and positive values represent recovery.

    harmonicCoefficients: A 1-D array of the computed harmonic coefficient pairs. The coefficients are ordered as [constant, sin0, cos0, sin1, cos1...]

    rmse: the RMSE from the harmonic regression.

    rSquared: r-squared value from the harmonic regression.

    residuals: 1D array of residuals from the harmonic regression.

See: Brooks, E.B., Wynne, R.H., Thomas, V.A., Blinn, C.E. and Coulston, J.W., 2014. On-the-fly massively multitemporal change detection using statistical quality control charts and Landsat data. IEEE Transactions on Geoscience and Remote Sensing, 52(6), pp.3316-3332.

UsageReturns
ee.Algorithms.TemporalSegmentation.Ewmacd(timeSeries, vegetationThreshold, trainingStartYear, trainingEndYear, harmonicCount, xBarLimit1, xBarLimit2, lambda, lambdasigs, rounding, persistence)Image
ArgumentTypeDetails
timeSeriesImageCollection

Collection from which to extract EWMA. This collection is expected to contain 1 image for each year and be sorted temporally.

vegetationThresholdFloat

Threshold for vegetation. Values below this are considered non-vegetation.

trainingStartYearInteger

Start year of training period, inclusive.

trainingEndYearInteger

End year of training period, exclusive.

harmonicCountInteger, default: 2

Number of harmonic function pairs (sine and cosine) used.

xBarLimit1Float, default: 1.5

Threshold for initial training xBar limit.

xBarLimit2Integer, default: 20

Threshold for running xBar limit.

lambdaFloat, default: 0.3

The 'lambda' tuning parameter weighting new years vs the running average.

lambdasigsFloat, default: 3

EWMA control bounds, in units of standard deviations.

roundingBoolean, default: true

Should rounding be performed for EWMA

persistenceInteger, default: 3

Minimum number of observations needed to consider a change.

Examples

JavaScript

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Python

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