Hydro-meteorological aspects of soil fluorides in semi-arid soils using microwave remote sensing.

Soil fluoride is a critical determinant of soil fertility, human health and crop productivity. Soil fluoride can be increased by climatic conditions, irrigation water and anthropogenic activity, and it is important to control fluoride by understanding the complex relationships between atmospheric conditions and water systems. In this research, a detailed focus is on the hydrological and meteorological aspects of soil fluorides in semi-saturated and saturated soils to discuss the impact of irrigation, capillary rise and the combination of rainfall and anthropogenic activities such as fertilizer application on the soils in the dry spell and monsoon seasons of 2021 and 2022. A Sentinel-1 data can be used to estimate fluoride levels to the above soil conditions. In an effort to estimate fluoride levels in different hydro-meteorological scenarios, we have put forward a hypothesis that focuses on understanding the potential connections between hydro-meteorological factors (precipitation, groundwater levels, and temperature) and the levels of fluoride. The findings indicate that the extensive use of groundwater for irrigation leads to a rise in fluoride levels, posing a significant threat to crop health over time. Furthermore, the combined effects of irrigation and upheaval leaching on fluoride levels have shown strong statistical conformity (R2 > 0.85) with the relevant field-measured fluoride data for the year 2022. Importantly, areas affected by F upheaval are more sensitive to the sand and clay percentage in the soil because potential and dispersion behaviour enlarge the capillaries to decelerate the upward movement. A region-based discussion details the factors contributing to the increase of fluoride in soil helpful in taking remedial measures and mitigation plans.

Radar vegetation indices for monitoring surface vegetation: Developments, challenges, and trends.

Monitoring surface vegetation is essential for environmental protection, disaster prevention, and carbon sequestration in forests. However, optical remote-sensing methods and their derivative technologies typically fail to fully meet this requirement due to constraints such as lighting and weather. Radar vegetation indices (RVIs), developed based on microwave remote-sensing data, describe the dielectric properties and morphological structure of vegetation and have been applied for vegetation monitoring at various scales. This technical review is the first to systematically summarize RVIs; it analyzes and discusses their principles, developments, categories and applications, and provides a comprehensive guide for their use. Additionally, the challenges faced by RVIs, as well as their applicability, were analyzed, and future improvements and development trends were carefully projected. The selection of RVIs must consider the type of data used, the terrain and location of the study area, and the major vegetation types. The effectiveness of RVIs applied to vegetation monitoring can be affected by various factors, including index performance, sensor type, study area, and data type and quality. These factors reduce the reliability and robustness of results, as well as guide the improvement direction of RVIs. The development of technologies, such as artificial intelligence, in remote sensing offers new possibilities for RVIs, enabling the removal of background scattering, improvement in interpretation accuracy, and reduction in application thresholds. Additionally, the development trends in high resolution, multi-polarization, multi-base, multi-dimensional, and networked synthetic aperture radar (SAR) and their satellite platforms offer data support for the next generation of RVIs. The rapid development of RVIs strongly supports the use of surface vegetation monitoring and terrestrial ecosystem research.

The Role of Molecular Structure in Monte Carlo Simulations of the Secondary Electron Yield and Backscattering Coefficient from Methacrylic Acid.

In this paper, we show the influence of the chemical structure of four different conformers on the secondary electron emission and backscattering of an electron beam from a gel of methacrylic acid. The conformers have different permanent dipole moments, which determines the cross sections for elastic collisions with electrons. The cross sections are used in Monte Carlo simulations of an electron beam, which enters the gel of methacrylic acid. The secondary electron yield and the backscattering coefficient are computed as a function of the beam energy.

Analysis of Interpolation Methods in the Validation of Backscattering Coefficient Products.

Validation is the basis of synthetic aperture radar (SAR) image quantification applications. Based on the point target of the field site, the radiation characteristics of the backscattering coefficient image can be used to optimize the SAR imaging, and the product production system can be more closely targeted, to ensure the image product accuracy in the actual quantification application. In this study, the validation of the backscattering coefficient image was examined using calibrators, and the radiometric properties of the image were evaluated by extracting the radar cross-section of each point target. Bilinear interpolation and fast Fourier transform (FFT) interpolation methods were introduced for the local area interpolation of point targets, and the two methods were compared from the perspective of response function imaging and validation accuracy. The results show that the FFT interpolation method is more favorable for validating the backscattering coefficient.

Characterizing how size distribution and concentration affect echogenicity of ultrasound contrast agents.

We investigated the effects of UCA gas bubble size distribution and concentration on the generated ultrasound echogenicity signal. Gas bubble size characterization using Coulter Counter and cryogenic-SEM revealed the hollow structure and rare presence of microbubbles >10 µm in a commercial UCA product, Lumason™. Volume-weighed size and concentration were observed to be more sensitive to changes in UCA bubble stability than number-weighted size and concentration. Size distribution measurements showed that the force (e.g., shaking/agitation energy) used to redisperse the sample did not affect the size distribution, concentration, or echogenicity of the UCA sample. The ultrasound backscattering coefficient (BSC) of size fractionated and serial diluted microbubbles showed that the echogenicity signal correlates most with UCA bubble concentration, especially volume-weighted concentration. Findings from this study may be used to support demonstrating the equivalence of a generic UCA product to the reference listed drug.

Significant decline in aerosols in the mixing layer in Beijing from 2015 to 2020: Effects of regional coordinated air pollution control.

Beijing's air quality has improved significantly since the implementation of the Air Pollution Prevention and Control Action Plan in 2013, but the local and regional contributions to this improvement have rarely been studied. Here, the vertical profile of the atmospheric backscattering coefficient (ABC) was measured by a ceilometer in Beijing from 2015 to 2020. The results show that the ABC in Beijing decreased the most at ground level from 2015 to 2020, decreasing 51.4%. Interannual variability decreased with height, and no noticeable change was found in the height range above 600 m. The most apparent declines occurred in autumn and winter, with decreases greater than 55.0%, and the minimum decrease occurred in summer, with a reduction of only 20.0%. To analyze the reasons for the autumn and winter declines, we divided the whole day into four periods according to the evolution characteristics of the atmospheric boundary layer. The significant decrease in the backscattering coefficient near the ground during the daytime confirms the effect of local emission reductions. In contrast, the considerable decreases in the backscattering coefficient measured at different heights in the midday mixing layer demonstrate the contribution of regional transport reduction. The above research results confirm the importance of regional coordinated air pollution control.

The different sensitivities of aerosol optical properties to particle concentration, humidity, and hygroscopicity between the surface level and the upper boundary layer in Guangzhou, China.

This study investigates the impact of aerosol liquid water content (ALWC) and related factors, i.e., relative humidity (RH), aerosol mass concentration (PM2.5), and aerosol hygroscopicity, on aerosol optical properties, based on field measurements made in the Pearl River Delta (PRD) region of China at the surface (1 November 2019 to 21 January 2020) and in the upper boundary layer (the 532-m Guangzhou tower from 1 February to 21 March 2020). In general, temporal variations in the ambient aerosol backscattering coefficient (ßp) and ALWC followed each other. However, the surface ßp and 532-m ßp had generally opposite diurnal variation patterns, caused by dramatic differences in PM2.5 and ambient RH between the surface and the upper boundary layer. The ambient 532-m RH was systematically higher than the surface RH, with the latter having a much pronounced diurnal cycle than the former. The surface PM2.5 concentration was systematically higher than the PM2.5 concentration at 532 m, and their diurnal cycle patterns were overall opposite. These dramatic differences reveal that the atmospheric variables, i.e., ambient RH and the PM2.5 concentration in the upper boundary layer, cannot be directly represented by the same variables at the surface. Vertical variability should be considered. Clear differences in the sensitivities of aerosol light scattering to ambient RH, PM2.5, and aerosol hygroscopicity between the two levels were found and examined. Aerosol chemical composition played a minor role in causing the differences between the two levels. In particular, ßp was more sensitive to PM2.5 at the surface level but more to the ambient RH in the upper boundary layer. The larger contribution of aerosol loading to the variability in ßp at the surface implies that local emission controls can decrease ßp and further improve atmospheric visibility effectively at the surface during winter in the PRD region.

Mapping flood by the object-based method using backscattering coefficient and interference coherence of Sentinel-1 time series.

The SAR has the ability of all-weather and all-time data acquisition, it can penetrate the cloud and is not affected by extreme weather conditions, and the acquired images have better contrast and rich texture information. This paper aims to investigate the use of an object-oriented classification approach for flood information monitoring in floodplains using backscattering coefficients and interferometric coherence of Sentinel-1 data under time series. Firstly, the backscattering characteristics and interference coherence variation characteristics of SAR time series are used to analyze whether the flood disaster information can be accurately reflected and provide the basis for selecting input classification characteristics of subsequent SAR images. Subsequently, the contribution rate index of the RF model is used to calculate the importance of each index in time series to convert the selected large number of classification features into low dimensional feature space to improve the classification accuracy and reduce the data redundancy. Finally, the SAR image features in each period after multi-scale segmentation and feature selection are jointly used as the input features of RF classification to extract and segment the water in the study area to monitor floods' spatial distribution and dynamic characteristics. The results showed that the various attributes of backscatter coefficients and interferometric coherence under time series could accurately correspond with the actual flood risk, and the combined use of backscattering coefficient and interferometric coherence for flood extraction can significantly improve the accuracy of flood information extraction. Overall, the object-based random forest method using the backscattering coefficient and interference coherence of Sentinel-1 time series for flood extraction advances our understanding of flooding's temporal and spatial dynamics, essential for the timely adoption of adaptation and mitigation strategies for loss reduction.

Ultrasound assessment of the conversion of sound energy into heat in tissue phantoms enriched with magnetic micro- and nanoparticles.

PURPOSE: Nowadays, the improvement of ultrasonic hyperthermia therapy is often achieved by adding hard particles to the sonicated medium in order to increase the heating efficiency. The explanation of the phenomenon of ultrasonic heating still requires testing on tissue mimicking materials (TMMs), enriched with particles of different sizes and physical properties. Our goal was to determine, by comparing their quantitative acoustic properties, which TMMs, with magnetic micro- or nanoparticles, convert more ultrasonic energy into heat or which of the particles embedded in the agar gel act as more effective thermal sonosensitizers. METHODS: We manufactured a pure agar gel and an agar gel with the addition of magnetic micro- or nanoparticles in two proportions of 8 and 16 mg/ml. Ultrasound quantitative techniques, the broadband reflection substitution technique and backscattered spectrum analysis were used to characterize the samples by speed of sound (SOS), frequency-dependent attenuation, and backscattering coefficients. The integrated backscattering coefficients were also calculated. The quantitative parameters, scattering, and attenuation coefficients of ultrasound in phantoms with micro- and nanoparticles were estimated. Based on the attenuation and scattering of ultrasound in the samples, the ultrasonic energy absorption, which determines the heating efficiency, was evaluated. Additionally, the temperature increase during sonication of the phantoms by an ultrasonic beam was directly measured using thermocouples. RESULTS: The density of the materials with nanoparticles was higher than for the materials with microparticles with the same fractions of particles. The SOS for all materials ranged from 1489 to 1499 m/s. The attenuation in the whole frequency range (3-8 MHz) was higher for the materials with nanoparticles than for the materials with microparticles. For the materials with the lower content (8 mg/ml) of particles, the attenuation coefficient was 0.2 dB/(MHz cm). For the 16 mg/ml concentration of nanoparticles and microparticles, the attenuation coefficients were 0.66 and 0.45 dB/(MHz cm), respectively. The value of backscattering coefficient in the whole frequency range was greater for the materials with microparticles than for the materials with nanoparticles. The values of the integrated backscattering coefficient were 0.05 and 0.08 1/m for the materials with nanoparticles and 0.46 and 0.82 1/m for the materials with microparticles and concentrations of 8 and 16 mg/ml, respectively. The rates of temperature increase in the first 3 s due to ultrasonic heating were higher for the materials with nanoparticles than for the materials with microparticles. CONCLUSIONS: Based on acoustical measurements, we confirmed that all materials can be used as tissue phantoms in the study of ultrasonic hyperthermia, as their properties were in the range of soft tissue properties. We found that the nanoparticle-doped materials had greater attenuation and smaller scattering of ultrasound than the materials with microparticles, so absorption in these materials is greater. Thus, the TMMs with nanoparticles convert more acoustic energy into heat and we conclude that magnetic nanoparticles are more effective thermal sonosensitizers than microparticles. This conclusion is confirmed by direct measurement of the temperature increase in the samples subjected to sonification.

Features of X-Band Radar Backscattering Simulation Based on the Ocean Environmental Parameters in China Offshore Seas.

The X-band marine radar has been employed as a remote sensing tool for sea state monitoring. However, there are few literatures about sea spectra considering both the wave parameters and short wind-wave spectra in China Offshore Seas, which are of theoretical and practical significance. Based on the wave parameters acquired from the European Centre for Medium-Range Weather Forecasts reanalysis data (ERA-Interim reanalysis data) during 36 months from 2015 to 2017, a finite depth sea spectrum considering both wind speeds and ocean environmental parameters is established in this study. The wave spectrum is then built into a modified two-scale model, which can be related to the ocean environmental parameters (wind speeds and wave parameters). The final results are the mean backscattering coefficients over the variety of sea states at a given wind speed. As the model predicts, the monthly maximum backscattering coefficients in different seas change slowly (within 4 dB). In addition, the differences of the backscattering coefficients in different seas are quite small during azimuthal angles of 0° to 90° and 270° to 360° with a relative error within 1.5 dB at low wind speed (5 m/s) and 2 dB at high wind speed (10 m/s). With the method in the paper, a corrected result from the experiment can be achieved based on the relative error analysis in different conditions.

The sensitivity of backscattering coefficients to elastic scattering cross-sections and electron stopping powers.

The sensitivity of Monte Carlo estimates of backscattering coefficients η to the accuracy of their input data is examined by studying the percentage change in η due to changes of 10% and 20% in the differential elastic scattering cross-section dσ/dΩ and corresponding changes in the stopping power S(E) in the primary energy range 200-10,000 eV. To a good approximation equivalent elastic and inelastic scattering changes produce equal and opposite shifts in η, a result consistent with predictions of transport theory. For medium to high atomic numbers an x% error in the specification of either S(E) or dσ/dΩ produces a percentage change in η significantly less than x%, while at low atomic number Δη/η increases approximately linearly with ln E so that Monte Carlo predictions are then more sensitive to parameter precision at high energy.

Characterizing olive grove canopies by means of ground-based hemispherical photography and spaceborne RADAR data.

One of the main strengths of active microwave remote sensing, in relation to frequency, is its capacity to penetrate vegetation canopies and reach the ground surface, so that information can be drawn about the vegetation and hydrological properties of the soil surface. All this information is gathered in the so called backscattering coefficient (σ(0)). The subject of this research have been olive groves canopies, where which types of canopy biophysical variables can be derived by a specific optical sensor and then integrated into microwave scattering models has been investigated. This has been undertaken by means of hemispherical photographs and gap fraction procedures. Then, variables such as effective and true Leaf Area Indices have been estimated. Then, in order to characterize this kind of vegetation canopy, two models based on Radiative Transfer theory have been applied and analyzed. First, a generalized two layer geometry model made up of homogeneous layers of soil and vegetation has been considered. Then, a modified version of the Xu and Steven Water Cloud Model has been assessed integrating the canopy biophysical variables derived by the suggested optical procedure. The backscattering coefficients at various polarized channels have been acquired from RADARSAT 2 (C-band), with 38.5° incidence angle at the scene center. For the soil simulation, the best results have been reached using a Dubois scattering model and the VV polarized channel (r(2) = 0.88). In turn, when effective LAI (LAI(eff)) has been taken into account, the parameters of the scattering canopy model are better estimated (r(2) = 0.89). Additionally, an inversion procedure of the vegetation microwave model with the adjusted parameters has been undertaken, where the biophysical values of the canopy retrieved by this methodology fit properly with field measured values.