Remote Measurement Research Articles

Assessment of the reliability of at-home caregiver-collected anthropometric measurements.

Anthropometric measurements provide valuable information about infant growth patterns and can help identify nutrition, growth, and developmental concerns. With the increasing use of telehealth and decentralized clinical trial approaches, there is potential for caregivers to collect anthropometric measurements at home via teleconference with healthcare providers (HCPs) to monitor infant growth, which indirectly reflects health status. This study aimed to evaluate whether telehealth-guided caregivers can utilize standardized methods and home-use measurement equipment to collect reliable anthropometric measurements compared to HCPs and study nurses. The study compared the weight, length, and head circumference measurements collected by caregivers (n = 8 pairs), pediatric HCPs (n = 7), and study nurses (n = 4), who served as the gold standard comparator group. Four silicone dolls with varied anthropometrics were used as surrogates for human infants. Caregiver inter- and intra-observer technical errors of measurement (TEMs) were all equal to or below the maximum allowed error (MAE). For HCPs, only intra-observer TEM for length and inter-observer TEM for HC and length were within the MAE. There was no evidence of bias for either caregiver or HCP measurements compared to the gold standard. Coefficients of reliability (R) were greater than 0.96 for all measurements. Preliminary results from this study demonstrate that telehealth-guided caregivers can capture accurate and reliable anthropometric measurements compared to HCPs. The results suggest that remote measurement collection allows for more frequent monitoring while reducing the burden on patients and caregivers in primary care and clinical trials such as infant formula growth monitoring studies.

Remote liquid level monitoring based on coda wave interferometry

Abstract Accurate monitoring of liquid level is important for both liquid stocking and related industrial procedures, it is however difficult under extreme circumstances where the inner space of the container is inaccessible or out of reach. Therefore, this paper proposes a remote liquid level monitoring method based on the use of ultrasonic coda wave interferometry. Coda waves stem from multiply scattering of elastic waves under the interactions with the boundary of propagation medium or scatters during their propagation, they are commonly observed in complex propagation medium. For having propagation trajectories much longer than the coherent waves, coda waves are capable of sampling the propagation medium repeatedly and more comprehensively, which in turn provides coda waves with higher sensitivity to its propagation medium. Letting ultrasonic waves propagate within the liquid container, which is often elastic medium, they are capable of probing the solid-liquid interface globally and repeatedly. As the changing in liquid level alters such solid-liquid interfaces inevitably, the propagation of coda wave is thus affected even without any contact with the liquid level. In this manuscript, experimental study is represented, of which the results show that waveform distortion of coda waves, estimated by remnant decorrelation coefficients, is quantitatively related with the change of liquid level, demonstrates the feasibility of remote liquid level measurement and continuous monitoring of liquid level with ultrasonic techniques.

Circumpolar Transport and Overturning Strength Inferred From Satellite Observables Using Deep Learning in an Eddying Southern Ocean Channel Model

AbstractThe Southern Ocean connects the ocean's major basins via the Antarctic Circumpolar Current (ACC), and closes the global meridional overturning circulation (MOC). Observing these transports is challenging because three‐dimensional mesoscale‐resolving measurements of currents, temperature, and salinity are required to calculate transport in density coordinates. Previous studies have proposed to circumvent these limitations by inferring subsurface transports from satellite measurements using data‐driven methods. However, it is unclear whether these approaches can identify the signatures of subsurface transport in the Southern Ocean, which exhibits an energetic mesoscale eddy field superposed on a highly heterogeneous mean stratification and circulation. This study employs Deep Learning techniques to link the transports of the ACC and the upper and lower branches of the MOC to sea surface height (SSH) and ocean bottom pressure (OBP), using an idealized channel model of the Southern Ocean as a test bed. A key result is that a convolutional neural network produces skillful predictions of the ACC transport and MOC strength (skill score of 0.74 and 0.44, respectively). The skill of these predictions is similar across timescales ranging from daily to decadal but decreases substantially if SSH or OBP is omitted as a predictor. Using a fully connected or linear neural network yields similarly accurate predictions of the ACC transport but substantially less skillful predictions of the MOC strength. Our results suggest that Deep Learning offers a route to linking the Southern Ocean's zonal transport and overturning circulation to remote measurements, even in the presence of pronounced mesoscale variability.

Interrater Reliability and Precision of a Novel Hand Strength Assessment and Treatment Device: The GripAble.

Occupational therapy practitioners need modern tools for the assessment of maximal grip strength in clinical and remote settings. To establish the (1) interrater reliability and (2) precision of the GripAble among three raters with different expertise in occupational therapy when testing healthy participants, and to (3) evaluate the relative reliabilities of different approaches to estimating grip strength (i.e., one trial, mean of two trials, and the mean of three trials). Measurement study. Minnesota Translational Musculoskeletal and Occupational Performance Research Lab, University of Minnesota, Minneapolis. Thirty volunteers, age ≥18 yr, without any hand problems. Using GripAble, three occupational therapy raters with varied experience measured the maximal grip strength of the dominant and nondominant hands of all participants. Using the mean of three trials when testing grip strength with GripAble adds precision. GripAble has excellent interrater reliability (i.e., intraclass correlation coefficient > .75) and acceptable precision (minimal detectable change < 15%) among healthy adults. GripAble allows occupational therapy practitioners with different experiences to assess grip strength in healthy hands quickly, precisely, and with excellent reliability. Additional research is needed on its psychometrics in clinical populations and capacities in remote monitoring and exergaming. Plain-Language Summary: The results of this study show that grip strength, an important biomarker and commonly assessed construct in occupational therapy, can be evaluated reliably, precisely, and rapidly with GripAble. The use of GripAble by occupational therapy practitioners in clinical settings may help to build an infrastructure for remote measurements and exergaming interventions in the future.

Development of a wireless multichannel miniature impedance measurement system and its application for bolt loosening detection

The piezoelectric impedance-based technique is always regarded as one of the most promising structural health monitoring and nondestructive evaluation methods. In recent years, impedance measurement chip AD5933 with the characteristics of high integration and cost-effectiveness makes it possible to address the huge and high-cost problems of the commercialized impedance measurement instrument during the process of structural health monitoring and defect identification. However, it still faces lots of challenges for the chips to be utilized in practical applications due to several limitations, such as short distance for data transmission, single measurement channel and artificial attendant requirement. In this paper, a wireless multichannel miniature impedance measurement system composed by the front-end measurement device and the remote measurement and control platform on the server, is firstly developed and presented with the functions of wireless data transmission, multi-channel acquisition and remote data post-processing. Subsequently, the design concept and composition of the system were introduced in detail. Then, a series of piezoelectric transducers related tests were conducted to validate its impedance measurement performance, especially when comparing with the ones measured by commercialized instruments. In addition, to verify its effectiveness and feasibility of the developed system for the structural damage detection, a bolt loosening detection experiment on the flange connection of a pipeline specimen was investigated for its damage localization and severity quantification. Finally, all the results demonstrated that the developed system provides a great possibility to be used as a convenient and portable impedance measurement tool for the civil structural health monitoring and damage identification in practical applications.

Phenotyping for Effects of Drought Levels in Quinoa Using Remote Sensing Tools

Drought is a principal limiting factor in the production of agricultural crops; however, quinoa possesses certain adaptive and tolerance factors that make it a potentially valuable crop under drought-stress conditions. Within this context, the objective of the present study was to evaluate morphological and physiological changes in ten quinoa genotypes under three irrigation treatments: normal irrigation, drought-stress followed by recovery irrigation, and terminal drought stress. The experiments were conducted at the UNSA Experimental Farm in Majes, Arequipa, Peru. A series of morphological, physiological, and remote measurements were taken, including plant height, dry biomass, leaf area, stomatal density, relative water content, selection indices, chlorophyll content via SPAD, multispectral imaging, and reflectance measurements via spectroradiometry. The results indicated that there were numerous changes under the conditions of terminal drought stress; the yield variables of total dry biomass, leaf area, and plant height were reduced by 69.86%, 62.69%, and 27.16%, respectively; however, under drought stress with recovery irrigation, these changes were less pronounced with a reduction of 21.10%, 27.43%, and 17.87%, respectively, indicating that some genotypes are adapted or tolerant of both water-limiting conditions (Accession 50, Salcedo INIA and Accession 49). Remote sensing tools such as drones and spectroradiometry generated reliable, rapid, and precise data for monitoring stress and phenotyping quinoa and the optimum timing for collecting these data and predicting yield impacts was from 79–89 days after sowing (NDRE and CREDG r Pearson 0.85).

Regulating Arrhenius Activation Energy and Fluorescence Quantum Yields of AuNCs-MOF to Achieve High Temperature Sensitivity in a Wide Response Window.

Luminescent thermometry affords remote measurement of temperature and shows huge potential in future technology beyond those possible with traditional methods. Strategies of temperature measurement aiming to increase thermal sensitivity in a wide temperature response window would represent a pivotal step forward, but most thermometers cannot do both of them. Herein, we propose a balancing strategy to achieve a trade-off between high Arrhenius activation energy (Ea), which could stretch the temperature response windows, and fluorescence quantum yields (QYs) in a manner that will increase thermal sensitivity in a wide response window. In particular, a luminescent thermometer composed of AuNCs-MOF is prepared via a facile impregnation process to enhance QYs and Ea, responsible for high relative sensitivity (Sr) (15.6% K-1) and ultrawide temperature linearity range (from 83 to 343 K), respectively. Taking fluorescence intensity and lifetime as multiple parameters, the maximum Sr can reach 22.4% K-1 by multiple linear regression. The maximum Sr and temperature response range of the proposed thermometer outperform those of the most recent luminescent thermometers. The strategy of balancing Sr and thermal response range by regulating Ea and QYs enables the construction of ultra-accurate thermal sensors in the age of artificial intelligence.

Identification of Blood Sugar Based on Non-invasive Measurements UsingPhotoplethysmography Method Signal Decoding in Diabetics in Tasikmalaya

Non-invasive blood sugar testing tools are now in great demand among the public. This research aims to develop a non-invasive blood sugar examination tool with a Photopletysmograph signal decoding system based on data acquisition from a wearable sensor device on the wrist. The tool used for data acquisition uses Near Infra Red Light-emitting Diode NIR LED 880 nm, 660 nm and 537 nm. This acquisition transfers signals from the body via a photodiode to a PC Personal Computer for processing using Matlab. The method used in this research is to look for the height of the systolic and diastolic amplitude of the Photopletysmograph PPG signal and use the peak-to-peak voltage Vpp to implement Beer Lambert's law. This method was tested on 54 people, randomly aged 26-89 years, with normal blood sugar to high blood sugar. The results show an error of 18.37% from the gold standard. In conclusion, the use of the PPG signal decoding method has proven to be significant in producing blood sugar values. Furthermore, this method was developed for real-time remote measurements via wearable sensor devices.

Hyper-reduced-order model for estimating convection heat transfer coefficients of turbine rotors

Forced convection heat transfer occurs inside the steam turbine, and it is crucial for thermal and strength analysis to accurately estimate the convection heat transfer coefficients of the turbine rotor. This paper presents a hyper-reduced-order model for efficiently estimating the forced convection heat transfer coefficients of a steam turbine rotor. Unlike the full-order finite element method, the hyper-reduced-order model uses the discrete empirical interpolation method to approximate the domain integration of transient heat conduction simulations. This approach greatly reduces the degrees of freedom of numerical integration, thus substantially improving the computational efficiency of forward heat conduction problems. The hyper-reduced-order model and Levenberg–Marquardt algorithm are combined to minimize temperature errors between the numerical simulation results and remote sensor measurements and iteratively estimate the heat transfer coefficients of forced convection in the rotor. The accuracy and efficiency of the proposed model are verified through a transient heat conduction simulation. Moreover, the effects of the initial guess values and measurement errors are investigated to demonstrate the universality and robustness of the proposed approach in determining the convection heat transfer coefficient. Compared with the full-order finite element model, the proposed hyper-reduced-order model can increase the efficiency of forward heat conduction simulations of the turbine rotor by more than 10 times, and it only takes 0.87 s computer runtime in single transient step simulation, and then rapidly estimate the forced convection heat transfer coefficients. Furthermore, the performance of the proposed approach is insensitive to the initial guess values, and it exhibits great robustness under measurement error. The mean errors are 4.78 %, 2.67 % and 10.51 % when the initial values are 0.015 mW·mm−3·°C−1, 0.05 mW·mm−3·°C−1 and 0.15 mW·mm−3·°C−1 respectively. When there is no measurement error, the estimated error of the convection heat transfer coefficients is 2.67 %, and even if the measurement error reaches 5 %, and the accuracy loss is only 5.57 %. Consequently, this approach is highly suitable for estimating convection heat transfer coefficients during the dynamic operation of steam turbines, and this research provides reliable guidance for the optimization design and safe operation of steam turbines.

What Can Hurricane Sam (2021) Tell Us About Extreme Ocean Waves Under Tropical Cyclones?

AbstractWe investigate the ocean wave field under Hurricane Sam (2021). Whilst measurements of waves under Tropical Cyclones are rare, an unusually large number of quality in situ and remote measurements are available in that case. First, we highlight the good consistency between the wave spectra provided by the Surface Waves Investigation and Monitoring (SWIM) instrument onboard the China‐France Oceanography SATellite, the in situ spectra measured by National Data Buoy Center buoys, and a saildrone. The impact of strong rains on SWIM spectra is then further investigated. We show that whereas the rain definitely affects the normalized radar cross section, both the innovative technology (beam rotating scanning geometry) and the post‐processing processes applied to retrieve the 2D wave spectra ensure a good quality of the resulting wave spectra, even in heavy rain conditions. On this basis, the satellite, airborne and in situ observations are confronted to the analytical model proposed by Kudryavtsev et al. (2015, https://doi.org/10.1002/2015JC011284). We show that an extended fetch mechanism may be invoked to explain the large significant wave height observed in the right front quadrant of Hurricane Sam.

Contrast-Phys+: Unsupervised and Weakly-Supervised Video-Based Remote Physiological Measurement via Spatiotemporal Contrast.

Video-based remote physiological measurement utilizes facial videos to measure the blood volume change signal, which is also called remote photoplethysmography (rPPG). Supervised methods for rPPG measurements have been shown to achieve good performance. However, the drawback of these methods is that they require facial videos with ground truth (GT) physiological signals, which are often costly and difficult to obtain. In this paper, we propose Contrast-Phys+, a method that can be trained in both unsupervised and weakly-supervised settings. We employ a 3DCNN model to generate multiple spatiotemporal rPPG signals and incorporate prior knowledge of rPPG into a contrastive loss function. We further incorporate the GT signals into contrastive learning to adapt to partial or misaligned labels. The contrastive loss encourages rPPG/GT signals from the same video to be grouped together, while pushing those from different videos apart. We evaluate our methods on five publicly available datasets that include both RGB and Near-infrared videos. Contrast-Phys+ outperforms the state-of-the-art supervised methods, even when using partially available or misaligned GT signals, or no labels at all. Additionally, we highlight the advantages of our methods in terms of computational efficiency, noise robustness, and generalization.

Mobile toolbox (MTB) remote measures of executive function and processing speed: development and validation.

The ability to remotely monitor cognitive skills is increasing with the ubiquity of smartphones. The Mobile Toolbox (MTB) is a new measurement system that includes measures assessing Executive Functioning (EF) and Processing Speed (PS): Arrow Matching, Shape-Color Sorting, and Number-Symbol Match. The purpose of this study was to assess their psychometric properties. MTB measures were developed for smartphone administration based on constructs measured in the NIH Toolbox® (NIHTB). Psychometric properties of the resulting measures were evaluated in three studies with participants ages 18 to 90. In Study 1 (N = 92), participants completed MTB measures in the lab and were administered both equivalent NIH TB measures and other external measures of similar cognitive constructs. In Study 2 (N = 1,021), participants completed the equivalent NIHTB measures in the lab and then took the MTB measures on their own, remotely. In Study 3 (N = 168), participants completed MTB measures twice remotely, two weeks apart. All three measures exhibited very high internal consistency and strong test-retest reliability, as well as moderately high correlations with comparable NIHTB tests and moderate correlations with external measures of similar constructs. Phone operating system (iOS vs. Android) had a significant impact on performance for Arrow Matching and Shape-Color Sorting, but no impact on either validity or reliability. Results support the reliability and convergent validity of MTB EF and PS measures for use across the adult lifespan in remote, self-administered designs.

MOVEMENT-CONTROLLED STREET LIGHTING SYSTEM WITH MINIMAL POWER CONSUMPTION

Energy consumption in the public lighting system represents the largest part of the energy usage of a community, while the maintenance and operation of the system are a considerable expense for every city. This paper focuses on products and innovative components for street lighting, proposing a consumption-reducing solution based on an intelligent system for remote measurements and control with dimming technologies for high-intensity discharge (HID) lamps. The results indicate that considerable energy savings are achieved and the service life of the lamps is extended. A movement-controlled street light system is controlled according to the specific mode. The modes are controlled by two sensors, which are the light-dependent resistor (LDR) and the infrared (IR) sensor. This system can automatically turn on and off the lights according to traffic flow. It operates at night, and the focus is only on the one-way road at a junction. The street light will be on when there is at least one road user; otherwise, it will turn off. This design can save a great deal of energy compared to conventional street lights that keep a light throughout the night. Moreover, the maintenance cost can be reduced, and the lifespan of the system will increase. As a result, the system has been successfully designed and implemented as a model system.

ANALYSIS OF THE DESTRUCTION OF UKRAINIAN NUCLEAR FUEL CYCLE ENERGY FACILITIES AS A RESULT OF RUSSIAN MILITARY OPERATIONS

Problem statement. Due to Russia's ongoing terrorist attacks on Ukraine's energy facilities, the energy system was damaged, resulting in blackouts and rolling blackouts across the country. The destruction of power capacities resulted in the unstable operation of certain critical infrastructure units for electricity generation at thermal, nuclear and hydroelectric power plants and the introduction of forced hourly blackout schedules. Seizure of the Chornobyl Nuclear Power Plant, occupation and full control of the Zaporizhzhia Nuclear Power Plant and the Zaporizhzhia Thermal Power Plant (TPP). Complete destruction of the Kakhovka hydroelectric power station (HPP), partial destruction of the Dnipro HPP, Dniester HPP and Kaniv HPP. During the hostilities, Kryvyi Rih and Prydniprovia TPPs were damaged, Luhansk TPP (90–100 %), Vuhlehirsk TPP (90–100 %), Zmiiv TPP (up to 90 %) were completely destroyed, Burshtyn TPP (80–90 %) and Ladyzhyn TPP (70–95 %) were almost completely destroyed. The purpose of the article is to identify and analyse the damage to Ukrainian TPPs, HPPs and NPPs caused by the Russian military actions against Ukraine and to determine possible consequences for the nuclear fuel cycle of our country and possible prospects for the transition to new nuclear reactors of European and global fuel cell manufacturers, to improve equipment and stabilise the energy market in the context of military operations. Conclusion. In the course of the analysis of potential hazards at radiation hazardous facilities (RHF) in Ukraine, it was determined that the main threat is accidents at RHF with release of radiation into the atmosphere, lithosphere and hydrosphere. In the light of recent events regarding the military seizure of the Chornobyl NPP and Zaporizhzhya NPP, measurements using standard methods of research, screening and monitoring are not possible, and access of IAEA representatives is limited, which is why the latest measurement methods should be used with the use of autonomous remote-controlled ground, surface and air drones in automatic object or sample measurement of radiation parameters at RNS. It is the use of autonomous vehicles (drones) that is currently the most pressing issue of radiation safety not only in the nuclear power industry but also in the entire nuclear fuel cycle as part of the environmental safety of Ukraine. In case of seizure of a nuclear facility or limited access to it, research methods should be changed. If the facility is partially seized or access is available, then express methods of radiation contamination registration or sampling can be used and the method of laboratory research can be used in the future. However, if a nuclear power plant or a facility that is part of the nuclear fuel cycle of Ukraine is captured and access to it is impossible, then only methods of remote measurement of the radiation situation at and around nuclear facilities using ground and airborne autonomous vehicles remain. For further research, it is necessary to identify technical possibilities for using Ukraine's own mineral resources and switching from Soviet RBMK-1000, VVER-440 and VVER-1000 reactors with fuel elements supplied to us from the Russian Federation to newer types of European and American reactors with appropriate fuel elements.

Optimal control technique applied to the minimization of uncertainty measurements in surveying instruments

The objective of this study was to develop an optimal control approach by numerical calculus to predict how to reduce the overall uncertainty of survey instruments unable to directly measure inaccessible points. To reach our goal, two approaches were used to attain the objective. The first was inspired by mathematical models related to three methods appropriately selected and contained in Zhuo’s work proposed in 2012. These were Remote Elevation Measurement (REM), Remote Elevation Dual Measurement (REDM), and Front-to-Back Measurement (FBM) methods whose uncertainties on the measurements of points were deduced using error propagation equations. Optimal control technique helps us to show that for the REM, the height h of the prism contributed more than 70% compared to the global uncertainty for ranges [Formula: see text] from the prism. For the REDM, when the distance between two consecutive stations increases, the weight of the contribution of the two zenith angles [Formula: see text] and [Formula: see text] tends to 50% each for [Formula: see text] close to [Formula: see text], which is to be avoided. For the FBM, the weight of the contribution during the front measurement process before is negligible. The second approach used the Swedish regulation of SIS-TS 21143:2009 which classified total stations according to types of uncertainty to compare the results given by the total station of class T3 unable to directly measure inaccessible points with the more sophisticated class T1 station with direct measurements. Thus, for small spans at the rear measurements [Formula: see text], the height [Formula: see text] of the front prism has the greatest relative contribution more than 90% for zenithal differences [Formula: see text]. This results of our analysis were convincing and provided designers with the data to minimize the overall uncertainties essential in the conception of total stations.

The adaptability research and evaluation of digital distance protection based on Python and PSCAD

With the development of power systems, digital distance protection, as an innovative and cutting-edge technology, plays a crucial role in ensuring the stable operation of the power grid. Due to its high precision, rapidity, and reliability, digital distance protection has become a key component of power system safety. Distance protection is widely used in distribution networks at or below 35 kV. Therefore, studying its adaptability and effectiveness as a remote backup protection can provide an effective foundation for improving grid security.With the utilization of Python and PSCAD, the adaptability of digital distance protection is meticulously examined in the context of low voltage side faults in 110 kV/35 kV transformers, specifically as a remote backup protection measure. The core objective of this investigation is to assess the efficacy of this protection strategy in upholding the safety and reliability of power systems. To achieve this, 3 approaches is employed: theoretical analysis, simulation modeling, and experimental validation. This process allows for a comprehensive evaluation of the performance characteristics and application efficacy of digital distance protection. The insights garnered from this meticulous study offer profound understanding into the strengths and potential limitations of this protection paradigm, serving as a solid foundation for the refinement of existing protection strategies and the enhancement of the overall resilience of power systems. In essence, this article aims to evaluate the effectiveness of digital distance protection as a remote backup protection strategy for faults on the low-voltage side of 110 kV/35 kV transformers. The core objective is to assess the efficacy of this protection strategy in maintaining the safety and reliability of the power system.

Method for remote measurement of specific conductivity and moisture of subsurface soil horizons

The aim of the research is to develop a radar method for determining the physical and chemical parameters of subsurface soil horizons, providing rapid determination of moisture and specific conductivity in the area of the plant root system. The proposed method is based on a set of Fresnel equations which describe reflection of electromagnetic waves from the interface between dielectric media in vertical and horizontal polarization of the probing signal. For the practical implementation of the method, it is proposed to use two unmanned aerial vehicles that form a bistatic radar system which irradiates the Earth's surface obliquely in order to create the Brewster's effect and increase the fraction of the radio signal reflected from subsurface horizons. The percentage of moisture and the specific conductivity of soil are calculated from the measured values of the imaginary part of the complex permittivity. The required accuracy of moisture and conductivity measurements is achieved by two-step calibration of the measuring device. The values of the moisture content and specific conductivity of soil obtained by radar at a frequency of 469 MHz are in good agreement with the results of measuring these parameters using the soil moisture meter TDR 150 Spectrum Technologies, Inc.

Influence of Temperature and LED Light Spectra on Flavonoid Contents in Poa pratensis

Light and temperature are the driving forces in plant development and growth. Specific photoreceptors provide the ability to sense and interpret light and temperature to regulate growth. Under the limited light conditions in most sports stadiums, natural grasses suffer from light deficiency. Artificial light provided by light-emitting diodes (LEDs) is used to increase their growth and adjust their development. Flavonoids like flavonols and anthocyanins are influenced by light conditions and temperature. Increased blue light can elevate the content of these secondary metabolites. Remote measurements of internal parameters using non-destructive methods provided information on their content under different temperature conditions for quality monitoring. This experiment tested flavonoid contents in Kentucky bluegrass (Poa pratensis) for different blue-to-red light ratios (0.6 and 0.4) and three temperature courses (constant temperature of 4 °C, constant temperature of 12 °C, and temperature switching among 12–8–4–8–12 °C). The results show elevated levels of flavonoids under blue-dominant artificial light as well as increased content under low-temperature (4 °C) conditions. The lack of flavonoids at elevated temperatures (12 °C), especially under red-dominant light, suggests an increased requirement for artificial blue light at increased temperatures. Non-destructive flavonoid determination was suitable for this experiment and can therefore be used for practical sports turf quality monitoring.

Estimation of Soil Moisture from Multispectral Remote Sensing Data

Soil moisture is an important parameter in agricultural and environmental studies and affects the exchange of water and energy at the boundary between the earth’s surface and the atmosphere. Accurate estimation of spatial-temporal changes in soil moisture is critical for numerous studies in the agricultural sciences. Vegetation indices, based on combinations of digital data of reflected light in the visible and near-infrared range, are suitable for the detection of water stress in plants. Therefore, they are widely used to monitor and detect drought conditions, but their accuracy is dependent on different vegetation types. The main objective of this research was to develop a novel procedure for the estimation of soil moisture using multispectral remote measurements. This study has been done using a multispectral camera Survey 3W Red+Green+NIR, which records images in three spectral channels: green (550 nm), red (660 nm) and near-infrared (850 nm). Eleven soil samples with different water content were investigated. SNAP (Sentinel Application Platform) software was used to process the captured multispectral images. It allows an easy calculation of various vegetation indices. The suitability of the normalized difference vegetation index (NDVI) for the assessment of soil moisture was evaluated. The average NDVI values did not indicate a well-established trend in relation to the SWC. A new simple vegetation index NIR/Green was successfully used for the assessment of soil moisture. The new NIR/Green index gives consistent results in relation to the real soil water content and could be used for mapping of the soil moisture with multispectral cameras.

Mesocosm Experiment to Evaluate Relations between Chlorophyll-a Concentration and Water Surface Reflectance in an Anthropogenic Reservoir

This paper presents the results of a mesocosm experiment for the evaluation of remote sensing chlorophyll-a (chl-a) concentration estimations in an anthropogenic water reservoir. The chl-a presence in the water causes changes in the water surface reflectance spectrum, especially in the green and red part, but many factors could affect the remote measurements of chl-a content. The in situ mesocosm method of the experiment was used for investigating the spectral reflectance of the inland water surface in a wide range of chl-a concentrations. Eight specially designed measurement boxes were placed into the water. In half of the boxes, the devices to support the development of the submerged water plant were installed. During the experiment, simultaneously, spectral data from the water surface were gathered and physical–chemical analyses of water were carried out. The obtained results confirm the usefulness of the mesocosm experiment for the remote sensing chl-a concentration algorithms being developed. The concentration of dissolved organic carbon was identified as a key factor that interfered with remote chl-a estimations in the analyzed reservoir.