Spatial Assessment of Soil Properties and Soil Quality Dynamics (SFI and SQI) on Hainan Island Using Field Observations and Remote Sensing Data

Soil salinity and nutrient availability are major constraints affecting crop productivity, soil quality, and agroecosystem sustainability, particularly in coastal regions vulnerable to seawater intrusion. This study provides a comprehensive spatial and temporal assessment of soil properties and quality dynamics on Hainan Island by integrating field observations and multi-temporal remote sensing (RS) datasets. In 2024, a total of 152 sampling sites were surveyed, with three topsoil soil samples collected at each location. Multi-year RS data (2024–2021), including soil salinity reflectance indices (SRSI and SI), the Normalized Difference Vegetation Index (NDVI), and land use and land cover (LULC), were analyzed to evaluate temporal and spatial variability. The soil fertility index was calculated using alkali-hydrolyzed nitrogen (AN), available phosphorus (AP), available potassium (AK), soil pH, and soil organic matter (SOM). The soil quality index was calculated using the same parameters with the addition of chromium (Cr) to account for potential heavy metal contamination. Furthermore, in this study the Inverse Distance Weighting (IDW) method was used for spatial distribution maps of soil properties and other indices. The results indicated that soils were predominantly acidic (pH < 6.0) with generally low electrical conductivity (0.01–0.53 mS cm−1) across inland areas, whereas higher salinity levels (2.28–5.31 mS cm−1) were observed in southern and eastern coastal zones, suggesting potential seawater intrusion. Nutrient concentrations ranged from 60.1 to 150 mg kg−1 (AN), 4 to 332 mg kg−1 (AP), and 50.1 to 100 mg kg−1 (AK). NDVI values (0.70–0.94) indicated high vegetation density over most agricultural landscapes. Significant positive correlations were observed between soil EC and the SRSI (r = 0.781) and SI (r = 0.663; p < 0.01), demonstrating the reliability of RS-derived indices for salinity assessment. The integrated indicator-based framework developed in this study provides a scientific basis for precision agriculture, soil health monitoring, and sustainable land management in coastal agroecosystems.