In this article, an on-line microwave moisture sensing system (OM2S2) based on a multifrequency swept technique was developed to monitor the moisture content (MC) of corn in the fresh to dry state ...(MC ranged from 10.89 to 63.64%) in real time. Attenuation and phase shift data were collected under a frequency swept signal containing 801 frequencies from 2.00 to 10.00 GHz with a 10 MHz interval. To remove the inefficient frequencies, the optimized frequencies were selected by a two-stage frequency selection framework: 1) 17 frequency subsets were generated using the random forest-recursive feature elimination algorithm, and then 2) the optimal frequency set (including eight individual frequencies) was determined using voting strategies according to the results of tenfold cross-validation. The attenuation and phase shift data corresponding to the optimal frequency set were utilized as the input variables of six regression algorithms for MC prediction. A deep neural network (coefficient of determination(<inline-formula><tex-math notation="LaTeX">R^2</tex-math></inline-formula>) = 0.997, root mean square error (RMSE) = 1.087, mean absolute error (MAE) = 0.868) performed best according to the Friedman test and Nemenyi post hoc test and thus, was employed for the OM2S2. These results showed that the OM2S2 could measure the MC of corn changing from the fresh state to the dry state in real time, and it showed potential for utilization in the on-line determination of high MC in food processing and agriculture-related industries.
Moisture measurement has long been a challenge for agricultural products with high moisture content (MC). In this article, a novel microwave sensing system embedded with multifrequency-swept ...technique was built with off-the-shelf components and applied to moisture measurement of sweet corn MC is approximately 80% wet basis (w.b.). In order to collect sufficient moisture information, a frequency-swept signal (contains 41 frequencies from 2.60 to 3.00 GHz) was taken as the original measurement signal. A total of 20 redundant frequencies were removed from the original measurement signal according to the frequency selection for further measurements. Four different algorithms, including deep neural network (DNN), random forest (RF), adaptive boosting (AdaBoost), and extreme gradient boosting (XGBoost), were employed to establish moisture prediction models. The proposed six-layer DNN showed the best performance (<inline-formula> <tex-math notation="LaTeX">R^{2}=0.980 </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">RMSE =2.023\% </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">MAE =1.556\% </tex-math></inline-formula>) in predicting the MC of sweet corn (ranging from 15.45% to 81.19% w.b.). The results showed that the developed microwave sensing system was capable of measuring the MC of sweet corn and could potentially be applied to moisture determination of other agricultural products with high MC in food processing industry.
In preparation for the NISAR mission soil moisture algorithm, this study performs the validation of the European Center for Medium-Range Weather Forecast (ECMWF) ERA5-Land volumetric soil water (soil ...moisture) layer product with in situ measurements from the Soil Moisture Active Passive (SMAP) core validation sites (CVS) for 2015-2021. The ERA5-Land soil water layer was also compared against the SMAP-enhanced radiometer soil moisture product (gridded at 9 km) to a global extent. For comparison between the ERA5-Land and the SMAP soil moisture products, a matching temporal dataset was generated from ERA5-Land based on the acquisition time of SMAP for each 9 km grid. In comparison with the CVS in situ measurement, the ERA5-Land data exhibits an overall ubRMSE of about <inline-formula> <tex-math notation="LaTeX">\sim 0.05~\text{m}^{3}/\text{m}^{3} </tex-math></inline-formula> but has high wet bias over most of the sites except for sites in Australia, Denmark, and Argentina. The global comparison of the ERA5-Land soil moisture with the SMAP 9 km gridded product shows an overall wet bias with a high correlation in the tropical and temperate regions. The lowest bias was observed over the desert region but has poor correlation as it does not have enough soil moisture variability. Poor correlation with high bias and high RMSD observed over dense vegetated and tundra regions is possibly due to the inferior performance of the SMAP soil moisture product, which has not been validated for these areas.
The objective of this study is to propose a mapping of surface soil moisture ( SSM ) using airborne measurements based on the GLObal Navigation Satellite System Reflectometry Instrument (GLORI), a ...polarimetric instrument. GNSS-R measurements were acquired at the agricultural Urgell site in Spain in July 2021. In situ measurements describing the soil moisture and roughness and the vegetation cover leaf area index were then obtained simultaneously with flight measurements. An analysis of observable copolarization (right-right) reflectivity <inline-formula><tex-math notation="LaTeX">{{\rm{\Gamma }}}_{RR}</tex-math></inline-formula> and the cross-polarization (right-left) reflectivity <inline-formula><tex-math notation="LaTeX">\ {\Gamma }_{RL}</tex-math></inline-formula> behaviors as a function of incidence angle is proposed, as is normalization of the reflectivity function of the incidence angle. The sensitivity of reflectivities is then proposed as a function of surface soil moisture. An empirical model with two variables, soil moisture and the normalized difference vegetation index ( NDVI ), based on the principle of the tau-omega model is then considered for the inversion of GNSS-R reflectivity <inline-formula><tex-math notation="LaTeX">{\Gamma }_{RL}\ </tex-math></inline-formula> and estimation of soil moisture. This model is calibrated and validated by a threefold cross-validation approach. A mapping of SSM at 100 m resolution is created with data from the studied site and three acquired flights.
Frequency Domain Spectroscopy (FDS) is a powerful tool to study the dielectric properties of oil-paper insulation, which is widely used under high electric field strength. The motion of charge ...carriers under high electric field strength will cause new dielectric characteristics in FDS curves, from which more information could be extracted for insulation state assessment. In this paper, FD spectra are measured under high electric field strength. The electric field dependence of the loss peak in middle frequency and the characteristics of dielectric loss in low frequency are studied. With the influence of trapping on the motion of charge carriers under electric field being considered, charge carriers hopping polarization model and charge carriers motion dependent conductance model are proposed. The trap energy level of oil-paper insulation decreases when the moisture content increases, thus, the motion characteristics of charge carriers change, leading to decreasing loss peak in middle frequency and inverse dielectric loss characteristics in low frequency. These two models introduce the influence of traps on carrier motion into the dielectric response and enable one to gain a better understanding of the dielectric properties of oil-paper insulation under high electric field strength.
Estimating soil moisture (SM) using microwave Doppler radar is gaining attention to save fresh water and enhance crop growth and yield in agriculture due to its noncontact form of measurement. Most ...of the work in the literature focused on utilizing frequency-modulated continuous wave (FMCW) and ultrawideband (UWB) radar for their capability of measuring SM at different depths. However, none of the work in the literature focused on utilizing simpler architecture continuous wave (CW) radar. In this article, to estimate SM types, namely, dry, moist, and wet, a 24-GHz CW radar leveraged with time-frequency mapping is proposed. We utilized the time-frequency mapped scalogram images to train deep-learning models named DarkNet53, MobileNetV2, and ResNet101. Repetitive measurements were conducted for 108 h, capturing data from dry, moist, and wet soil samples, segmented using a 15-s window, resulting in a total of 25 920 images in the controlled environment experiment. In the outdoor environment, 12 h of data containing dry and wet samples were collected and similarly segmented, producing a total of 2880 images. Experimental results demonstrated that "DarkNet53" outperformed the other networks, achieving an accuracy of 91.3%. Additionally, with the addition of water content to the soil surface, a linear increasing trend of the phase of the radar-reflected echoes with the increase of water content was observed for short-scale study. To the best of our knowledge, this is the first reported investigation on utilizing CW radar for estimating SM, which has several potential applications, including smart irrigation systems, plant health monitoring, home plantation monitoring, and precision agriculture.
The newest soil moisture-dedicated satellite, the Soil Moisture Active Passive (SMAP) mission, provides global maps of soil moisture using concurrent L-band radar and radiometer acquisitions. To ...support the ongoing validation activities of SMAP soil moisture products, in this paper, we examined the retrieval accuracy of four SMAP soil moisture products by using well-calibrated and dense in situ measurements from the Little Washita Watershed network, one of the SMAP core validation sites with intensive ground sampling. The four SMAP products include the active (3 km), passive (36 km), active-passive (9 km), and the enhanced passive product which is a newly released soil moisture data set with a grid resolution of 9 km. Efforts on identifying the possible error sources of these products were also made for the purpose of improving the SMAP soil moisture algorithms. The results show that the passive and active-passive products can well capture the temporal dynamic of ground soil moisture with overall unbiased root-mean-square error (ubRMSE) values of 0.032 and <inline-formula> <tex-math notation="LaTeX">0.041~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>, respectively, which generally meet their mission requirement of <inline-formula> <tex-math notation="LaTeX">0.04~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>. In contrast, some irregular fluctuations exist in the active product, leading to an overall wet bias, which makes its accuracy a little poorer than its expected retrieval accuracy of <inline-formula> <tex-math notation="LaTeX">0.06~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>. The new enhanced passive product shows the lowest ubRMSE value of <inline-formula> <tex-math notation="LaTeX">0.026 ~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula> though it underestimates in situ measurements with a bias of <inline-formula> <tex-math notation="LaTeX">0.059 ~\text {m}^{3}\cdot ~\text {m}^{-3} </tex-math></inline-formula>, revealing its great potential to substitute the active-passive product to provide global soil moisture measurements at a medium resolution of 9 km. The underestimation of SMAP surface temperature data may be one of the reasons that contribute to the dry bias of SMAP passive, active-passive, and enhanced passive products. The microwave polarization difference index and HV-polarized backscatter show good response to in situ soil moisture and may be considered in SMAP algorithms to further improve the accuracy of soil moisture retrievals. We expect that our findings can be fed back to improve the SMAP soil moisture algorithms and thus promote the application of SMAP soil moisture products in terrestrial water, energy, and carbon cycles.
Gas-solid flows with nonuniform phase distribution and varying moisture often exist in the industrial process. Its solid concentration measurement is an important and challenging research field, and ...new effective measurement methods are needed. In this study, a novel method using the microwave resonant cavity sensor is proposed to measure solid concentration of gas-solid two-phase flow with varying moisture. The sensor is developed from a cylindrical resonant cavity with open ends, and the orthogonal experiment is carried out using simulation method to determine the resonant mode and optimize the sensor configuration. Afterward, experiments are conducted to evaluate the performance of the designed sensor and the proposed method. The sensor has a high and nearly constant sensitivity to the solid concentration and its output is almost not affected by the nonuniform phase distribution. The varying moisture brings effect to solid concentration measurement when the proposed sensor is used. To solve this problem, the new parameter named normalized resonant frequency is defined to reduce this influence, and finally, the solid concentration measurement is achieved.
When we speak about capacitance moisture meters for bulk materials we have to face with different values of dielectric permittivity for different bulk materials in dehydrated state, what causes a ...method error that can be named ‘type uncertainty’. Besides, different varieties of the same material have different values of dielectric permittivity, which depend from geographical origin, processing conditions etc. It can be hardly predicted automatically and type uncertainty can be compensated only in separate situations with the help of preliminary calibration. Main tasks of the research are to develop new comparison principle of moisture measurement with better accuracy due to effective compensation of physical, chemical and granulometric composition influence on the result of moisture measurement, develop new primary and secondary instrument transducers. Moisture sensor consists of four measuring capacitors. Two of them should be filled with a sample, which moisture content should be determined, and other pair of measuring capacitors should be filled with a same substance, but previously dehydrated. Mathematical models, developed to take into account granulometric composition of a bulk material were used to carry out a comparison analysis for three types of instrument measuring transducers. Obtained results proved that suggested principle of moisture measurement provides effective compensation of granulometric composition influence. Developed measuring principle had been experimentally tested what helped to confirm that it provides two times better compensation of different physical and chemical composition for different materials in comparison with the direct comparison method.
•Moisture measurement of bulk materials is a task of current importance for agriculture.•Moisture meter’s calibration is a problem because reference moist substances are usually absent.•Suggested method of moisture measurement provides effective “type uncertainty” compensation.•Suggested method provides effective compensation of granulometric composition influence.•Experimental researches confirmed that suggested moisture measurement method is effective.
A methodology to generate calibrated maps of soil moisture from C-band synthetic aperture radar (SAR) images processed by SAR interferometry (InSAR) technique is presented. The proposed methodology ...uses atmospheric phase delay (APD) maps obtained from a time series of Sentinel-1 interferograms, to disentangle the APD and soil moisture contributions to Sentinel-1 interferograms. We show how the high spatial resolution and short temporal baseline of Sentinel-1 image can help to estimate soil moisture using a daisy chain InSAR processing. The estimated soil moisture maps are compared with in situ data collected by five soil moisture sensors installed in an experimental field, characterized by bare soil, located close to Lisbon, Portugal. Results show that after removing the APD effects in SAR interferogram, there is a correction of the bias in the soil moisture estimation and an improvement in the correlation coefficient with the soil moisture measurements, from 0.38 to 0.78. Soil moisture changes were measured during a sequence of rain events in the winter season. A root-mean-square (rms) error less than 0.04 m 3 /m 3 was found over a variety of meteorological conditions.
