A novel remote sensing monitoring index of salinization based on three-dimensional feature space model and its application in the Yellow River Delta of China

Previous studies were mostly conducted based on two-dimensional feature space to monitor salinization, while studies on dense long-term salinization monitoring based on three-dimensional feature space have not been reported. Based on Landsat TM/ETM+/OLI images and three-dimensional feature space method, this study introduced six typical salinization surface parameters, including NDVI, salinity index, MSAVI, surface albedo, iron oxide index, wetness index to construct eight different feature space monitoring index. The optimal soil salinization monitoring index model was proposed base on field observed data and then the evolution process of salinization in Yellow River Delta (YRD) were analyzed and revealed during 1984-2022. The salinization monitoring index model of MSAVI-Albedo-I-Fe2O3 feature space had the highest accuracy with R-2 = 0.93 and RMSE = 0.678g/kg. The spatial distribution of salinization in YRD showed an increasing trend from inland southwest to coastal northeast and the salinization intensity showed an increasing trend during 1984-2022 due to the implements of agricultural measures such as planting salt-tolerant crops, microbial remediation and fertility improvement. The rate of salinization deterioration in the northeast part was greater than others. Zones of salinization improvement were mainly located in cultivated land of the southwest parts.

Automated summary

This study analyzed the evolution of soil salinization in the Yellow River Delta from 1984 to 2022 using a three-dimensional feature space method. The results showed that the salinization intensity in the delta increased from the inland southwest to the coastal northeast. The implementation of salinization control measures has exacerbated salinization, particularly in the northeast. However, some cultivated land in the southwest has shown improvement in salinization.