Deep covariate-learning: optimising information extraction from terrain texture for geostatistical modelling applications

22 May 2020Charlie Kirkwood

Where data is available, it is desirable in geostatistical modelling to make use of additional covariates, for example terrain data, in order to improve prediction accuracy in the modelling task. While elevation itself may be important, additional explanatory power for any given problem can be sought (but not necessarily found) by filtering digital elevation models to extract higher-order derivatives such as slope angles, curvatures, and roughness... (read more)

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