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 stats
1481
views
1
citations
410
downloads
geolocation
Twente (region)
lat (N): 52.304
lon (E): 6.688
view on openstreetmap
time coverage
2016/2018
licence
cc-0.png logo 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)