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Quality of data was carefully controlled by plotting data time series and inspection for possible outliers.
shall preferably be based on data time series of an adequate time span.
To facilitate this, the satellite data time series is separated into individual orbits prior to averaging.
Three absolute homogeneity tests were used to detect any variation in the data time series.
The BPNN is trained with the pressure data time series measured from adjacent pressure taps.
Finally, specific weather data time series may be chosen, which are integrated as WeatherStation object into the output data set.
In general the SDM requires more data (time series of NFIs) but is considered less uncertain [5].
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Data analysis is geared towards modelling sources of signal variation, i.e. reducing noise in the data time-series, and the cerebrovascular response to task-related changes in neuronal activity.
It produces an output sum combination of convergent series of selected relative polynomial derivative terms, which can substitute for an ordinary differential equation solution to describe and forecast real data time-series.
With the launch of high frequent remote sensing satellites and availability of data, time-series data derived from multi-temporal remote sensing images are receiving significant attention concerning the dynamics of regional vegetation growth, phenological crop identification, land use change detection, etc. [1 4].
Spatial analyses relied on Landsat data (time-series analyses) and recent SPOT-5 images.
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