| Abstrakt: |
This study aims to rapidly and accurately obtain surface soil salinity information in arid regions. To achieve this, Shajingzi irrigation district, Aksu Prefecture, Xinjiang, China was taken as the research area, ground-collected soil salinity data at depths of 0-10 cm and 10-20 cm were used along with corresponding Land-sat 9 OLI remote- sensing images to extract band reflectance values. This led to the creation of two- and three-band spectral indices, which resulted in the development of four remote- sensing salt detection indices (SDI1, SDI2, SDI3, and SDI4) under conditions of low vegetation cover. These four indices were then evaluated for their accuracy in estimating soil salinity at different depths. The results showed that: (1) The classification accuracies of the four indices were 73.56%, 66.35%, 43.75%, and 74.52%, respectively, for a soil depth of 0-10 cm and 61.06%, 62.50%, 66.35%, and 64.42%, respectively, for a soil depth of 10-20 cm. These findings suggest that the optimal inversion depth for soil layers in the irrigation district is 0-10 cm. (2) Among the four indices, SDI4, which was constructed with a three-band spectrum, outperformed the others, which are two-band spectrum-based. SDI4 effectively estimates the degree of soil salinization in the Shajingzi irrigation district, providing valuable technical references for managing and preventing soil salinization in irrigated areas. [ABSTRACT FROM AUTHOR] |
