1. Introduction
Tidal flats are intertidal shoals on the muddy coast that are considered the intersection of land and ocean, which are affected by water level changes and other various dynamic environmental factors [
1]. Tidal flats not only support the livelihoods of millions of humans worldwide and provide habitats for wild-life and resources for land reclamation but they also protect the coast from extreme meteorological or oceanic events [
2]. Moreover, tidal flats play an important role in the global carbon cycle and in climate change as an organic carbon sink [
3,
4]. Intensifying human activities [
5] and global climate change have greatly impacted tidal flats [
1,
6,
7]. Thorough research of tidal flats would be beneficial to understand the hydrological, ecological, geomorphological, and environmental impacts of intertidal zones. This is especially important, considering that the soil moisture content (SMC) of tidal flat surfaces not only affects the lives and migration of wild-life but also influences the formation, migration, and the mechanism of material exchange [
8,
9,
10]. In addition, considering the combined effect of tides and evaporation, the soil surface moisture of tidal flats is also closely related to their topography [
11,
12]. Thus, studies of the distribution and variation of soil surface moisture are important aspects of tidal flats research.
The traditional gravimetric method requires drying and weighing, and in situ measurement needs a water content measurement probe [
13,
14]. Although these methods are time-consuming and laborious, they were widely used and as calibrated data as they provide good results [
15,
16]. However, the periodic tides and muddy environment of tidal flats make it more difficult and hazardous to investigate the in situ soil moisture data [
17]. Therefore, these conventional methods are difficult to scale spatially and temporally to conduct continuous, stereoscopic, and comprehensive monitoring of tidal flats [
18,
19]. To adapt to the high dynamism of tidal flats, a noninvasive approach is required to assess changes in the surface characteristics and the SMC of tidal flats. The recent combination of remote sensing techniques and in situ surveying has given us a novel opportunity to investigate the moisture content of tidal flats faster and more conveniently [
14,
20,
21].
Remote sensing techniques using thermal infrared [
22,
23,
24] and microwave [
12,
25,
26,
27] have made significant progress in soil moisture monitoring. Although these methods are advantageous for improving the precision of SMC estimation, low spatial-temporal resolution constrains the use of microwave sensors for small regions. In addition, many studies have demonstrated that the solar domain (400 nm–2500 nm) could also be used for the study of soil moisture [
28,
29,
30,
31]. For example, Khanna et al. [
32] proposed an index that estimates the soil and vegetation moisture with near infrared (NIR, 858 nm) and shortwave infrared (SWIR, 1240 nm and 1640 nm) bands of a Moderate-resolution Imaging Spectroradiometer (MODIS). Using the Red-NIR spectral feature space, Gao et al. [
33] retrieved soil moisture by developing an empirical relationship between vegetation canopy and mixed pixels reflectance that was based on the linear decomposition algorithm. Peng et al. [
34] evaluated the effectiveness of discrete wavelet transform (DWT) for soil moisture retrieval. Bablet et al. [
35] and Sadeghi et al. [
36] developed a linear physically-based model and a multilayer radiative transfer model to estimate the surface SMC in the solar domain, respectively. These studies made great progress in describing the relationship between soil moisture and soil reflectance. However, the practice of combining spectral and directional reflectance properties of bare soil is rarely implemented. Surface anisotropy can be a diagnostic characteristic of surface properties and provide additional information for extracting SMC, which should not be dissociated in remote sensing applications [
37].
Soil is a complex combination of mineral, water, air, and organic matter [
38]. Soil reflectance is a cumulative property that derives from the inherent spectral behavior of the heterogeneous combination of its composition [
39]. The bidirectional spectral reflectance model based on the radiative transfer theory developed by Hapke [
40,
41,
42] can best describe how to characterize the orientation and heterogeneous scattering of soil particles. The Hapke model can be readily inverted against multi-angular spectral reflectance measurements and relate the radiance field emerging from a surface to physically meaningful parameters, such as the single scattering albedo (SSA), the roughness, and the scattering properties of the soil surface. The Hapke model was supplemented and improved by Hapke [
43,
44], and many scientists have extended it and applied new models to investigate the physical properties of soil. For example, Jacquemoud et al. [
37] developed the SOILSPECT model based on the Hapke model and were able to describe the directional reflectance of the soil surface from 450 nm to 2450 nm with higher accuracy. Yang et al. [
45] introduced the SMC into the soil bidirectional reflectance distribution function (BRDF) model, quantitatively converted the single scattering albedo in the SOILSPECT model and the soil reflectance of the dual-hemisphere and established an extended soil BRDF model. The Hapke model has been widely applied. For instance, Chappell et al. [
46] used the Hapke model to investigate the directional modeling of the reflectance of three soils with heavy rain and wind erosion and inverted it against the bidirectional soil spectral reflectance model. Furthermore, the Hapke model is also suitable for multi-scale assessments across large-scale areas of angular sensors on airborne and satellite platforms [
47]. However, satellite data of multi-angle sensors with low and medium spatial resolution cannot be used for small regions. Because of the large-scale difference between the in situ measurement data and the images of spaceborne sensors, much field research of tidal flats is still needed to retrieve preliminary surface properties. There are few published photometric properties of tidal flats retrieved from multi-angular data using bidirectional spectral reflectance models. Bidirectional reflectance spectra and the SOILSPECT model provide a novel approach to retrieve surface photometric characteristics and the SMC of tidal flats.
Therefore, the objective of this research is to retrieve the photometric characteristics and the SMC of tidal flats combined with the SOILSPECT model and multi-angle reflectance spectra under controlled conditions. The main objectives of this study include: (i) obtaining soil samples in tidal flats and measuring the multi-angle reflectance spectra and the corresponding SMC in the laboratory; (ii) employing the SOILSPECT model to retrieve the photometric characteristics of tidal flats; and (iii) applying the parameter of the SMC to the SOILSPECT model for analyzing and verifying the estimated SMC.
5. Discussion
In this study, all the soil samples were dried and sieved with a 0.5 mm mesh to remove larger impurities. However, after adding water to the soil samples, some “shell residues” floated on the soil surface (
Figure 11). Stoner and Baumgardner [
39] used a laboratory spectroradiometer to measure the spectral bidirectional reflectance factor from a total of 485 moist soil samples over the 520 to 2320 nm wavelength range. Five distinct soil spectral reflectance curve forms were identified. Among them, the organic-dominated form exhibited a characteristic concave shape from 500 to 1300 nm, similar to the curve shape of the soil samples collected in this article. It can also be noted from the comparison in
Figure 5 and
Figure 11, that the more “shell residues” that lay on the surface of the soil samples, the more obvious the concave shape in the range of 500 to 1300 nm. Although the foreign matter on the soil surface changed the curve shape in the visible and part of the NIR bands, the change trend of the spectrum was uniform, and there was no apparent abnormality in the retrieval of the bidirectional reflectance model. This also seems to indicate that similar situations on the soil surface of a tidal flat may not influence the retrieval results of SMC in future larger studies.
As the wet soil samples dried, the roughness parameter h increased gradually, but the h value of dry soil was smaller than that of loose soil. Changes in the soil surface during the drying process, especially in the soil crusts [
59,
60], reduce the roughness. Thus, the smaller the soil particle size, the tighter the soil particles will be bound together [
61]. The spectral information was related to changes in particle size distribution and texture at the surface of the soil. The soil samples in this research were taken from a tidal flat area, which has been affected by water level changes and various dynamic environmental factors for a long time. Thus, there was little loose dry soil. This was why we did not have loose soil samples in our experiment. Although the h value retrieved from the same soil sample with different moisture content increased with the decrease in moisture content roughly, it did not satisfy this rule completely. When the empirical model of SMC of the tidal flat was built, the state of the soil surface could not be ignored, especially since large errors may occur when the soil particles are similar in size.
Rough surfaces have more backscattering than smooth surfaces. Therefore, the empirical model of the normalized difference between backscattering and forward scattering was adopted to invert the soil surface roughness [
62,
63]. In this article, however, the results of the asymmetry factor were unexpected. Among the dry soil samples, the scattering-type of the soil surface fit the general law, that is, the soil sample 01-81 with the largest particle size exhibited backscattering, and the soil sample 01-19 with the smallest particle size exhibited forward scattering. However, the results changed when the soil sample was soaked with water. The asymmetry factor varied between negative and positive, which indicated that the scattering-type of the different SMC was not stable for one soil sample. The apparently irregular asymmetry factors for these soil samples may be due to the fact that water filled the interstices of the soil particles, which not only darkened the soil reflectance but also modified the angular pattern of the reflected radiation [
64,
65]. Simple descriptive models of the reflectance from dry soil and wet soil were illustrated by Tian and Philpot [
65] (see Figure 9 in [
65]). The incident first radiation interacts with the water film when the light source illuminates the wet soil surface (see Figure 9b in [
65]). Multiple internal reflections within the water layer at the soil surface provided a mechanism for the redistribution of light [
54,
66]. The mechanism that causes this change requires further research, especially in tidal flats where the water content changes extremely frequently.
In existing studies on the retrieval of soil surface characteristics using the bidirectional reflectance model, almost all the research has been carried out in farmland, forests, and other areas that have relatively slow-changing moisture content and relatively stable properties. There are very few published studies on the retrieved photometric properties of tidal flats. We set up a series of experiments to retrieve the SMC of the tidal flat along the coast of Jiangsu. There was a highly significant correlation between the SMC and the equivalent water thickness parameter, which indicates that this method can be adopted to obtain the soil moisture of the tidal flat. However, due to the particularity and complexity of this study area, some results (such as surface scattering and roughness parameters, etc.) did not show the regularity we expected. Nevertheless, our research is still meaningful. A significant contribution is using the soil particle size measured in the laboratory as one of the parameters for the inversion of SMC, which should be used especially cautiously in tidal flats.
6. Conclusions
In this study, we investigated the soil surface photometric properties of a tidal flat using multi-angle reflectance data. The SOILSPECT model, the relationship between double-hemisphere reflectance and single scattering albedo ω and the Beer–Lambert law were employed to calculate the SMC of the tidal flat. Field data were obtained from six bare soil sampling sites of the tidal flat, and a total of five moisture gradients were set up for each soil sample. We then obtained 30 sets of spectral data by measuring the multi-angle reflectance spectra and the corresponding soil moisture data in the laboratory. The main conclusions are as follows:
The stability of each parameter was evaluated by selecting a set of model parameter results from existing studies. The stability results followed the order: h > ω > b > b′ > c > c′, and showed that the soil surface roughness, h, is the most stable among the six parameters.
Model parameters retrieval was achieved by combining the particle swarm optimization algorithm for seven characteristic bands, which were identified by the continuum removal method. The parameters retrieval procedure was not sensitive to the initial values. Among all the parameters, the single scattering albedo ω had a strong correlation with soil moisture and showed an increasing trend as the soil moisture decreased for each soil sample. The larger the particle size in the dry soil samples was, the smaller the ω was. However, the change in ω with particle size did not demonstrate a general trend for soil samples with different water content. This phenomenon has important implications for using the soil particle size measured in the laboratory as one of the parameters for water content estimation. In this procedure, the soil surface state should be fully considered, especially in tidal flats. In the dry soil samples, the roughness parameter, h, showed an increasing trend as the particle size increased. The four parameters of the phase function, b, c, b′, and c′, had an impact on the scattering of the soil surface. Forward scattering was dominant in the soil surface with the highest moisture, while backscattering was dominant during the gradual drying process.
A regression analysis of model-estimated soil equivalent water thickness ξ and the measured SMC, demonstrated a significant positive correlation, as the determination coefficient was about 0.95 and the RMSE was 1.58.
Because of the limited soil samples, we set as many water content gradients as possible and measured the multi-angle reflectance indoors. In addition, due to the complexity of this work, the conclusions of this study require more experiments for further verification. Coupled with the SMC simulation in the laboratory, there will be deviations inevitably from the soil surface in the field. Based on the results of laboratory research, in the future, our works will be focused on (i) understanding the bidirectional reflectance characteristics of tidal flats surface, (ii) exploring how surface roughness influence on the bidirectional reflectance at satellite image scale, and (iii) finding a convenient and practical method for retrieving the soil moisture content to provide rapid and large region data support for tidal flats research.