Qian (2026) Dataset for developing and validating surface soil moisture estimation and spatiotemporal transfer models in agricultural regions

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-09-14
• Authors: Jiaxin Qian
• DOI: 10.17632/dvrcjn882h.1

Research Groups

• Department of Earth Sciences, University of Manitoba
• Department of Geography, University of Manitoba

Short Summary

This study provides a dataset for developing and validating surface soil moisture estimation models in agricultural regions, with a focus on Manitoba, Canada.

Objective

• Investigate the feasibility of using remote sensing data to estimate surface soil moisture in agricultural areas.

Study Configuration

• Spatial Scale: Provincial scale (Manitoba, Canada)
• Temporal Scale: Annual cycle (April to September)

Methodology and Data

• Models used: ISBA (Interactions between Soil, Biosphere, and Atmosphere) model
• Data sources: Satellite data from Sentinel-1 and Sentinel-2 missions

Main Results

• The dataset contains 10 years of surface soil moisture estimates at a spatial resolution of 100 m.
• The results show that the ISBA model can accurately estimate surface soil moisture in agricultural regions, with a mean absolute error (MAE) of 0.02 m³/m³.

Contributions

• This study provides a valuable dataset for developing and validating surface soil moisture estimation models in agricultural regions.
• The results contribute to the understanding of the spatial and temporal variability of surface soil moisture in Manitoba, Canada.

Funding

• This research was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC) through the Discovery Grants program.

Citation

@article{Qian2026Dataset,
  author = {Qian, Jiaxin},
  title = {Dataset for developing and validating surface soil moisture estimation and spatiotemporal transfer models in agricultural regions},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/dvrcjn882h.1},
  url = {https://doi.org/10.17632/dvrcjn882h.1}
}