Heterogeneous Data Pre-Processing for Stream Mining

JSI will be supported by RS experts (GEOVILLE and MAGELLIUM) and agriculture experts (AIS, L&F) to deliver deep data understanding, required for the development of coherent time-features. One of the main PerceptiveSentinel focuses will be to use biophysical indices as main input to develop TIME features. We intend to use different (streaming) aggregates, such as moving or exponential moving average, minimum, maximum, histogram, correlation, variance, sum and others. Streaming aggregates can be applied for different time-windows. Spatial, radiometric and time-series features of EO data will be supplemented by domain specific “agriculture” features to form a feature set – a list of attributes to enter the evaluation through data mining modelling. Streamline modelling and experimenting will be performed by the employment of standard JSI tools to evaluate learning feature set. Feature extractors will be developed by JSI. Their functionality is to receive Stage-1, Stage-2 and non-EO data from PerceptiveSentinel platform and to automatically extract features to be used in learning and operational phases of streaming processing.