To explore problems with the fast estimation method of moisture content (MC) in reconstructed soil under human disturbance, this paper used a fly ash-filled reconstructed soil region as the research object and obtained experimental data by Fieldspec4 high spectrometry and the laboratory drying method. The response characteristics of MC were analyzed from the original spectral data that underwent mathematical transformation and the spectral index data, and a corresponding inversion model was established. Combined with the successive projections algorithm (SPA), the model was optimized with a better fitting effect, and the optimal inversion model was obtained. The results showed that the composition of soil and fly ash were different, resulting in obvious differences in the shape of the spectral curve, but both had large moisture absorption peaks near 1420 nm and 1920 nm. After mathematical transformation, the correlation between the spectral reflectance and MC was enhanced, in which the absolute value of the maximum correlation between the soil moisture content (SMC) was 0.839, and the absolute value of the maximum correlation between the fly ash moisture content (FMC) was 0.801. Among them, the first-order differential of multivariate scattering correction (MSC′) and the first-order differential of logarithm ((lgR)′) had higher fitting accuracy for FMC and SMC, respectively. The scale and sensitivity of significance variables were greatly improved based on the spectral index of two-band operation. Better FMC and SMC models were constructed based on the difference soil index (DSI) under mathematical transformation, and R² were 0.73 and 0.87, respectively. After SPA optimization, the predictive ability of the model was further improved, in which the predictive accuracy R² of FMC and SMC reached up to 0.87 and 0.96, respectively, and the RPD was greater than 3. This shows that the DSI model based on MSC′ and (lgR)′ combined with the SPA method can be used as an effective means of predicting the MC in fly ash-filled reconstructed soil. These research results provide the theoretical basis and technical support for the application of soil near-earth sensing technology and rapid estimation of the MC of reconstructed soil under human disturbance.

为了探讨人为干扰条件下重建土壤含水量的快速估算方法存在的问题，以粉煤灰填充的重建土壤区域为研究对象，并通过Fieldspec4高光谱法和实验室干燥方法获得了实验数据。从经过数学变换的原始光谱数据和光谱指数数据分析了MC的响应特性，并建立了相应的反演模型。结合逐次投影算法（SPA），对模型进行了优化，拟合效果更好，获得了最优的反演模型。结果表明，土壤和粉煤灰的成分不同，导致光谱曲线的形状存在明显差异，但两者在1420 nm和1920 nm附近都有较大的吸湿峰。经过数学变换后，光谱反射率与MC之间的相关性得到了增强，其中土壤含水量（SMC）之间最大相关的绝对值为0.839，而粉煤灰含水量之间最大相关的绝对值为（ FMC）为0.801。其中，多元散射校正（MSC'）的一阶微分和对数（（lgR）'）分别对FMC和SMC具有更高的拟合精度。基于两波段操作的频谱指数，显着性变量的规模和敏感性得到了极大的提高。在数学转换的基础上，基于土壤差异指数（DSI），构建了较好的FMC模型和SMC模型，R ²分别为0.73和0.87。经过SPA优化后，该模型的预测能力进一步提高，FMC和SMC的预测精度R ²分别达到0.87和0.96，RPD大于3。 MSC'和（lg R）'与SPA方法相结合可以作为预测粉煤灰填充重建土壤中MC的有效手段。这些研究结果为土壤近地传感技术的应用和人为干扰下重建土壤MC的快速估算提供了理论依据和技术支持。