Schlagwort: random forest

Remote Sensing Applications
fkroeber

S-1 based crop analyses

Processing pipelines for the calculation of backscatter intensity, polarimetric decomposition parameters and coherence values are presented. Analyses regarding the informative value of these SAR features are exemplified by analysing timeseries for a few hundred fields. Correlations to the phenological development of the crops are made and random forest-based classifications are performed.

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others
fkroeber

Internship – UAV-based regression of biomass

Comparison of three different machine/deep learning approaches to perform regression for fractional vegetation coverage, vegetation height and vegetation volume. Tackling the issue of sparse training data vs. high model complexity

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Machine Learning
fkroeber

Hurricane track forecasts

6h forecasts of the next positions of hurricanes in the Atlantic Ocean. Taking into account the motion history of the hurricanes recorded up to that point as well as their current properties, feature sets are created that are then used to train and evaluate various machine learning models.

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Spatial Analyses
fkroeber

Solar radiation analyses

Performing a multitemporal classification of Sentinel imagery to extract vineyards. Subsequently, analysing the significance of irradiation intensity and duration for the location of vineyards. Using random forest as an embedded feature selection method.

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