Transmittance Model Research Articles

Dual-Discriminator Conditional Generative Adversarial Network-based LDPC-Coded OFDM Free-Space OCS for Improving BER Analysis

This paper proposes a Dual-Discriminator Conditional Generative Adversarial Network-based LDPC-Coded OFDM Free-Space OCS for Improving BER Analysis (LDPC-OFDM-FSO-DDcGAN). The proposed LDPC-OFDM-FSO-DDcGAN method containsthe transmitter model, the channel model and the receiver model. The binary data are given to the encoder of LDPC in the transmitter model and the input data encode previously controlling the situation using QAM. To decrease the effects of fading caused by turbulence, the channel model intends a probability density function with FSO-DDcGAN. The maximal ratio combing (MRC), equal gain combining (EGC) and selection combining (SC) can be employed by the combiner to integrate the signal once it has been received from the FSO channel. The combiner is used to improve one signal by combining the several signals received. The bit of data is transformed towards a sequential stream after combiner. The proposed Probability Density Function (PDF) offers high SNR gain, BER reduction and power efficiency when combined with DDcGAN. To achieve large coding gain, the standard coding methods of LDPC are used through only a code percentage as realistic to imitation data. The proposed LDPC-OFDM-FSO-DDcGAN technique is executed in MATLAB. The LDPC-OFDM-FSO-DDcGAN method provides higher power efficiency and lower bit error rate analysed with the existing models.

Spatial and temporal analysis of decomposition models in China

This study presents a comprehensive evaluation of 15 decomposition models (12 empirical and 3 atmospheric transmittance models) for estimating diffuse horizontal irradiance at 17 radiation sites in China, using hourly radiation data from 2011 to 2020. Our results show distinct patterns in model performance across different geographical regions, seasons, and sky conditions. The Liu model demonstrates the best overall performance with an RMSE of 78.20 W/m2, while model accuracy shows significant geographical variation, performing best in South and Southeast China (RMSE<70 W/m2) and worst in the Qinghai-Tibet Plateau and Northwest China (RMSE>90 W/m2). Seasonal analysis reveals better performance in winter than in summer, with RMSE differences approaching 40 W/m2, mainly due to the higher proportion of solar elevation angles exceeding 30° in summer. Under different sky conditions (classified by clearness index: 0–0.35 for overcast, 0.35–0.65 for partly cloudy, 0.65–1 for clear skies), most models follow an RMSE pattern of partly cloudy > clear sky > overcast. However, the Reindl2, Boland, DIRINT, and DIRINDEX models deviate from this trend due to their formula structure and sensitivity to atmospheric parameters. To reduce these regional disparities, we propose a new region-specific model selection strategy: the DIRINDEX model for eastern regions, DIRINT for central areas, and Karatasou for western regions. This combined approach reduces the overall RMSE to 73.17 W/m2. This research deepens our understanding of the application of decomposition models in China's complex geographical and climatic conditions, offering valuable references for solar radiation modeling and renewable energy forecasting in diverse climatic regions.

Application of Triple Glazing Thickness Optimization Based on Artificial Fish Swarm Algorithm

In response to the growing demand for energy-efficient building designs in cold northern regions, this study explores the optimization of triple glazing thickness to maximize the transmission of solar energy within the wavelength range of 300-2000 nm. The optimization employs the Artificial Fish Swarm Algorithm (AFSA), which is used to iteratively determine the optimal combination of glass thicknesses. A transmittance model of solar radiation through triple glazing is established, where the thicknesses of the three glass layers are treated as variables. The study shows that the optimized thickness combination significantly enhances the indoor heating effect by maximizing solar energy incidence, offering theoretical support and practical guidance for energy-saving building designs in cold climates. Parameter settings of the AFSA, including perception range, step size, and crowding factor, are analyzed to understand their influence on optimization performance. The results suggest that AFSA efficiently addresses complex optimization problems, demonstrating its potential in optimizing material properties for energy-efficient applications. Future directions include multi-objective optimization considering additional factors such as thermal insulation and cost, algorithmic improvements to enhance search accuracy, and experimental validation of the results in real-world conditions. This research provides a scientific foundation for integrating advanced optimization algorithms into the sustainable design of building materials.

Use of spectral transmittance model to improve the detection accuracy of chromium in soil

As a new quantitative analysis method for heavy-metal elements in soil, the main function of the polarization resolution model is to filter out the disturbance of other elements on the spectral signal of target plasma. In order to quantify the mechanism of improving detection performance, the spectral transmittance of plasma intensity in the polarization-resolved optical path has been derived, and the relationship between the intensity of polarization-resolved laser-induced breakdown spectroscopy (PRLIBS) and the characteristic peak wavelength has been defined. Using the spectral data in the wavelength range of 424.50–429.24 nm as the characteristic signal, a quantitative analysis method for detection of the Cr element in soil has been developed. The improvement of spectral intensity stability at the characteristic peak of Cr I 425.7 was analyzed, and the mechanism of enhancing the detection accuracy was elucidated. Research has shown that, based on the polarization characteristics of Cr element plasma, PRLIBS is not affected by the matrix effects of soil and characterizes the amplitude conversion from the reference concentration of Cr element to the plasma spectral intensity. The spectral transmittance of plasma spectra depends not only on the characteristic peak wavelength and complex refractive index of heavy-metal elements but also on the measurement conditions such as spatial geometric angles and reflectivity of the transmission medium.

Can satellite products monitor solar brightening in Europe?

Satellite products provide the best way to monitor the solar radiation reaching the Earth’s surface on a global scale. However, their capability to monitor solar radiation trends needs to be constantly evaluated. This depends on their temporal stability and the accurate representation of all processes driving solar radiation. This study evaluates these aspects by comparing and cross-comparing different solar radiation products (ERA5, CAMS-RAD 4.6, SARAH-3, CLARA-A3, CERES-EBAF 4.2) against in-situ measurements over Europe.All products show a moderate positive bias over Europe but strong differences in their root mean squared deviation (RMSD) related to their different cloud transmittance models. Geostationary-based products (SARAH-3, CAMS-RAD 4.6) provide the smallest RMSD closely followed by CLARA-A3, whereas ERA5 shows a large RMSD due to random errors in cloud transmittance.All products show an increase in surface solar radiation, or brightening, over the last 40 years over Europe, but the magnitude of the trends and their spatiotemporal variability differ between products. Despite finding temporal inhomogeneities in some products, the different trends are mostly due to different aerosol modeling approaches implemented by each product. Both SARAH-3 (+2.3 W/m2/decade, 2001–22) and CERES-EBAF 4.2 (+2.2 W/m2/decade, 2001–22) provide the most consistent trends compared to in-situ data, showing that after stabilizing in the late 2000s, brightening is particularly recovering in Western Europe. In-situ measurements show a reduction of aerosol optical depth from 2001 to 2022 that has been accentuated in the last 10 years, particularly in Western Europe. This would be consistent with the hypothesis that brightening recovery is driven by an aerosol reduction, though other analyses suggest that clouds also play a role in this recovery. More work is needed to understand the contribution of aerosols to solar radiation trends and the exact aerosol effects represented by each solar radiation product.

Satellite Onboard Transmitter Design With Spread Spectrum MIMO Antenna for 5G Wireless Networks

AbstractThe 5G new era implements standalone satellite communications that support wireless networking systems for future mobile communications by locating multiple satellites in low Earth orbit to provide global coverage of the entire Earth's surface. In this research, a newly found model of a satellite onboard transmitter using a uniform circular array multiple‐input multiple‐output antenna was designed to operate at a carrier frequency of 12 GHz and derived theoretical equations compared to the real‐time scenario. The integration of spread spectrum with multiple‐input multiple‐output antenna provides an advantage for higher capacity. It has a higher percentage of gain amplification on improving the transmission of electromagnetic power to meet the bandwidth requirement of center operating frequency, and this can transmit over a bandwidth of 1.28 GHz. The proposed satellite onboard transmitter model design aims to minimize the components, increase the speed of operations for higher bandwidth, and transmit large amounts of information to a large group of users. The transmitter can operate for the speed of 1.28 Gbps using pseudo‐random code, direct‐sequence spread spectrum, quadrature phase shift keying modulation, bandwidth separated in bands for 64 symbols using 128 Chebyshev‐type bandpass filter for transmission using 128‐element uniform circular array multiple‐input multiple‐output antenna. The satellite transmitter antenna produces a maximum gain of 14.526 dBi, and a maximum directivity of 17.986 dBi, and the efficiency at 12 GHz is 45.1% for the radiated power at 0.93 mW. This satellite transmitter will interconnect 5G wireless networks for the application of mobile communications complement terrestrial‐dependent networks.

Optimization of distribution function and model parameters for molecular communication via diffusion with OtoO approximation

The analysis is generally conducted in stationary receiver and transmitter models in a diffusion environment for the fundamental Molecular communication (MOC) models. However, a mobile MOC model is employed in this study, deviating from the existing literature. This mobile MOC model considers the mobility of all variables in the diffusion environment, including the transmitter, receiver, and molecules. Firstly, a novel MOC model is proposed, departing from the conventional normal distribution for the mobility of variables. Instead, alternative distribution functions such as the Pareto distribution, extreme value distribution, t-distribution, and generalized extreme value distribution are employed. Furthermore, the system's performance is enhanced by optimizing the distribution function and model parameters, such as the diffusion coefficient, using the optimization of optimization (OtoO) approach. In this approach, the Multi-Verse Optimization (MVO) algorithm serves as the primary algorithm, while the Grey Wolf Optimization (GWO) algorithm functions as the auxiliary algorithm. Essentially, the MVO algorithm optimizes the parameters of the MOC model, while simultaneously, the GWO algorithm optimizes the impact of the optimization processes of MVO on the parameters ``p'' and ``N'' as well as the constant parameter of the distribution function. By optimizing both the parameters of the MOC model and the distribution function, the number of received molecules is significantly increased. Therefore, this study not only improves the results of the MOC model structure based on different distribution functions but also optimizes all parameters of the proposed model using the MVO-GWO OtoO approach.

A comprehensive analysis of spatial and temporal patterns of anthropogenic adult mortality of Bonelli's eagles in eastern Spain

AbstractIn eastern Spain, Bonelli's eagle (Aquila fasciata) abundance has declined almost 50% in the last 25 years and, consequently, the species is listed as regionally endangered. Therefore, the aim of this study is to report the mortality causes of territorial breeding Bonelli's eagles, including the spatial and temporal patterns, and to assess the effects on population dynamics. From 2015–2023, we tracked 60 Bonelli's eagles via global positioning system‐global system for mobile communications (GPS‐GSM) telemetry; 33 of the eagles died (median survival time = 1,519 days). Survival did not differ in relation to sex, age at capture (subadult vs. adult birds), breeding site (coastland vs. inland territories), or transmitter's model. One‐year probability of survival (95% CI) was 0.716 (0.607–0.845); 2‐year survival was 0.640 (0.524–0.781); and 3‐year survival was 0.581 (0.464–0.729). Anthropogenic mortality (66.7% of cases) prevailed over natural (27.3%) and unknown causes (6.0%). Causes of mortality were intra‐ and interspecific predation (24.2% of cases), electrocution (18.2%), poisoning (15.1%), collision with power lines (9.1%), shooting (9.1%), drowning (9.1%), collision with other man‐made infrastructure (6.1%), and disease (3.0%). Deaths were most frequent during the early breeding season. Only 2 (6.1%) of 33 deaths recorded occurred within a protected area. Natural causes of mortality were more frequent away from the Mediterranean coast. In contrast, anthropogenic deaths were more frequent near the Mediterranean coast, where human population density is high. We estimated that probability of extirpation of the species in our study area is 17.8% in the next 50 years and 99.2% in 100 years. Nonetheless, a small reduction in adult mortality by ≥15% could prevent extirpation in the next 50 years. Therefore, actions to reduce adult mortality are urgently needed to preserve the Bonelli's eagle in eastern Spain.

On the uncertainty in numerical modeling of wireless communication devices operating at frequencies of 900 MHz, 1800 MHz, and 28 GHz.

Some of the difficulties in numerical modeling of wireless communication devices for dosimetric evaluations arise from, e.g. incomplete documentation available for the numerical model, such as missing information on dielectric materials or the antenna matching circuitry. This study investigates the impact of these difficulties on the dosimetric results, such as the peak spatial average specific absorption rate at 900 and 1800MHz and the peak spatial average power density at 28GHz. The impact of dielectric losses, detuning, and mesh resolution is quantified using different generic and Computer Aided Design (CAD) based models of wireless transmitters. The findings show that the uncertainties of the numerical results due to detuning and mesh resolution can be reduced by normalization to the antenna feedpoint power instead of the feedpoint current. Uncertainties due to variations in dielectric losses can largely be compensated by normalization to the radiated power.

Deep Learning Based Over-the-Air Training of Wireless Communication Systems without Feedback.

In trainable wireless communications systems, the use of deep learning for over-the-air training aims to address the discontinuity in backpropagation learning caused by the channel environment. The primary methods supporting this learning procedure either directly approximate the backpropagation gradients using techniques derived from reinforcement learning, or explicitly model the channel environment by training a generative channel model. In both cases, over-the-air training of transmitter and receiver requires a feedback channel to sound the channel environment and obtain measurements of the learning objective. The use of continuous feedback not only demands extra system resources but also makes the training process more susceptible to adversarial attacks. Conversely, opting for a feedback-free approach to train the models over the forward link, exclusively on the receiver side, could pose challenges to reliably end the training process without intermittent testing over the actual channel environment. In this article, we propose a novel method for the over-the-air training of wireless communication systems that does not require a feedback channel to train the transmitter and receiver. Random samples are transmitted through the channel environment to train a mixture density network to approximate the channel distribution on the receiver side of the network. The transmitter and receiver models are trained with the resulting channel model, and the transmitter can be deployed after training. We show that the block error rate measurements obtained with the simulated channel are suitable for monitoring as a stopping criterion during the training process. The resulting method is demonstrated to have equivalent performance to the end-to-end autoencoder training on small message sequences.

X-ray pulsar observation signals simulation method at the spacecraft in near-Earth space

The near-Earth space holds significant strategic value, and X-ray pulsar-based navigation in this region can diversify navigation methods, enhancing the safety and autonomy of spacecraft. Due to the challenges and high costs associated with obtaining actual measurements of pulsars in near-Earth space, the simulation technology for X-ray pulsar signals in this region can provide input for demonstrating the feasibility of technical solutions and experiments related to the application of X-ray pulsar-based navigation in near-Earth space. Therefore, this paper proposes a method for simulating X-ray signals in near-Earth space. Firstly, a scale transforming method is employed to generate a photon arrival time sequence at the spacecraft that includes energy information. Subsequently, the atmospheric transmittance model is utilized for photon selection, obtaining a sequence of photons that have passed through the atmosphere after absorption. Finally, experimental validation of the proposed algorithm is conducted using Crab pulsar data measured by the Insight-HXMT. The similarity between the simulated data and the measured data is evaluated in terms of profiles, phases, and energy spectra. Simulation experiments demonstrate that the time delay estimation error caused by the simulation algorithm is less than 17.17 us. When the observation tangent point altitude is in the range of 160 km to 180 km, the Pearson correlation coefficient of the profiles between simulated and measured data is 73.74 %. The Pearson residuals of the energy spectra are evenly distributed between −0.2 and 0.2, indicating a good level of similarity between the two.

Theoretical Exploration of Flexible Transmitter Model.

Neural network models generally involve two important components, i.e., network architecture and neuron model. Although there are abundant studies about network architectures, only a few neuron models have been developed, such as the MP neuron model developed in 1943 and the spiking neuron model developed in the 1950s. Recently, a new bio-plausible neuron model, flexible transmitter (FT) model (Zhang and Zhou, 2021), has been proposed. It exhibits promising behaviors, particularly on temporal-spatial signals, even when simply embedded into the common feedforward network architecture. This article attempts to understand the properties of the FT network (FTNet) theoretically. Under mild assumptions, we show that: 1) FTNet is a universal approximator; 2) the approximation complexity of FTNet can be exponentially smaller than those of commonly used real-valued neural networks with feedforward/recurrent architectures and is of the same order in the worst case; and 3) any local minimum of FTNet is the global minimum, implying that it is possible to identify global minima by local search algorithms.

Online measurement of birefringence of sensing fibers in the AFOCT system

AbstractThis paper presents a novel scheme to online measure the birefringence of the sensing fiber in all‐fiber optic current transformer (AFOCT) system, which monitors the current on direct current (DC) transmission lines using the Faraday magneto‐optic effect in sensing fibers. In this scheme, by purposefully varying the difference of square‐wave modulated phases via the phase modulator in the AFOCT system, different system transmittances can be obtained. On the basis of the relationship between the system transmittance and linear and circular birefringences, an online measurement scheme of both the linear and circular birefringences of the sensing fibers can be established. In this scheme, the AFOCT system is described by the transmission model based on the Jones matrices, with which the current on DC transmission lines can be measured from the phase shift caused by the Faraday effect. Then, under different square‐wave modulated phases, the system transmittance models are constructed with respect to the linear and circular birefringences of the sensing fiber. For a given sensing fiber with certain linear and circular birefringences, the specific system transmittances are determined and are the curves in space in the respective system transmittance models. Subsequently, these curves in space can be projected onto the coordinate plane composed of the linear and circular birefringence coordinate axes, where the intersection point of the projected plane curves gives the to‐be‐measured values of the linear and circular birefringences of the sensing fiber. The proposed scheme is validated by the preset linear and circular birefringences of the sensing fiber, with different linear birefringences of the polarization‐maintaining fiber. The measurement results show the values consistent with the preset ones.

Evaluation of transpiration in different almond production systems with two-source energy balance models from UAV thermal and multispectral imagery

AbstractA growing number of intensive irrigated production systems of the almond crop have been established in recent years. However, there is little information regarding the crop water requirements. Remote sensing-based models such as the two-source energy balance (TSEB) have proven to be reliable ways to accurately estimate actual crop evapotranspiration. However, few efforts have been made to validate the transpiration with sap flow measurements in woody row crops with different production systems and water status. In this study, the TSEB Priestley-Taylor (TSEB-PT) and contextual approach (TSEB-2T) models were assessed to estimate canopy transpiration. In addition, the effect of applying a basic clumping index for heterogeneous randomly placed clumped canopies and a rectangular hedgerow clumping index on the TSEB transpiration estimation was assessed. The TSEB inputs were obtained from high resolution multispectral and thermal imagery using an unmanned aerial vehicle. The leaf area index (LAI), stem water potential (Ψstem) and fractional intercepted photosynthetically active radiation (fIPAR) were also measured. Significant differences were observed in transpiration between production systems and irrigation treatments. The combined use of the TSEB-2T with the C&amp;N-R transmittance model gave the best transpiration estimations for all production systems and irrigation treatments. The use of in situ PAR transmittance in the TSEB-2T model significantly improved the root mean squared error. Thus, the better agreement observed with the TSEB when using the C&amp;N-R model and in situ PAR transmittance highlights the importance of improving radiative transfer models for shortwave canopy transmittance, especially in woody row crops.

Evaluation of a forest radiative transfer model using an extensive boreal forest inventory database

The forest reflectance and transmittance model (FRT) is applicable over a wide swath of boreal forest landscapes mainly because its stand-specific inputs can be generated from standard forest inventory variables. We quantified the accuracy of this model over an extensive region for the first time. This was done by carrying out a simulation study over a large number (12,369) of georeferenced forest plots from operational forest management inventories conducted in Southern Finland. We compared the FRT simulated bidirectional reflectance factors (BRF) with those measured by Landsat 8 satellite Operational Land Imager (OLI). We also quantified the relative importance of several explanatory factors that affected the magnitude of the discrepancy between the measured and simulated BRFs using a linear mixed effects modelling framework. A general trend of FRT overestimating BRFs is seen across all tree species and spectral bands examined: up to ∼0.05 for the red band, and ∼0.10 for the near infrared band. The important explanatory factors associated with the overestimations included the dominant tree species, understory type of the forest plot, timber volume (acts as a proxy for stand maturity), vegetation heterogeneity and time of the year. Our analysis suggests that approximately 20% of the error is caused by the non-representative spectra of canopy foliage and understory. Our results demonstrate the importance of collecting representative spectra from a diverse set of forest stands, and over the full range of seasons.

New solar radiation transmittance models of transparent envelope based on spectral splitting and their influence on building heat gain

Climate change and the energy crisis have led to increasing attention to building energy efficiency worldwide, and transparent envelopes are more critical as a weak link in building energy efficiency. However, there is a lack of quantitative research on the spectral transmittance properties of transparent envelopes. In this paper, the spectral transmittance of transparent envelopes is quantitatively studied using the controlled variable method. The transmittance calculation formula in the existing standard is modified. Firstly, five types of transparent envelopes commonly used are selected, and their transmittance to the full solar spectrum is studied to establish a transmittance model for different wavelengths. The study also focuses on the 300 nm–1100nm waveband and establishes a solar radiation transmittance benchmark model (SRTB model) based on single-pane clear glass. Secondly, the solar radiation transmittance at different wavelengths is tested by considering both the glass material and the inclination angle, and a solar radiation transmittance modified model (SRTM model) that can be modified to the SRTB model is established. Thirdly, the variation between the incident angle and transmittance is investigated, and the solar radiation transmittance-incident angle model (SRT - IA model) is developed. The results show that deviations between the fixed transmittance and SRT - IA model can reach a maximum of more than 10% for incident angles of less than 60°. Finally, the variation in radiation heat gain due to the SRT - IA model and fixed transmittance is compared in China based on typical meteorological year data. The research conclusion can provide a more precise assessment of the building heat gain from transparent envelopes and then evaluate the building energy consumption reasonably, and provide a theoretical basis for the full-spectrum utilization efficiency of solar radiation.

Analysis of the Transmission Spectrum of Flat Glass from Near-infrared to the Ultraviolet

Contemporarily, glass windows have a great impact on human beings’ daily life. It is crucial to design a glass with a reasonable thickness with a high transmission of visible light as well as a high reflection of near infrared light. In general, reflection from the glass surface and absorption of light waves by the glass material are important features for transmission. Therefore, for UV-visible near-infrared light waves, the greater the thickness of the glass, the greater the light absorption loss and the lower the transmission rate. However, it is believed that there are multiple reflections of light waves in flat glass and that the losses caused by reflections should also be related to the refractive index of the glass and the wavelength of the incident light. On this basis, this study has developed theoretical models of transmittance versus incident light wavelength and glass thickness, refractive index and absorption coefficient. According to the theoretical analysis, the thickness of the glass has a significant effect on the transmission spectrum of sunlight. To experimentally verify this theoretically predicted anomaly, this paper designed the experimental and measurement route and built the experimental test rig. A variety of glass samples in the thickness range of 1mm-10mm were designed and prepared for this project, and the UV-Vis-NIR transmission of the glass was scanned and measured, while the final measurement results observed anomalies in the variation of transmission with thickness. The experimental results, therefore, provide valid support for the theoretical model of this paper.

Molecular Communication Transmitter Design in Limited-Capacity Storage Regime.

The limited storage capacity at the transmitters of a molecular communication (MC) system can affect the system's performance. One of the reasons for this limitation is the size restriction of the transmitter, which the storage must be replenished so that the transmitter has enough molecules for future transmission. This paper proposes a biologically inspired transmitter model based on neurons for MC whose storage charging and discharging follow differential equations. The proposed transmitter opens its outlet for a specific time in each time frame to exponentially release a portion of stored molecules to code bit-1 and remains silent to code bit-0. We analyze our model based on different transmission parameters. These parameters are the symbol duration, the release time duration, the storage capacity, and the release and replenishment rate of the storage. We find that the storage outlet must be open for a certain period within the time slot duration in order to improve the performance of the proposed system. Additionally, we demonstrate that determining the effect of storage capacity size can be important for practical MC due to the significant differences between the ideal transmitter and the proposed one, which have a limited size. We show that increases in the transmitter storage size can improve the system performance. As a result, taking a closer look at these practical transmitters is essential to solving the problems and challenges of molecular communication systems.

Receiver mount design, transmitter depth, and wind speed affect detection probability of acoustic telemetry transmitters in a Missouri River tributary

BackgroundOne of the most important considerations for acoustic telemetry study designs is detection probability between the transmitter and the receiver. Variation in environmental (i.e., wind and flow) and abiotic (i.e., bathymetry) conditions among aquatic systems can lead to differences in detection probability temporally or between systems. In this study we evaluate the effect of distance, receiver mount design, transmitter depth, and wind speed on detection probabilities of two models of acoustic transmitters in a mid-sized river. InnovaSea V16-6H (hereafter V16) and V13-1L (hereafter V13) tags were deployed in the James River, SD at 0.36 m (deep) and 2.29 m (V16 tag) or 1.98 m (V13 tag; shallow) above the benthic surface downstream of InnovaSea VR2W stationary receivers at distances of 100, 200, or 300 m. We used two receiver mount designs that included a fixed position within a PVC pipe on the downstream side of a bridge piling or a metal frame deployed in the middle of the river channel. Tags were deployed for 72 h at each location, and hourly detections were summarized. We evaluated downstream distance, receiver mount design, tag depth, and wind effects on tag detection using Bayesian logistic regression.ResultsDetection probability decreased as distance increased for all combinations of tag types and mount designs and varied from nearly 100% at 100 m to less than 10% at 300 m. The V16 transmitter had greater detection probability by the receiver mounted in the pipe than in the midriver frame. For both mounts, the deep V16 transmitter had greater detection probability than the V16 shallow transmitter. Detection probability of the V13 transmitter was similar between receiver mounts or transmitter depths. Wind speed had a negative impact on detection probabilities of both transmitter types and depths, except the deep V16 transmitter.ConclusionsDeploying acoustic receivers in PVC pipes rather than midriver frames provided greater downstream detection probabilities for V16 transmitters under conditions evaluated in this study. In addition, V16 transmitters had greater detection probabilities when positioned deep within the water column rather than near the surface. We also demonstrated that wind speed can have a negative impact on detection probabilities.

Improved parametrisation of a physically-based forest reflectance model for retrieval of boreal forest structural properties

Physically-based reflectance models offer a robust and transferable method to assess biophysical characteristics of vegetation in remote sensing. Forests exhibit explicit structure at many scales, from shoots and branches to landscape patches, and hence present a specific challenge to vegetation reflectance modellers. To relate forest reflectance with its structure, the complexity must be parametrised leading to an increase in the number of reflectance model inputs. The parametrisations link reflectance simulations to measurable forest variables, but at the same time rely on abstractions (e.g. a geometric surface forming a tree crown) and physically-based simplifications that are difficult to quantify robustly. As high-quality data on basic forest structure (e.g. tree height and stand density) and optical properties (e.g. leaf and forest floor reflectance) are becoming increasingly available, we used the well-validated forest reflectance and transmittance model FRT to investigate the effect of the values of the “uncertain” input parameters on the accuracy of modelled forest reflectance. With the state-of-the-art structural and spectral forest information, and Sentinel-2 Multispectral Instrument imagery, we identified that the input parameters influencing the most the modelled reflectance, given that the basic forestry variables are set to their true values and leaf mass is determined from reliable allometric models, are the regularity of the tree distribution and the amount of woody elements. When these parameters were set to their new adjusted values, the model performance improved considerably, reaching in the near infrared spectral region (740–950 nm) nearly zero bias, a relative RMSE of 13% and a correlation coefficient of 0.81. In the visible part of the spectrum, the model performance was not as consistent indicating room for improvement.