Improved soil salinity estimation in arid regions: Leveraging bare soil periods and environmental factors.

In the context of global land degradation and increasing salinization of cultivated land, accurately and sustainably estimating soil salinization is essential for effective land management. This study explores a novel approach to improve soil salt content (SSC) monitoring by minimizing the influence of long-term environmental variability and incorporating relevant environmental factors. Focusing on exposed cultivated land in arid regions, we analyzed the sensitivity of multispectral indices and environmental factors to SSC during pre-seeding and post-harvest bare soil periods. Our findings indicate that soil mechanical composition and salinity indices exhibited strong correlations with SSC, which further enhanced when the periods were analyzed separately. Dividing the bare soil periods improved the model performance, increasing R by 10.2%-55.7%, and the support vector regression model performed better, with an R of 0.77, RMSE of 0.11%. This approach offers a robust framework for precision agriculture and sustainable land management in salinity-affected regions.