Data underlying the publication: Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data

Datacite citation style:
Michiel Pezij; D.C.M. (Denie) Augustijn; Hendriks, D.M.D. (Dimmie); Hulscher, S.J.M.H. (Suzanne) (2019): Data underlying the publication: Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:ba33fc56-e07b-4547-9630-9b1565d18040
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

University of Twente logo

Usage statistics

1594
views
1
citations
460
downloads

Geolocation

Twente (region)
lat (N): 52.304
lon (E): 6.688
view on openstreetmap

Time coverage

2016/2018

Licence

CC0
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.

History

  • 2019-10-28 first online, published, posted

Publisher

4TU.Centre for Research Data

Format

media types: application/vnd.google-earth.kml+xml, application/zip, text/csv, text/plain, text/x-python

Funding

  • NWO-TTW, 13871

Organizations

University of Twente, Faculty of Engineering Technology, Department of Water Engineering & Management

DATA

Files (2)