Inversion of soil salinity according to different salinization grades using multi-source remote sensing

Abstract

Soil salt information from unified soil salinity content (SSC) inversion models based on all samples is insufficient for accurate regional SSC monitoring. Here, a method of building SSC inversion models for different salinization grades is proposed, combined with unmanned aerial vehicle (UAV) and Sentinel-2A images. According to different salinization grades, three groups of samples (mild (M), medium-severe (S), and whole (W)) were obtained. Their SSC spectra characteristics, parameters, and quantitative inversion models were analysed, constructed, and compared, based on UAV images, and substituted into different salinization grade areas in Sentinel-2A. The UAV-based models for M and S outperformed those for W; the same trend occurred after substituted into Sentinel-2A images. The inversion results were closer to the field survey results. Models for different salinization grades achieved better regional inversion than those of the whole. UAV-based SSC models can be applied to satellite imagery to invert regional SSC.

Keywords:

• Different salinization grades
• unmanned aerial vehicle
• multi-spectra
• Sentinel-2A
• soil salinity

Acknowledgements

We thank the ESA for maintaining Sentinel-2A dataset and research groups for providing in situ measured SSC and UAV data.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research has been supported by the Natural Science Foundation of Shan-dong Province, China (grant no. ZR2019MD039), the National Natural Science Foundation of China (grant nos. 41877003 and 41671346), the Funds of Shandong “Double Tops” Program (grant no. SYL2017XTTD02).