## 4 Discussion
### Uncertainties of HSI Image Inversion  
It should be noted, however, the data used in the PLSR models were narrowband in-lab spectra measured with air dried and sieved soils. While the relationships between soil spectra and salinity/alkalinity were better identified without in-situ noises from soil roughness, vegetation and moisture, etc., uncertainties were introduced when applying the models to satellite images. It was less a concern in this study because the images were acquired in a flat plain and the pixel size (100 m) is much larger than the variations of soil texture and roughness in this relatively homogeneous agricultural region. The white salt crusts (mainly carbonate) are only observed in early, dry spring before growing season starts. Moreover, crusts are rare sporadic small patches on top of soil surface. Its little impact on that of large pixel with mixed different alkaline and saline soils. In most studies of soil salinity utilizing field spectra (e.g., [15; 59; 60]), field spectra at multiple soil samples are often averaged to reduce the noises from field heterogeneity. [PERSON] [59] also found that the image spectra generally match to that of field spectra within about \(\pm\)5% absolute reflectance at most wavelengths, including VIS-NIR bands. In this sense, our soil reflectance in the laboratory also reduces the field-related noise and therefore, could be applied to the 100-m HSI image in our study area. As for vegetation, it indeed can modify the spectral reflectance of salt-affected soils [61; 62] and cause spectral confusion in quantifying levels of alkaline and saline soils [63]. In our study, the PLSR models included the red band both sensitive to soil pH, EC and vegetation. Careful selection of image acquisition dates could optimally reduce these vegetation effects. In late April and early May in our study area, crops are not planted and grass is just beginning to sprout. In this period, vegetation is less a concern and a threshold of NDVI < 0.3 effectively masks it out. For moisture in soils, it decreases soil spectral reflectance and, therefore, underestimates the soil salinity and alkalinity. In our study area, however, precipitation in early spring is very low [4; 9], and the topsoil moisture is homogeneously low across the plain. Its effects to spectra of air-dried soil in lab were neglected in this study. The bidirectional effect of soil albedo could also affect the PLSR model development. It was not considered in this study because the HSI imagery is acquired at nadir and fixed local time. Our in-lab spectral measurement simply mimics the sun-Earth-sensor geometry of the HSI image acquisition. In future research, intensive field experiments will be conducted to further examine the above-mentioned effects to soil spectra, as well as to satellite images. Finally, in most studies of image inversion, simultaneous in-field measurements are often required to maximally match field spectra with satellite images [64; 65]. It dramatically limits the usage of historical satellite data and the application in a large area, which actually are important assets of satellite remote sensing. The spectra used in this study were acquired in ideal lab conditions and eliminated the abovementioned noises. Although it introduced uncertainties in the PLSR model, by not requiring simultaneous field measurement, it allows us to examine soil properties in a large study area, or even across the basin when more ground samples and satellite imagery are added in. Compared with the PLSR models constructed from the spectral data, the accuracies of estimating soil alkalinity and salinity were slightly lower when applied to HSI images. Thus, the PLSR model, which had three components, was an optimum linear solution. However, the stripe noises in the first 20 bands [60] still had a minimal effect on bands 21-95 and resulted in less significant strips in the inversion maps. To a certain extent, the stripe noises will bring excessive noise from HSI images and result in deviation in estimating and abstraction in classes.