TY - DATA
T1 - Data underlying the publication: Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data
PY - 2019/10/28
AU - Michiel Pezij
AU - D.C.M. (Denie) Augustijn
AU - D.M.D. (Dimmie) Hendriks
AU - S.J.M.H. (Suzanne) Hulscher
UR - https://data.4tu.nl/articles/dataset/Data_underlying_the_publication_Applying_transfer_function-noise_modelling_to_characterize_soil_moisture_dynamics_a_data-driven_approach_using_remote_sensing_data/12713879/1
DO - 10.4121/uuid:ba33fc56-e07b-4547-9630-9b1565d18040
KW - Data-driven modelling
KW - Hydrology
KW - Remote sensing
KW - Soil moisture
KW - Transfer function-noise modelling
KW - Unsaturated zone
KW - Water management
N2 - This dataset includes the input data, Python scripts, and Pastas model output for the scientific manuscript "Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data". The manuscript is currently under review. The data covers the years 2016, 2017, and 2018. We refer to the readme file included in the dataset for further details.
ER -