Shaojie Zhao

A Nested Ecohydrological Wireless Sensor Network for Capturing the Surface Heterogeneity in the Midstream Areas of the Heihe River Basin, China

This letter introduces the ecohydrological wireless sensor network (EHWSN), which we have installed in the middle reach of the Heihe River Basin. The EHWSN has two primary objectives: the first objective is to capture the multiscale spatial variations and temporal dynamics of soil moisture, soil temperature, and land surface temperature in the heterogeneous farmland; and the second objective is to provide a remote-sensing ground-truth estimate with an approximate kilometer pixel scale using spatial upscaling. This ground truth can be used for validation and evaluation of remote-sensing products. The EHWSN integrates distributed observation nodes to achieve an automated, intelligent, and remote-controllable network that provides superior integrated, standardized, and automated observation capabilities for hydrological and ecological processes research at the basin scale.

Estimate of Phase Transition Water Content in Freeze–Thaw Process Using Microwave Radiometer

Ground surface freeze-thaw cycles caused by changes in solar radiation have a great impact on soil-air water heat exchanges due to the phase transition of pore water. This influence should not be ignored in the land surface process and global environment change studies because of its large extent and the rapid changes in daily and seasonal frozen ground. The key index for evaluating the influence intensity is the content of water-ice phase transition in soil pores at the ground surface. In this paper, a data set was generated by observing field experiments and physical model simulations based on the configuration of the Advanced Microwave Scanning Radiometer-EOS (AMSR-E). The results showed that microwave radiation from freezing/thawing soil has an obvious correlation to the phase transition process of soil water. A large change in soil surface emissivity was shown after the freezing of soil. The magnitude of the difference in emissivity change is strongly related to the amount of water-ice phase transition. It can be shown that the higher the phase transition water content (PTWC), the greater the emissivity difference, and the higher the frequency, the smaller the emissivity difference. Based on an analysis of a large amount of random simulation data, an interesting characteristic was found, in that the emissivity difference in vertical polarization at each frequency is nearly proportional to the phase transition water content. Thus, a ratio index called Quasi-emissivity (Qe) was developed to eliminate temperature effects during retrieval. Using these clear rules, a physical statistical algorithm was put forth to estimate the phase transition water content. Finally, the inferred results by ground-based radiometer observation were compared with the ground truth. A satisfying agreement was achieved with a root mean square error of 0.0265 (v/v). This indicated that the microwave radiometer has a great potential in the measurement of PTWC.

Comparison of the classification accuracy of three soil freeze–thaw discrimination algorithms in China using SSMIS and AMSR-E passive microwave imagery

This study compared the classification accuracies of three soil freeze–thaw discrimination algorithms in China using Special Sensor Microwave Imager/Sounder (SSMIS) and Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E) passive microwave imagery from 2008. The algorithms used were the dual-index algorithm (DIA), the decision tree algorithm (DTA), and the discriminant function algorithm (DFA). The comparison was conducted based on 0 cm land-surface temperature data from 756 meteorological stations across China by constructing error meta-matrices, and it is divided into two parts. The first part compared the overall classification accuracies from two aspects: temporal variation and spatial distribution. In the second part, the classification accuracies of frozen and thawed soils were evaluated. Results showed that both SSMIS and AMSR-E data can be applied to the DIA, DTA, and DFA algorithms, although they were originally developed from different satellite data sets. However, each of the three algorithms has its own advantages and disadvantages. Possible improvements in the three algorithms for future work are also discussed.

The complicate observations and multi-parameter land information constructions on allied telemetry experiment (COMPLICATE)

The Complicate Observations and Multi-Parameter Land Information Constructions on Allied Telemetry Experiment (COMPLICATE) comprises a network of remote sensing experiments designed to enhance the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Two types of experimental campaigns were established under the framework of COMPLICATE. The first was designed for continuous and elaborate experiments. The experimental strategy helps enhance our understanding of the radiative and scattering mechanisms of soil and vegetation and modeling of remotely sensed information for complex land surfaces. To validate the methodologies and models for dynamic analyses of remote sensing for complex land surfaces, the second campaign consisted of simultaneous satellite-borne, airborne, and ground-based experiments. During field campaigns, several continuous and intensive observations were obtained. Measurements were undertaken to answer key scientific issues, as follows: 1) Determine the characteristics of spatial heterogeneity and the radiative and scattering mechanisms of remote sensing on complex land surfaces. 2) Determine the mechanisms of spatial and temporal scale extensions for remote sensing on complex land surfaces. 3) Determine synergist inversion mechanisms for soil and vegetation parameters using multi-mode remote sensing on complex land surfaces. Here, we introduce the background, the objectives, the experimental designs, the observations and measurements, and the overall advances of COMPLICATE. As a result of the implementation of COMLICATE and for the next several years, we expect to contribute to quantitative remote sensing science and Earth observation techniques.

An empirical model to estimate the microwave penetration depth of frozen soil

The technique of microwave remote sensing has been used to monitor the soil frozen/thawed status for many years. The dielectric constant of frozen soil is relatively lower than that of unfrozen soil, so that microwave could penetrate deeper into frozen soil. However, we are still lack of the knowledge of the Microwave Penetration Depth (MPD) of frozen soil. In this study, a noncoherent microwave radiation was used to find the factors that influence the MPD of frozen soil and then validated by experiments. The results showed that the frequency of microwave, the temperature of frozen soil and the soil texture are the main factors that determine the MPD of frozen soil. An empirical model that estimates the MPD of frozen soil was proposed based on the simulation data.

Modeling of the Permittivity of Holly Leaves in Frozen Environments

The dielectric property of vegetation has a considerable effect on the characteristics of the microwave radiation of vegetation. In frozen environments, when the temperature is colder than normal, changes such as increased soluble sugar and decreased moisture content (MC) can occur in the vegetation. The dielectric property of vegetation, which is almost entirely controlled by its free and bound water content, will also change. To characterize the dielectric behavior of vegetation in frozen regions, a sensitive experiment was conducted on holly leaves with a high-performance coaxial probe over a frequency range from 0.5 to 40 GHz and a temperature range from 0°C to -20°C. Based on the measurements and the physical properties of the constituent substances of vegetation, a semiempirical dielectric model for holly leaves in low temperature environments was developed. In this model, a decrease in MC, which causes a reduction in the complex permittivity, was described as an increase in the ice content. The complex permittivity of bound water was measured using a saturated sucrose solution at -6.5°C. The research will provide a reference for the dielectric property study of the vegetation in frozen environments.

The influence of organic matter on soil dielectric constant at microwave frequencies (0.5–40 GHZ)

In this study, the dielectric constants of 12 types of soil with different organic matter content were measured using the coaxial probe method by network analyzer (0.5-40 GHz) at room temperature (approx. 23°C). The observed dielectric constant increases only slowly with soil volumetric water content up to a transition point. Beyond the transition point, it increases rapidly with volumetric water content. It was found that the value of the transition point was higher and the observed dielectric constant was lower at the same soil volumetric water content and frequency for soil with higher organic matter content. A simple semi-empirical model was proposed to describe the dielectric behavior of soil with organic matter. This model was developed based on the refractive mixing dielectric model (RMDM).

Microwave emission of soil freezing and thawing observed by a truck-mounted microwave radiometer

This article presents a study of the interference effect of the microwave emission of soil during freezing and thawing processes. The microwave brightness temperature (T B) was measured at the C (6.925 GHz), X (10.65 GHz), K (18.7 GHz) and Ka (36.5 GHz) bands using a truck-mounted dual-polarized microwave radiometer. Obvious T B oscillation behaviour was shown in the results, which were compared with both coherent and non-coherent emission models. The characteristics of the measured and modelled results were similar, except for the oscillation frequency and amplitude. This was attributed to the error in estimation of the dielectric constant of frozen soil and some other factors. This effect was important in analysing the experimental data.

Evaluation and analysis of AMSR-2, SMOS, and SMAP soil moisture products in the Genhe area of China

High-precision soil moisture products play an important role in estimating forest carbon storage and carbon emissions in Genhe, China. In this paper, we evaluated the Soil Moisture and Ocean Salinity (SMOS) L3 product, the Soil Moisture Active Passive (SMAP) L3 product, and four soil moisture products derived from the Advanced Microwave Scanning Radiometer (AMSR2), i.e., the Dual Channel Algorithm based on the Qp Model (QDCA) product, the Japan Aerospace Exploration Agency (JAXA) L3 product, and the Land Parameter Retrieval Model (LPRM) C band and X band products in the Genhe area of China. The results indicated that the root mean square error (RMSE) and bias of the QDCA product were lower than those of the other AMSR-2 products, although the QDCA still fell outside of the acceptable range with a volumetric error of no greater than 6%. The JAXA product underestimated the soil moisture and had a constant bias of 0.089-0.099 m3 m-3. The LPRM C-band and X-band products had a constant variable season bias of 0.261-0.576 m3 m-3. The quality of the SMOS was better than that of the AMSR-2 products; however, the results were noisy and unstable. The SMAP was closest to the ground measurements and presented a low RMSE (0.039-0.063 m3 m-3) and bias (0.022-0.050 m3 m-3). Finally, an assessment was performed on the parameters in these soil moisture algorithms.

Dielectric Properties of Saline Soils and an Improved Dielectric Model in C-Band

To retrieve the soil salinity by microwave remote sensing, we must clarify the relation of dielectric properties of saline soils with soil salinity. The objective of this paper was to determine how dielectric properties are affected by soil salinity in the remote sensing range and develop an improved model applying for the saline soil. Laboratory measurements of dielectric constant are made with a microwave vector network analyzer using soil mixture samples of various soil moistures and salinities prepared artificially from natural soils. The results confirmed that the real part is strongly affected by soil moisture, whereas the imaginary part depends on both the soil moisture and salinity, particularly at lower frequencies (1-6 GHz). Thus, as a key factor, soil salinity is introduced into the expression of the imaginary part of dielectric constant in the Dobson semiempirical dielectric mixing model, combining the dielectric model for saline water and the impact of electrical conductivity of soil solution. The improved model yields results, which are in good agreement with the laboratory measurements, the slopes of fitting curves between measurements and simulation nearly being equal to 1, and coefficient R2 are higher than 0.89. In addition, the improve model is independent of soil-texture parameters. However, it should be noted that the improved model can be applied only to the C-band remote sensing.