M (2026) Field and laboratory data for assessing soil salinity and crop stress using Sentinel-2

Identification

• Journal: Mendeley Data
• Year: 2026
• Date: 2026-01-14
• Authors: Bharthisha S M
• DOI: 10.17632/963h6nmnyj

Research Groups

• University of Agricultural Sciences Dharwad

Short Summary

This study utilized Sentinel-2 imagery and ground truth data to assess soil salinity and crop stress in the Ghataprabha command area, India. It found strong linear relationships between spectral bands and soil electrical conductivity, demonstrating Sentinel-2's high efficacy for operational salinity monitoring in semi-arid agroecosystems.

Objective

• To delineate soil salinity classes and assess their spectral signatures using Sentinel-2 multispectral imagery.
• To evaluate the efficacy of Sentinel-2 for assessing soil salinity and crop stress in tropical semi-arid agroecosystems.

Study Configuration

• Spatial Scale: Ghataprabha command area, Karnataka, India; 120 soil samples collected from 0-0.3 m depth.
• Temporal Scale: March 2024.

Methodology and Data

• Models used: Google Earth Engine (for image processing), multiple regression model.
• Data sources: Sentinel-2 multispectral imagery, ground truth data from 120 soil samples (electrical conductivity, ECe).

Main Results

• Strong linear relationships were observed between individual spectral bands (Blue, Green, Red, NIR, SWIR1) and soil electrical conductivity (ECe), with correlation coefficients (r) ranging from 0.98 to 0.99 (p < 0.01).
• A multiple regression model incorporating all spectral bands achieved a coefficient of determination (R²) of 1 for predicting ECe.
• Vegetation indices like EVI showed moderate negative correlations with ECe (r = -0.26, p < 0.01).
• Salinity-specific indices exhibited weaker associations with ECe.
• The approach achieved high accuracy in mapping salinity extents.

Contributions

• Demonstrated the high efficacy of Sentinel-2 multispectral imagery for operational monitoring of soil salinity and crop stress in tropical semi-arid agroecosystems.
• Provided a validated methodology for delineating salinity classes and assessing their spectral signatures using readily available satellite data.

Funding

• Not explicitly mentioned in the provided text.

Citation

@article{M2026Field,
  author = {M, Bharthisha S},
  title = {Field and laboratory data for assessing soil salinity and crop stress using Sentinel-2},
  journal = {Mendeley Data},
  year = {2026},
  doi = {10.17632/963h6nmnyj},
  url = {https://doi.org/10.17632/963h6nmnyj}
}