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We compare five slope correction methods developed by Walter et al., Montes et al., Schleppi et al., España et al., and Gonsamo et al. (referred to as WAL, MON, SCH, ESP, and GON, respectively) using artificial fisheye pictures simulated by graphics software and a lookup table (LUT) retrieval method. The LUT is built by simulating the directional gap fraction as a function of leaf area index (LAI) and average leaf inclination angle (ALIA) using the Poisson law. LAI and ALIA estimates correspond to the case of the LUT that provides the lowest root-mean-square error between the observed gap fractions after slope correction and the simulated ones. Three LAI values (1.5, 3.5, and 5.5), four ALIA values (26.8°, 45°, 57.5°, and 63.2°), and three slope angles (0°, 20°, and 50°) constituted 36 samples of random scenes. ESP is recommended because its results are accurate and independent on the leaf angle distribution (LAD), while GON only performs well for spherical LAD. The three other methods present less good performances with underestimation or overestimation of LAI and/or ALIA depending on the LAD, and the recommended order for them is MON, SCH, and WAL. [ABSTRACT FROM PUBLISHER]

A new geometric optical model is proposed in this letter to simulate the directional brightness temperature (DBT) distribution over mixed scenes of continuous crop and road. The DBT distributions of the crop and road zones are separately calculated, and the road zone consists of a road and adjacent crop sides. A road distribution polar map is designed to show all of the roads of different lengths, widths, and orientations in the scene. The airborne multiangle data set of the thermal infrared band that was acquired during the Heihe Watershed Allied Telemetry Experimental Research experiment is used for validation. The results demonstrate that the proposed model can simulate the DBT of a heterogeneous scene (90\times 90\ \m^2) with a root-mean-square error equal to 1.1 K and good trend similarity. [ABSTRACT FROM PUBLISHER]

Based on analyzing the high-speed welding process, this paper introduced various electrical current waveform control methods such as constant current, constant voltage, big constant current and small constant current. And it also introduced their work process respectively. Through experiment the waveform method that is suitable for high speed welding, big constant current and small constant current characteristic, was acquired. By optimizing the parameters of waveform control, the welding speed is raised to 1.5 m/min, the process of welding is stable and splash small, the welding quality is good. The two constant current control in arc period is a new control thought, which is propitious to the accurate control of the arc energy. [ABSTRACT FROM AUTHOR]

The Earth surface thermal infrared (TIR) radiation shows conspicuously an anisotropic behavior just like the bi-directional reflectance of visible and near infrared spectral domains. The importance of thermal radiation directionality (TRD) is being more and more widely recognized in the applications because of the magnitude of the effects generated. The effects of TRD were originally evidenced through experiments in 1962, showing that two sensors simultaneously measuring temperature of the same scene may get significantly different values when the viewing geometry is different. Such effect limits inter-comparison of measurement datasets and land surface temperature (LST) products acquired at different view angles, while raising the question of measurement reliability when used to characterize land surface processes. These early experiments fostered the development of modeling approaches to quantify TRD with the aim of developing a correction for Earth surface TIR radiation. Initiatives for pushing the analysis of TIR data through modeling have been lasted since 1970s. They were initially aimed at mimicking the observed TIR radiance with consideration of canopy structure, component emissivities and temperatures, and Earth surface energy exchange processes. Presently, observing the Earth surface TRD effect is still a challenging task because the TIR status changes rapidly. Firstly, a brief theoretical background and the basic radiative transfer equation are presented. Then, this paper reviews the historical development and current status of observing TRD in the laboratory, in-situ, from airborne and space-borne platforms. Accordingly, the TRD model development, including radiative transfer models, geometric models, hybrid models, 3D models, and parametric models are reviewed for surfaces of water, ice and sea, snow, barren lands, vegetation and urban landscapes, respectively. Next, we introduce three potential applications, including normalizing the LST products, estimating the hemispheric upward longwave radiation using multi-angular TIR observations and separating surface component temperatures. Finally, we give hints and directions for future research work. The last section summarizes the study and stresses three main conclusions. • A review of thermal radiation directionality models in past 50 years is performed. • Current status of multi-scale multi-angle observation is reviewed. • Fourteen quantities for describing the TRD effect are summarized. • Three potential applications and five future directions are suggested. [ABSTRACT FROM AUTHOR]

• Anisotropy in emissivity in the split-window channels was analyzed. • Influence of emissivity angular variation on temperature estimation was quantified. • Incorporating the directional emissivities in the split-window algorithm improves LST accuracy. The angular variation of land surface emissivity (LSE) is rarely considered in the split-window algorithm for retrieving land surface temperature (LST), and this can cause large uncertainties in LST retrievals. To analyze the influence of angular LSE variation on LST retrievals, we built a look-up table (LUT) of directional emissivities from the MYD21A1 LST/LSE product in the Moderate Resolution Imaging Spectroradiometer (MODIS) split-window channels. The extracted directional emissivities were then input into the MODIS generalized split-window (GSW) algorithm to substitute for the classification-based emissivities. A simulation analysis was first conducted based on the LUT. Furthermore, the LST retrievals estimated from MODIS observations using the directional emissivities were compared with those estimated using the classification-based emissivities. In-situ measurements from the US SURFRAD and China's HiWATER networks were used to evaluate LST retrievals obtained using the two different emissivities. The results showed that angular LSE variations in the split-window channels for vegetated surfaces were generally minor during the daytime, but more pronounced during the night-time (approximately 0.005 between nadir and 60°). For barren surfaces, the angular LSE variation in the ˜12 μm channel was negligible but reached approximately 0.01 in the ˜11 μm channel. In the simulation, the influence of angular LSE variation was minor for view-zenith angles (VZA) <40°, but pronounced for VZA >40° reaching approximately 1.0 and 0.7 K at VZA 65° for barren and vegetated surfaces, respectively. In the evaluation, the LST estimated using the directional emissivities showed a higher accuracy than those estimated using the classification-based emissivities, especially over barren surfaces where the improvement reached >1 K. We conclude that angular LSE variation cannot be ignored in LST estimation using the GSW algorithm when VZA is >40°, especially over barren surfaces. The accuracy of the GSW algorithm is improved pronouncedly by using the directional emissivities extracted from the MYD21 product. [ABSTRACT FROM AUTHOR]

The Cu/Al dissimilar joint, welded by high-power ultrasonic welding technology, is still facing challenges despite the significant research attention it has attracted. In this work, the microstructure and mechanical properties of resistance heat-assisted high-power ultrasonic welding of Cu/Al are investigated, in order to obtain high-quality joints. The intermetallic compound (IMC) at the interface of hybrid welding is primarily composed of Al2Cu, and the additional resistance of heat reduces the thickness of this brittle IMC layer. The average shear stress for the joint prepared by hybrid welding is ~97 MPa, which is higher compared to the joint strength without resistance heat (90 MPa). Moreover, the duration of the hybrid welding process is shorter. Finally, the fracture of the hybrid weld is found to be a brittle–ductile hybrid mode. [ABSTRACT FROM AUTHOR]

The land surface emissivity (LSE) in the MYD21 product contains the effects of viewing zenith angle. The influence of the angular variation of LSE on the surface upwelling longwave radiation (SULR) estimation is still unexplored at the satellite scale. We performed statistical analyses of MYD21 emissivity retrievals over different land surface types for three longwave bands centred around 8.55 μm (Band 29), 11 μm (Band 31) and 12 μm (Band 32), respectively. A look-up table was generated to describe the angular variations for both single-band and broadband emissivities. The results showed that the angular variation of directional emissivity in Band 29 could reach up to 0.03, but was <0.01 for Bands 31 and 32. The angular variation in broadband emissivity was intermediate to that for individual bands. In all cases, the directional emissivity was greatest and symmetric around nadir. By integrating the directional broadband emissivity, the influence of angular variation of the LSE on estimated SULR was quantified using simulation and measurements at seven stations from the US surface radiation budget network (SURFRAD). The difference between the directional and integrated hemispheric broadband emissivity was within 0.01. As a result, the influence of angular variation of LSE on the SULR estimation was modest. For the SURFRAD stations, the differences of root-mean-square error (RMSE) before and after considering the angular variation of LSE were generally <1 W m−2. We conclude that the angular variation of broadband emissivity is not pronounced because of the small linear weight for Band 29 in the calculation of broadband emissivity. Ignoring the anisotropy of emissivity does not introduce large errors in SULR estimation generally. • MODIS 8.5–12 μm emissivities retrieved using a physical algorithm were analysed. • Anisotropy in emissivity was demonstrated and quantified. • Emissivity differences were found between surface types, day/night, and seasons. • Ignoring emissivity anisotropy does not affect longwave radiation estimation greatly. [ABSTRACT FROM AUTHOR]

Surface upwelling longwave radiation (SULR) is a major component of the Earth's radiation budget and directly influences the retrieval of evapotranspiration (ET) in the terrestrial ecosystems. Land surface temperature (LST) is an Essential Climate Variable (ECV) for direct estimation of SULR. However, accurate retrieval of SULR from satellite observations may be severely hindered by the anisotropic properties of land surface targets since most of them show marked angular variations in LST. This study aims at investigating the magnitude and impact factors of the directional effects of LST on SULR estimation over vegetated surfaces given that angular variation in emissivity has a limited impact on SULR estimation over most land surface types. It follows an attempt to correct for such effects in SULR estimation. We further explore the possibility to find a viewing direction at which SULR estimated from the directional LST can surrogate the hemispherical integration. To do so, a parametric model mimicking LST anisotropy with the hot spot is incorporated into the physical temperature-emissivity method. Two widely used Moderate Resolution Imaging Spectroradiometer (MODIS) LST products (i.e., MYD11_L2 and MYD21_L2) are analyzed. SULR estimates before and after correcting for LST directionality are compared with in-situ measurements acquired at 15 sites from the FLUXNET and SURFRAD networks in different regions. Our analysis reveals that LST directional effects on SULR estimation exhibit diurnal and seasonal variations, which are substantial in spring and summer for the daytime. The effects are negligible (<5 W m−2) in autumn and winter for the daytime except for in arid and semiarid regions. For the night-time, the effects are insignificant over all the biomes. Using MYD21 LST, after correction, the average root-mean-square error (RMSE) and bias of SULR estimates for all sites decrease by 8 and 8.34 W m−2 in spring, and by 8.9 and 12.13 W m−2 in summer. Using MYD11 LST, after correction, the average RMSE is between 10 and 15 W m−2 and the average bias is close to zero in all seasons. The RMSE and absolute bias of SULR estimates for sites with low to moderate vegetation (LAI <3) is lowered substantially (7–14 W m−2) after correction. Interestingly, SULR estimates from LST viewed at 54° backward and hemispherically integrated are close, with differences <3 W m−2 at most of the sites. These findings support a strategy for SULR estimation in ET retrieval over vegetated surfaces from directional LST. • LST directional effects on SULR are substantial in spring and summer for daytime. • SULR accuracy after considering LST directionality is markedly improved. • The improvement is the greatest for sites with low to moderate vegetation. • SULR from LST viewed at 54° backward and hemispherically integrated are close. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is an essential climate variable (ECV) which can be estimated from appropriate measurements of the surface thermal infrared (TIR) radiance. LST varies on a very short time scale and closely depends on the illumination and scan angles considered. To fully exploit LST products, a method for reconstructing the temporal profile and the angular dependence at the same time is proposed here. A combined visible-thermal envelope method (VT-KDTC) is built using kernel-driven (KD) and diurnal temperature cycle (DTC) models, referring to the surface structure and thermal factors, respectively. To demonstrate the reliability of the approach, TIR data from the geostationary satellite Himawari 8 are combined with visible and near-infrared (VNIR) data from the polar orbit satellite Sentinel-3A/3B. In addition to satellite observations, a synthetic dataset from the Soil Canopy Observation, Photochemistry and Energy Fluxes (SCOPE) model is also generated. Considering an anisotropy model in addition to the DTC model leads to a method displaying a better ability to simulate LSTs with a root mean squared error (RMSE) of 0.48 K against the original satellite results, compared to only the DTC model up to 1.44 K. By utilizing the field measurements as a reference, the reconstructed results are improved with a total bias of 0.72K and an RMSE of 2.58 K. Compared to the original results without correction, approximately 41% and 10% decreases are obtained in bias and RMSE, respectively. Our proposed method can also achieve LST downscaling supported by the higher spatial resolution of VNIR data when the temperature difference is assumed to be homogeneous within the coarse pixels. Thus, a simple achievable solution can be used for temperature reconstruction to enhance the quality of the LST product. • Reconstruct the angular and temporal change of LST. • Apply the VNIR and TIR observations together. • Combine kernel driven and diurnal temperature cycle models. • The spatial resolution of LST can be further improved. [ABSTRACT FROM AUTHOR]

Surface downward longwave radiation (SDLR) is a key component of the Earth's energy budget. To use new-generation geostationary satellite data with high spatial and spectral resolution for SDLR estimation, we developed a clear-sky SDLR algorithm based on multi-channel brightness temperature (BT) and precipitable water vapor (PWV), named as MBTW, for strictly clear conditions, and a clear-sky SDLR algorithm based on atmospheric parameters (named as NewAtmos) for probably clear conditions. Then , we developed a framework to estimate all-sky SDLR; the framework combined the two clear-sky algorithms and an existing cloudy-sky algorithm. Finally, the clear-sky and all-sky SDLRs were calculated using the proposed algorithms and framework for the FY-4A and GOES-16 data. The validation results against field measurements indicated that the MBTW and NewAtmos algorithms performed well under the expected clear-sky conditions. The clear-sky SDLRs combined using MBTW and NewAtmos algorithms had RMSEs of 24.8 W/m2 and 18.3 W/m2 for the FY-4A and GOES-16 data, which is comparable to those derived using a single algorithm based on atmospheric parameters; the former portrayed better consistency with field measurements than the latter. The RMSE of instantaneous all-sky SDLR calculated using the proposed method were 24.6 W/m2 and 20.1 W/m2 for FY-4A and GOES-16 data, and they were 23.7 W/m2 and 18.3 W/m2 for the hourly SDLR. The hourly SDLR from the combined algorithms showed a better accuracy than those of the ERA5 SDLR at the same resolution, and also yielded more details of spatial variation than those from ERA5 and from single atmospheric-parameter-based algorithm, because high-resolution thermal infrared (TIR) BT was used in our method. Furthermore, using ERA5 derived PWV, cloud liquid water path and ice water path produced very similar SDLR to those produced using satellite parameters; therefore, for the conditions missing satellite parameters, the ERA5 parameters can be an alternative to achieve continuous SDLR estimation. • A clear-sky SDLR algorithm using multi-channel BT and PWV (MBTW) was developed. • All-sky SDLR was estimated combined using MBTW and other algorithms. • Clear-sky and all-sky SDLRs estimated for FY-4A and GOES-16 data had good results. • Combined algorithms yielded more spatial details of SDLR than single algorithm. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is a vital parameter in the surface energy budget and water cycle. One of the most important foundations for LST studies is a theory to understand how to model LST with various influencing factors, such as canopy structure, solar radiation, and atmospheric conditions. Both physical-based and empirical methods have been widely applied. However, few studies have compared these two categories of methods. In this paper, a physical-based method, soil canopy observation of photochemistry and energy fluxes (SCOPE), and two empirical methods, random forest (RF) and long short-term memory (LSTM), were selected as representatives for comparison. Based on a series of measurements from meteorological stations in the Heihe River Basin, these methods were evaluated in different dimensions, i.e., the difference within the same surface type, between different years, and between different climate types. The comparison results indicate a relatively stable performance of SCOPE with a root mean square error (RMSE) of approximately 2.0 K regardless of surface types and years but requires many inputs and a high computational cost. The empirical methods performed relatively well in dealing with cases either within the same surface type or changes in temporal scales individually, with an RMSE of approximately 1.50 K, yet became less compatible in regard to different climate types. Although the overall accuracy is not as stable as that of the physical method, it has the advantages of fast calculation speed and little consideration of the internal structure of the model. [ABSTRACT FROM AUTHOR]

Land surface temperature (LST) is a vital parameter for the achievement of the surface energy budget and in thorough investigations of water cycle processes. Lightweight thermal infrared (TIR) sensors onboard unmanned aerial vehicles (UAVs) are rapidly becoming key instruments for extracting high-resolution LSTs given the flexibility they offer in capturing different scales. With this expansion, there has been increasing concern regarding the growing demand to obtain a mapping of normalized LST given the directional anisotropy (DA) of surface fine-scale emissions. To date, this topic suffers from a lack of deep analysis and practical solutions for characterizing the DA of fine-scale TIR data from UAV measurements over tree and crop canopies. In this paper, the first objective was to understand the pattern of brightness temperatures (BTs) DAs at a high spatial resolution by using UAV-based multiangle observations and three-dimensional (3D) radiative transfer model simulations. This study highlighted the need for first performing an angular normalization of the BTs of fine-scale pixels prior to any application, as these were easily affected by adjacent pixels and displayed broad spatial variability from 0.5 °C to 5.0 °C due to 3D occlusion. The second objective of the present study was to appraise the reliability of a modified kernel-driven model, in comparison to the model from which it was derived, with an additional kernel designed to mimic the adjacency effect, plus, a quadratic function used to simplify the estimate of the directional emissivity kernel. The root mean square error of the best fit between the measured UAV dataset and the modified kernel-driven model was approximately 0.65 °C, which proves its efficiency since the DA indexes of the BTs were about 1.40 °C. This outlined the role of the model to normalize from directional effects the camera image pixels and thereby deliver fine-scale BTs. In addition, results from LESS simulations also demonstrated the good performance of the modified kernel-driven model for simulating the DAs of thermal emissions for both tree and row-planted scenes. Index Terms—Land surface temperature, UAV, directional anisotropy, high spatial resolution. • Highlight the understanding of directional anisotropies for fine-scale TIR data. • Propose a new kernel for 3D occlusion between adjacent pixels. • Propose a simplified version for a directional emissivity kernel. • Explore a potential angular normalization strategy for UAV TIR data. [ABSTRACT FROM AUTHOR]

Measurements of the surface thermal infrared (TIR) radiance provides an estimate of the land surface temperature (LST). However, any TIR measurement must be acquired under a certain geometry observation, which may refer to strong directional anisotropies. Although physical radiative transfer models can provide high precision directional brightness temperature simulation, they are too complex for processing large volumes of satellite data. With the objective to compare TIR measures acquired under different viewing angles, the topic of angular normalization issue for retrieved LSTs could be treated based on semi-empirical modelling. In this paper, we consider such category of models to simulate the directional anisotropy of surface brightness temperatures in combination with visible and near-infrared (VNIR) data. In these models, the vegetation fraction and the hot spot effect are depicted by a vegetation index and a brightness factor, respectively. An evaluation of the method is performed with both synthetic and measured datasets. The directional anisotropies that are fitted by this semi-empirical model demonstrate good agreement with an extensive synthetic dataset that is generated with the Soil Canopy Observation, Photochemistry and Energy Fluxes (SCOPE) soil-vegetation-atmosphere transfer model. An evaluation using airborne multi-angle TIR data also reveals that this model performs well when predicting BT directional anisotropies, with root mean square errors (RMSEs) of less than 0.31 °C over a maize-planted area. Relative to Roujean-Lagouarde (RL) and Vinnikov models using only TIR data, the proposed model offers better performances. In addition, for future use with satellite data, the proposed model using observations at different times and the combination with VNIR BRDF model are also evaluated, and good results are obtained. It yields a promising approach for the angular normalization of LST and mosaics of fine-scale images. [ABSTRACT FROM AUTHOR]

The enhancement of the living conditions in big cities since the end of the last century is closely related to changes in the thermal environment and besides in urban microclimate, particularly for metropolitan areas. In this context, a knowledge of the spatial and temporal variability of urban heat island (UHI) became an increasing matter of concern, which can be measured from land surface temperature (LST). Actually, LST can be derived from thermal infrared (TIR) remote sensing observations to ensure the necessary spatial and time frequency coverage. But a full exploitation of satellite TIR data cannot be achieved without accounting for the strong anisotropy of urban landscape. Hitherto, a poor investigation was focused on the modeling and the analysis of the directional anisotropies of LSTs considering the complexity of urban building surfaces (e.g., heterogeneity of building morphology and temperature distribution) whereas it is fundamental to establish reliable critical indicators derived from energy balance. Herein, we propose an analytical model to simulate the angular signatures of urban temperatures, in which the geometric optical theory is considered to model the direct radiances of the main components (i.e., sunlit and shaded street, roof and wall). The built model assumes a random distribution of low/middle-rise and high-rise buildings, which depicts realistically the heterogeneity of urban architectural distribution. We evaluated the proposed model using both measured datasets from airborne and satellite sensors and a simulated dataset from a 3D ray-tracing model so-called discrete anisotropic radiative transfer (DART). Results indicate that 1) the proposed model is effective for simulating directional anisotropies of LSTs, with a root mean square error (RMSE) lower than 0.90 ° C and R 2 > 0.49 for comparison with measured datasets; and 2) the directional anisotropies of LSTs are significantly affected by variations in building height, with values possibly exceeding 1.5 ° C. The proposed model can be perceived as a useful tool to analyze the contribution of each component and to assess the impact of urban structure. Furthermore, it can serve to improve urban radiation budget estimations in mixed pixels. • Analyze the directional anisotropy of urban temperature. • Consider the building shape and multiple scattering effect. • Propose an analytical model to simulate angular temperatures. • Quantify the impact of urban heterogeneity on temperature. [ABSTRACT FROM AUTHOR]

Soil salinization and water deficits are considered the primary factors limiting economic development and environmental improvement in arid areas. However, there remains limited knowledge of the adaptability of typical shrubs to salinization of desert areas in arid zones. This study was conducted in a desert oasis transition zone (Tarim River, China), aiming to investigate: i) the spatial-temporal changes in soil salinity; ii) the interactions between the pedoenvironment vs typical shrub (Calligonum mongolicum). The van Genuchten soil salinity retention ensemble model (TVGSSREM-3D) was developed to simulate variations in soil water-salt transport in the desert-oasis zone and to accurately explain the main factors influencing Calligonum mongolicum desert-oases transition areas. The results showed that monthly average salinity ranged from 2.0 to 8.0 g kg−1, with a peak in August (9.17 g kg−1). The presence of human activities (Salt Drainage Canal) and the distribution of Calligonum mongolicum resulted in a clear spatial salinity zonation. Moreover, analysis of environmental indicators using the TVGSSREM-3D model revealed strong correlations between the distribution of salinity in Calligonum mongolicum desert-oases transition areas and groundwater depth (GD), minimum relative humidity (MRH), and water vapor pressure (WVP). These findings provide a scientific basis for stabilizing, restoring, and reconstructing the ecosystem of the oasis-desert transition zone. • The ensemble model was established for the assessment of soil environment. • Salt Drainage Canal is the main reason for salt accumulation. • The presence of C. mongolicum reduced soil salinity by 1 g kg−1 after its occurrence. • The indicator, groundwater depth (GD), was sensitive to the response of salinity levels. [ABSTRACT FROM AUTHOR]

Characterizing drought is mandatory for a thorough monitoring of crop growth. Such information can be inferred from radiometric measurements in optical and thermal spectral ranges. The Temperature Vegetation Dryness Index (TVDI) presents the advantage to mix spectral information since it associates land surface temperature (LST) with normalized difference vegetation index (NDVI). NDVI is known to be weakly impact by directional effects, which is not the case of TVDI as the accuracy assessment of LST can be severely hampered directional anisotropy (DA). In this paper, DA feature of TVDI is analyzed using the kernel-driven model Vinnikov-Li (VinLi) that serves to perform through simulations and remove DA. The study uses both airborne and satellite datasets. TVDI was found to be angularly dependent, with a possible uncertainty larger than 15%. Compared against TVDI without angular correction, the normalized results displayed a better correlation with soil moisture content, and the root mean squared error (RMSE) of estimated soil moisture content decreased obviously, from 0.050 m 3/ m 3 to 0.045 m 3/ m 3 for airborne data over maize canopies, from approximately 0.036 m 3/ m 3 to 0.030 m 3/ m 3 for satellite data over cropland canopies, and from approximately 0.032 m 3/ m 3 to 0.028 m 3/ m 3 for satellite data over grassland canopies. The evaluation was carried out using the complied synthetic datasets based on the Soil Canopy Observation, Photochemistry and Energy Fluxes (SCOPE) model. These also confirmed the occurrence of significant DAs of TVDIs and good performance of VinLi in reducing DA of TVDI by >50%. Based on the VinLi method, an angular-independent TVDI appears necessary to reduce uncertainties originated from illuminating and viewing geometries for the purpose of agriculture monitoring with possible drought episodes. Although further evaluation is still needed using surface measurements, the outcomes support a confident use of TVDI for observations from satellite and airborne/unmanned aerial vehicle. • Analyze the directional anisotropy of TVDI. • Propose a parametric method to simulating angular TVDIs. • Extend the kernel-driven strategy to TVDI. • Introduce an angular-independent TVDI. [ABSTRACT FROM AUTHOR]

Abstract: In this study, the Visible Infrared Imager Radiometer Suite (VIIRS) land surface temperature (LST) environmental data record (EDR) and Moderate Resolution Imaging Spectroradiometer (MODIS) L2 swath LST products (collection 5) from both the Terra and Aqua satellites were evaluated against ground observations in an arid area of northwest China during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) experiment. Four barren surface sites were chosen for the evaluation, which took place from June 2012 to April 2013. The results show that the current VIIRS LST products demonstrate a reasonable accuracy, with an average bias of 0.36K and −0.58K and an average root mean square error (RMSE) of 2.74K and 1.48K for the four sites during daytime and nighttime, respectively. The accuracy of the nighttime LST is much better than that of daytime. Furthermore, it was also found that the VIIRS split-window (SW) algorithm provides better performance than the VIIRS dual split-window (DSW) algorithm during both daytime and nighttime. For MODIS LST products, the results show that both Terra and Aqua MODIS C5 LST products underestimate the LST for the four barren surface sites at daytime, and the biases and RMSEs are much larger for Aqua, with biases varies from −0.91K to −3.13K for Terra and from −1.31K to −3.76K for Aqua. [Copyright &y& Elsevier]

Land surface temperature (LST) is listed as an essential climate variable (ECV) and supports quantitative estimates of the energy budget while serving as a proxy for measuring the effects of climate change and extreme events. Forested areas are considered a major land unit impacted by temperature rise; therefore, thorough monitoring is mandatory. An accuracy assessment of the LST of forests must consider their directional anisotropy (DA). This latter can be well depicted by thermal infrared (TIR) radiative transfer models, but the problem is complex for forests because many of the shaded areas generate multiscale gradients of temperature. In this paper, we adapted a mature and widely used visible and near-infrared (VNIR) radiative transfer model called forest reflectance and transmittance (FRT) to enhance the characterization of the DA of forest temperature. In the FRT model, the vertical heterogeneity of the forest is quantified by using the discrete elements of multilayer scene components (i.e., the tree crown, trunk, understory vegetation, and soil), thus inferring vertical thermal gradients. The Planck function and spectral-invariant theory are considered to assess the thermal emissions of the scene components and their multiple scattering processes. The FRT model is validated using directional forest brightness temperatures (BT) measured from an unmanned aerial vehicle (UAV) and simulated by using the three-dimensional ray-tracing LESS (large-scale remote sensing data and image simulation framework over heterogeneous 3D scenes) model. The results show that FRT behaves reliably since the root mean square error (RMSE) is lower than 1.0 °C for UAV measurements obtained at 09:20 and 13:10 and with coefficients of determination ( R 2 ) larger than 0.74 and 0.56, respectively; these results are better than the simulated results by existing models. Moreover, the comparison with ray-tracing simulations was also deemed satisfactory. According to the analysis, large variations in BT DAs may appear for different forests and seasonal changes staged by structural and thermal stratification, thus indicating the necessity of using the FRT model for complex and dynamic forest canopies. • Extend the VNIR FRT model to TIR applications. • Consider forest structural and thermal stratification • Analyze BTs DAs with different forests and seasonal changes. • Introduce a spectral-invariant theory to FRT. [ABSTRACT FROM AUTHOR]

UAV thermal infrared remote sensing technology, with its high flexibility and high temporal and spatial resolution, is crucial for understanding surface microthermal environments. Despite DJI Drones' industry-leading position, the JPG format of their thermal images limits direct image stitching and further analysis, hindering their broad application. To address this, a format conversion system, ThermoSwitcher, was developed for DJI thermal JPG images, and this system was applied to surface microthermal environment analysis, taking two regions with various local zones in Nanjing as the research area. The results showed that ThermoSwitcher can quickly and losslessly convert thermal JPG images to the Geotiff format, which is further convenient for producing image mosaics and for local temperature extraction. The results also indicated significant heterogeneity in the study area's temperature distribution, with high temperatures concentrated on sunlit artificial surfaces, and low temperatures corresponding to building shadows, dense vegetation, and water areas. The temperature distribution and change rates in different local zones were significantly influenced by surface cover type, material thermal properties, vegetation coverage, and building layout. Higher temperature change rates were observed in high-rise building and subway station areas, while lower rates were noted in water and vegetation-covered areas. Additionally, comparing the temperature distribution before and after image stitching revealed that the stitching process affected the temperature uniformity to some extent. The described format conversion system significantly enhances preprocessing efficiency, promoting advancements in drone remote sensing and refined surface microthermal environment research.

Microwave photonic mixing can realize the frequency conversion of microwave signals in the optical domain, breaking through the bandwidth bottleneck and electromagnetic interference problems of traditional microwave mixing methods. In the background of the hybrid macro-micro cellular system, a wideband, large dynamic range and reconfigurable microwave photonic mixer is proposed, theoretically analyzed and experimentally demonstrated in this paper. By adjusting the modulator bias voltages and matching the proper digital domain operations, a microwave photonic mixer with reconfigurable functions including single-ended dispersion immune mixing, I/Q frequency down-conversion, image rejection mixing, and double-balanced mixing are realized, respectively. Meanwhile, optimizing the electrical attenuator using convex optimization can suppress the third-order intermodulation distortion (IMD3), maximize the conversion gain, and finally improve the spur-free dynamic range (SFDR). Experimental results show that the proposed scheme can be operated with a frequency from 5 to 20 GHz, and the SFDR can achieve 118.3 dB·Hz 4/5 . Over the whole frequency range, I/Q frequency down-conversion can be well conducted with an amplitude imbalance below 0.7 dB and a phase imbalance below ±0.7°. After an I/Q imbalance compensation algorithm, the image rejection ratio of over 60 dB is produced. The power fading caused by fiber dispersion is also compensated successfully. For a vector signal with 16 quadrature amplitude modulation, the best error vector magnitude (EVM) reaches 3.4%.

The ray transfer matrix method is widely used for analyzing beam-transmission properties and designing multi-pass systems. In this paper, a modified ray transfer matrix method is proposed for tracing an accurate non-sequential ray in three-dimensional space based on a vector reflection theory. The modified ray transfer matrix method can be utilized to analyze a ray transmitting between arbitrary surfaces, which is not confined to rotational symmetrical structures. There is no need to project rays onto two perpendicular planes, nor to introduce a paraxial approximation in our calculation. Since the length and angle of every ray can be calculated accurately, almost no deviation is accumulated in multi-pass system. The modified ray transfer matrix method can be applied in optical design, especially in the design of multi-pass cavities and multi-pass cells.

Objective: To explore the effects of mechanical stimulation on the expression of autoantigens in myoblasts., Methods: According to different processing methods, C2C12 cells were divided into the experimental group and control group; the experimental group was divided into 4 subgroups: 2-, 4-, and 6-day and 1-day stretch groups. In 2-, 4-, and 6-day stretch groups, mechanical loading was added on the C2C12 cells at a stretching frequency of 0.25 Hz and cellular deformation amplitude of 10%, 2 hours a day for 2, 4, and 6 days respectively by Flexercell 5000 strain unit, and at a stretching frequency of 1 Hz and cellular deformation amplitude of 15% for 1 hour in 1-day stretch group. In the control group, the cells were routinely cultured for 1, 2, 4, and 6 days (1-, 2-, 4-, and 6-day control). The cells were observed by inverted phase contrast microscope. The cell proliferation was detected by flow cytometry; the expressions of autoantigens were detected by Western blot method, including the Ku/the catalytic subunit of DNA-dependent protein kinase (DNA-PKcs), U1-70 (A part of ATP-dependent DNA helicase II), histidyl tRNA synthetase (HRS), and Mi-2 (reconfigurable components deacetylase complexes of NuRD)., Results: The exfoliated cells were found in 1-day stretch group, but no exfoliated cell was seen in the control group for 1-day culture. The cells proliferated more obviously in 2-day stretch group than in the control group for 2-day culture; cell differentiation was found in 4-day stretch group, and cell fusion in 6-day stretch group, which were similar to those in the control group for 4- and 6-day culture. After single stretching, cell apoptosis was found in 1-day stretch group, showing no significant difference in the relative DNA proliferation index (DPI) when compared with DPI of control group for 1-day culture (t = 0.346, P = 0.747). After cyclic stretching, DPIs of 2- and 4- day stretch groups were significantly increased when compared with those of the control group for 2- and 4-day culture (P < 0.05), but no significant difference was found between control group for 6-day culture and 6-day stretch group (t = 1.191, P = 0.303). Compared with the control group for 2-day culture, the relative protein expression of autoantigens (DNA-Pkcs, Mi-2, HRS, and U1-70) in 2-day stretch group decreased significantly (P < 0.05), but no significant difference was found between control group for 4-day culture and 4-day stretch group (P > 0.05). The relative protein expressions of autoantigens in 4-day stretch group significantly increased when compared with those of 2-day stretch group (P < 0.05), but the relative protein expressions of autoantigens in the control group for 4-day culture significantly decreased when compared with those of the control group for 2-day culture (P < 0.05)., Conclusion: Short-term mechanical stimulation can inhibit the expressions of autoantigens in myoblasts, but with the time prolonging, cell differentiation and fusion and adaptation to mechanical stimulation would result in diminished inhibitory effect.

Objective: To assess the effects of seawater immersion of open abdominal wound and drowning on plasma electrolyte levels in dogs., Methods: Twenty-one dogs with open abdominal wounds were randomly divided into 3 groups, namely the control group (n=7), seawater immersion group (n=7) and seawater immersion and drowning group (n=7). The dogs in the control group were subjected to simple open abdominal wound, and those in the latter two groups were immersed into seawater after the abdominal injury. The changes in the plasma electrolytes and osmotic pressure were observed after the treatments. RESULTS AMD CONCLUSION: Seawater immersion of the open abdominal wound results in hypematremia, hyperkalemia and hypertonic dehydration, and the effect is proportional to the length of immersion time, but seawater airway perfusion does not cause obvious changes of the plasma electrolytes and osmotic pressure in dogs.

Raman spectra of liquid carbon disulfide (CS) and carbon tetrachloride (CCl4) were measured. And the spectral intensity was analyzed using the J. F. Bertran theory and the group theory. The rule about Fermi resonance was obtained from the Raman spectra of carbon disulfide (CS) and carbon tetrachloride (CCL4): (1) The energy can transfer between a fundamental and an overtone frequency about Fermi resonance; the two spectra have the same intensity. The spectral intensity of the two spectra was equal (R=1) about Fermi resonance, when the difference between fundamental of Fermi resonance and overtone of Fermi resonance was very small. (2) The intensity of overtone is stronger than that of fundamental's. (3) The spectrum of Fermi resonance was observed, but the fundamental frequency was not. This article has very good reference value for the assignments in the molecular structure and the research of contents.

Lycopene and beta-carotene are two important nutritional components in tomato. The main Raman spectrum group of lycopene and beta-carotene abundant in tomato is identical and difficult to be distinguished through fundamental frequency. With excitation wavelength of 514.5 nm, the excited light was just present in the half width range of the main absorption bands of Lycopene and beta-carotene, so the resonance Raman effect can occur. Based on resonance Raman spectra, by on-body measuring the second harmonic of stretching vibration of carbon-carbon conjugated double bond in lycopene and beta-carotene, the content of lycopene and beta-carotene can be obtained according to the integrated intensity of each component calculated by software. And this provides a method for on-body determining the content of the components with the homologous group.

Fermi resonance is a very common phenomenon in molecule vibration spectra, especially in polyatomic molecule with complex structure. Fermi resonance appears when a fundamental vibration frequency lies closely to an overtone or combination frequencies. One can observe two peaks coming from Fermi resonance and the energy transfer also occurs between the two peaks. Fermi resonance phenomenon appears in both infrared spectrum and Raman spectrum. The Raman spectrum of CCl4 was measured. The frequency separation between the two peaks in a Fermi resonance doublet was observed and the integrated intensities were calculated with the software of Origin Pro 7.5. Fermi resonance interaction was caused by the CCl4 C-Cl f-symmetrical stretching fundamental nu3 coupling. The combination frequency (nu1 + nu4) of C-Cl a1-symmetrical stretching nu1 and band C-Cl2 f-symmetrical bending nu4 was calculated. Based on Bertran's theory, Fermi coupling coefficient W was calculated and the theoretical value nu3(0) of nu3 was estimated. The present article provided good reference for better understanding of the relationship between molecular vibration frequency and molecular structure.