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Found 5 publication(s)

  1. 1

Turini, N.; Thies, B.; Horna, N. & Bendix, J. (2021): Random forest-based rainfall retrieval for Ecuador using GOES-16 and IMERG-V06 data. European Journal of Remote Sensing 54(1), 117-139.
Contreras, P.; Orellana-Alvear, J.; Muñoz, P.; Bendix, J. & Celleri, R. (2021): Influence of Random Forest Hyperparameterization on Short-Term Runoff Forecasting in an Andean Mountain Catchment. Atmosphere 12(2), 1-16.
Orellana-Alvear, J.; Celleri, R.; Rollenbeck, R. & Bendix, J. (2019): Optimization of X-Band Radar Rainfall Retrieval in the Southern Andes of Ecuador Using a Random Forest Model. Remote Sensing 11(14), 1632.
Guio Blanco, C.M.; Brito Gómez, V.M.; Crespo, P. & Ließ, M. (2018): Spatial prediction of soil water retention in a Páramo landscape: Methodological insight into machine learning using random forest. Geoderma 316, 100-114.
Vorpahl, P.; Elsenbeer, H.; Märker, M. & Schröder, B. (2012): How can statistical models help to determine driving factors of landslides?. Ecological Modelling 239, 27-39.
  1. 1


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