The output is a 5 band image containing 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.
Usage | Returns |
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ee.Algorithms.TemporalSegmentation.Ewmacd(timeSeries, vegetationThreshold, trainingStartYear, trainingEndYear, harmonicCount, xBarLimit1, xBarLimit2, lambda, lambdasigs, rounding, persistence) | Image |
Argument | Type | Details |
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timeSeries | ImageCollection | Collection from which to extract EWMA. This collection is expected to contain 1 image for each year and be sorted temporally. |
vegetationThreshold | Float | Threshold for vegetation. Values below this are considered non-vegetation. |
trainingStartYear | Integer | Start year of training period, inclusive. |
trainingEndYear | Integer | End year of training period, exclusive. |
harmonicCount | Integer, default: 2 | Number of harmonic function pairs (sine and cosine) used. |
xBarLimit1 | Float, default: 1.5 | Threshold for initial training xBar limit. |
xBarLimit2 | Integer, default: 20 | Threshold for running xBar limit. |
lambda | Float, default: 0.3 | The 'lambda' tuning parameter weighting new years vs the running average. |
lambdasigs | Float, default: 3 | EWMA control bounds, in units of standard deviations. |
rounding | Boolean, default: true | Should rounding be performed for EWMA. |
persistence | Integer, default: 3 | Minimum number of observations needed to consider a change. |