基于差异化光谱指数的盐渍土水分含量预测——以滨海盐土为例

以滨海盐土为研究对象，通过添加不同浓度的盐溶液并模拟蒸发过程，获取不同含水、含盐量的土壤样品，并测定土壤光谱和土壤含水量，分别运用光谱指数法和偏最小二乘回归法(PLSR)对土壤含水量进行预测。结果表明：由2027 nm和1878 nm构建的土壤水分差异化光谱指数(NDMI2027,1878)是预测土壤水分的最优指数，且适用于任何等级的盐渍化土壤，其建模集和验证集的预测结果均优于PLSR方法，验证集R2达0.99，RMSE仅为21.84 g/kg，可比较准确地预测盐渍化土壤的含水量。

Prediction of Saline Soil Moisture Content Based on Differential Spectral Index: A Case Study Of Coastal Saline Soil

Soil samples with various soil salt and moisture contents were artificially obtained by adding different amount of NaCl solutions to costal saline soil to simulate the evaporation process. During the evaporation process, soil moisture contents and soil spectra were regularly collected, then were analyzed using spectral indices and partial least squares regression(PLSR), to quantify the soil moisture content. The results showed that the differential moisture index derived from the reflectance value of 2027 nm and 1878 nm was the best index to predict soil moisture content, and the result obtained from NDMI2027, 1878 in both calibration and validation process were slightly better than PLSR, with the determined coefficient (R2) of the prediction as high as 0.981, and the root mean square error (RMSE) only 0.022 g/g, and were not affected by the salinity grades. It could be concluded that soil moisture content can be accurately predicted by NDMI2027, 1787.