This session will cover techniques for processing remote sensing timeseries data for analysis along with their implementation in Google Earth Engine. You will learn how to properly prepare your remote sensing timeseries for regression and trend analysis. You will also learn about joins and advanced filters in EE.

The session will cover two broad topics
1. TimeSeries Gap Filling: Many applications require replacing missing pixels in an image with an interpolated value from its temporal neighbours. We will complete examples that show how to replace cloudy pixels and interpolate missing timesteps.
2. TimeSeries Smoothing: Smoothing filters are applied to a time series for removal of the noise. We will cover example implementation of movingwindow smoothing and savitzky–golay filtering.

Speakers:
Ujaval Gandhi, Spatial Thoughts

You can also view this video and slides on the Geo for Good Summit website at https://earthoutreachonair.withgoogle...