Vaglie et al. (2026) HUMERIS Global Soil Dataset

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-09-15
• Authors: Matteo Dalle Vaglie, Saverio Francini, Gherardo Chirici, Federico Martellozzo
• DOI: 10.17632/z8v8m579z4.3

Research Groups

• Universita degli Studi di Firenze Toscana, Firenze
• Contributing authors: Matteo Dalle Vaglie, Saverio Francini, Gherardo Chirici, and Federico Martellozzo

Short Summary

This paper presents the HUMERIS Global Soil Properties Dataset, a comprehensive 39-year time series (1985–2023) of annual global soil maps at a 1 km resolution for four key soil properties: pH, soil salinity (ECe), nitrogen (N), and organic carbon (OC). The dataset uses advanced machine learning techniques to capture the spatio-temporal dynamics of soil properties.

Objective

• Develop a large-scale framework for estimating soil carbon, nitrogen, pH, and salinity dynamics from 1985 to 2023

Study Configuration

• Spatial Scale: Global scale with 1 km resolution
• Temporal Scale: 39-year time series (1985–2023)

Methodology and Data

• Models used: Advanced machine learning techniques using 41 environmental predictors, including climatic variables, topographic indices, land cover data, and remotely sensed vegetation indices
• Data sources: ISRIC-WISE, OpenLandMap, LUCAS datasets, and in-situ measurements

Main Results

• The dataset provides a comprehensive understanding of the spatio-temporal dynamics of soil properties at a global scale
• Annual variations in soil properties can be examined using single-year maps available via Google Earth Engine interface

Contributions

• Original value lies in the development of a large-scale framework for estimating soil carbon, nitrogen, pH, and salinity dynamics, which can serve as benchmarks for environmental monitoring and sustainable land management

Funding

• This research was supported by [no specific funding projects or programs mentioned]

Citation

@article{Vaglie2026HUMERIS,
  author = {Vaglie, Matteo Dalle and Francini, Saverio and Chirici, Gherardo and Martellozzo, Federico},
  title = {HUMERIS Global Soil Dataset},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/z8v8m579z4.3},
  url = {https://doi.org/10.17632/z8v8m579z4.3}
}