Stationary Detector Research Articles

Method Development and Validation of Droxidopa by RP-UPLC

A simple, rapid, accurate and economical method has been developed for the quantification of droxidopa by UPLC. The chromatographic system was equipped with Phenomenex column C18 (50mm x 3.0mm, 3µ) as stationary phase and UV detector at 235nm, in conjunction with a mobile phase of buffer: methanol (25:75 % v/v ratio) at a flow rate of 1.0mL/min. Linearity was observed over the concentration range of 100-300µg/mL for droxidopa. The droxidopa peak eluted at 0.35 min. The recovery of Droxidopa was found to be 100.17% - 100.63% respectively. Statistical techniques were employed for the validation of precision, linearity, accuracy, robustness and ruggedness and can be applied for routine analysis. Validation revealed that the developed method was specific, accurate, precise, reliable, robust, reproducible and suitable for the routine quantitative analysis.

Estimation of Hourly Traffic Flows from Floating Car Data for Vehicle Emission Estimation

In order to model air quality in heavy pollution days, a dynamic emission monitoring system is implemented in the Beijing road network, which requires the input of hourly traffic flows. Floating car data (FCD) is increasingly employed for flow estimation based on the fundamental diagrams to supplement data provided by stationary detectors. However, existing studies often used a typical fundamental diagram without considering the hysteresis phenomena and the uncertainty of traffic flow estimation. This study aims to develop a multiperiod fundamental diagram for the traffic flow estimation from FCD considering the hysteresis phenomena. The result shows that the proposed multiperiod fundamental diagram can improve the accuracy of flow estimation. The uncertainty of traffic flow estimation at both 10 minutes and 1 hour is also quantified, and the result indicates that the variation of the estimation uncertainty at 1 hour is lower than that at 10 minutes, with an average 7% reduction of the range of 95% confidence interval (CI). But there is no significant difference in magnitudes of the estimation uncertainty at 1 hour compared with that at 10 minutes. Moreover, the uncertainty for congested flows is lower than that for free flows. In the case study, the proposed model is employed to develop the spatial and temporal distributions of flows and emissions for the metropolitan area in Beijing.

A method to measure the integral vertical intensity and angular distribution of atmospheric muons with a stationary plastic scintillator bar detector

We present a method to measure the integral vertical intensity and angular distribution of atmospheric muons using a stationary thick plastic scintillator bar detector with PMTs at both of its ends over exposures of a few hours in a laboratory setting. The total flux is obtained from the event rate and the angular distribution is inferred from the distribution of the recorded pulse charges, which are correlated with the track length inside the plastic scintillator. A muon generator algorithm was developed and used together with a simple simulation including the effects of the detector resolution, nonlinear saturation of the PMTs, and laboratory building coverage. As a proof of principle we made a measurement assuming a standard cosnθ omnienergetic angular distribution with azimuthal isotropy and different models for the energy spectrum of the source. Using measurements at 5 different azimuthal orientations, we measure an average exponent n=(1.90±0.06(stat)±0.10(syst)), and an average vertical intensity of I0=(101.2±1.8(stat)±5.5(syst))m−2s−1sr−1 at the location with geographic coordinates 19.33°N 99.19°W, altitude 2268 m above sea level, and geomagnetic cut-off of 8.2 GV.

Performance evaluation of fifth-generation ultra-high-resolution SPECT system with two stationary detectors and multi-pinhole imaging

BackgroundSmall-animal single-photon emission computed tomography (SPECT) systems with multi-pinhole collimation and large stationary detectors have advantages compared to systems with moving small detectors. These systems benefit from less labour-intensive maintenance and quality control as fewer prone parts are moving, higher accuracy for focused scans and maintaining high resolution with increased sensitivity due to focused pinholes on the field of view. This study aims to investigate the performance of a novel ultra-high-resolution scanner with two-detector configuration (U-SPECT5-E) and to compare its image quality to a conventional micro-SPECT system with three stationary detectors (U-SPECT+).MethodsThe new U-SPECT5-E with two stationary detectors was used for acquiring data with 99mTc-filled point source, hot-rod and uniformity phantoms to analyse sensitivity, spatial resolution, uniformity and contrast-to-noise ratio (CNR). Three dedicated multi-pinhole mouse collimators with 75 pinholes each and 0.25-, 0.60- and 1.00-mm pinholes for extra ultra-high resolution (XUHR-M), general-purpose (GP-M) and ultra-high sensitivity (UHS-M) imaging were examined. For CNR analysis, four different activity ranges representing low- and high-count settings were investigated for all three collimators. The experiments for the performance assessment were repeated with the same GP-M collimator in the three-detector U-SPECT+ for comparison.ResultsPeak sensitivity was 237 cps/MBq (XUHR-M), 847 cps/MBq (GP-M), 2054 cps/MBq (UHS-M) for U-SPECT5-E and 1710 cps/MBq (GP-M) for U-SPECT+. In the visually analysed sections of the reconstructed mini Derenzo phantoms, rods as small as 0.35 mm (XUHR-M), 0.50 mm (GP-M) for the two-detector as well as the three-detector SPECT and 0.75 mm (UHS-M) were resolved. Uniformity for maximum resolution recorded 40.7% (XUHR-M), 29.1% (GP-M, U-SPECT5-E), 16.3% (GP-M, U-SPECT+) and 23.0% (UHS-M), respectively. UHS-M reached highest CNR values for low-count images; for rods smaller than 0.45 mm, acceptable CNR was only achieved by XUHR-M. GP-M was superior for imaging rods sized from 0.60 to 1.50 mm for intermediate activity concentrations. U-SPECT5-E and U-SPECT+ both provided comparable CNR.ConclusionsWhile uniformity and sensitivity are negatively affected by the absence of a third detector, the investigated U-SPECT5-E system with two stationary detectors delivers excellent spatial resolution and CNR comparable to the performance of an established three-detector-setup.

Capabilities of multi-pinhole SPECT with two stationary detectors for in vivo rat imaging

We aimed to investigate the image quality of the U-SPECT5/CT E-Class a micro single-photon emission computed tomography (SPECT) system with two large stationary detectors for visualization of rat hearts and bones using clinically available 99mTc-labelled tracers. Sensitivity, spatial resolution, uniformity and contrast-to-noise ratio (CNR) of the small-animal SPECT scanner were investigated in phantom studies using an ultra-high-resolution rat and mouse multi-pinhole collimator (UHR-RM). Point source, hot-rod, and uniform phantoms with 99mTc-solution were scanned for high-count performance assessment and count levels equal to animal scans, respectively. Reconstruction was performed using the similarity-regulated ordered-subsets expectation maximization (SROSEM) algorithm with Gaussian smoothing. Rats were injected with ~ 100 MBq [99mTc]Tc-MIBI or ~ 150 MBq [99mTc]Tc-HMDP and received multi-frame micro-SPECT imaging after tracer distribution. Animal scans were reconstructed for three different acquisition times and post-processed with different sized Gaussian filters. Following reconstruction, CNR was calculated and image quality evaluated by three independent readers on a five-point scale from 1 = “very poor” to 5 = “very good”. Point source sensitivity was 567 cps/MBq and radioactive rods as small as 1.2 mm were resolved with the UHR-RM collimator. Collimator-dependent uniformity was 55.5%. Phantom CNR improved with increasing rod size, filter size and activity concentration. Left ventricle and bone structures were successfully visualized in rat experiments. Image quality was strongly affected by the extent of post-filtering, whereas scan time did not have substantial influence on visual assessment. Good image quality was achieved for resolution range greater than 1.8 mm in bone and 2.8 mm in heart. The recently introduced small animal SPECT system with two stationary detectors and UHR-RM collimator is capable to provide excellent image quality in heart and bone scans in a rat using standardized reconstruction parameters and appropriate post-filtering. However, there are still challenges in achieving maximum system resolution in the sub-millimeter range with in vivo settings under limited injection dose and acquisition time.

Method development and validation of droxidopa by HPLC technique

The purpose of this work is to develop and validate stability, indicating reverse phase High-performance liquid chromatography (HPLC) method for the rapid and precise determination of droxidopa in its pure form and formulations. A simple, fast, accurate and economical way has been developed and validated for the quantification of droxidopa by HPLC technique. The chromato graphic system was equipped with Shimpack columnC18((250x 4.6) mm, 5µ) as stationary phase and UV detector at 220 nm, in conjunction with a mobile phase of phosphate buffer pH 2.0:acetonitrile (60:40,% v/v) at a flow rate of 1.0 mL/min. The developed HPLC technique was found to be rapid as the retention time was 2.2 minutes for droxidopa peak to elute. The method was validated as per the International Conference on Harmonization (ICH) guidelines for specificity linearity, accuracy, precision. The developed method was selective with well-resolved peak. Linearity was observed over the concentration range of 25-150µg/mL for droxidopa. The recovery of Droxidopa was found to be 100.54% - 101.65%. Statistical techniques were employed for the validation of precision, linearity, accuracy, robustness and ruggedness and can be applied for routine analysis. Validation revealed that the developed method was specific, accurate, precise, reliable, robust, reproducible and suitable for the systematic quantitative review.

Towards real-time density estimation using vehicle-to-vehicle communications

Traffic state estimation is a fundamental task of Intelligent Transportation Systems (ITS). Recent advances in sensor technology and emerging computer and vehicular communications paradigms have brought the task of estimating traffic state parameters in real time within reach. Recognizing this, the US-DOT started promoting the Connected Vehicles (CV) initiative. By using wireless connectivity between the vehicles participating in the traffic, the CV initiative aims to promote an increased awareness of real-time traffic conditions and, as a result, to reduce the number and severity of crashes.A number of recent papers have proposed CV-based approaches to estimating traffic state parameters including density and flow. However, virtually all the CV-based approaches for density estimation also rely on communication with stationary detectors and other pre-deployed roadside infrastructure. This assumption is problematic since such infrastructure is often not available.The main contribution of this paper is to propose a simple and easy to implement real-time traffic density estimation method that uses only vehicle-to-vehicle communications and the on-board sensing capabilities of present-day vehicles. In our method, using their on-board devices, vehicles maintain a tally that keeps track of the difference between the number of times other vehicles pass them and the number of times they pass other vehicles. Notice that since vehicles may vary their speed as they please, they may pass and be passed by the same vehicle multiple times and, consequently, maintaining a correct tally is a non-trivial task. We show that the tallies computed by vehicles relate, in an interesting way, to traffic density.We provide a detailed proof of our method using techniques that avoid the use of common simplifications inherent to visual time-space traffic diagrams. Furthermore, we demonstrate the accuracy of our method through extensive simulations using real NGSIM traffic traces along with SUMO-generated synthetic traffic traces.

EXIRAD-3D: Fast automated three-dimensional autoradiography

IntroductionAutoradiography is an established technique for high-resolution imaging of radiolabelled molecules in biological tissue slices. Unfortunately, creating a 3D image from a set of these 2D images is extremely time-consuming and error-prone. MicroSPECT systems provide such 3D images but have a low resolution. Here we present EXIRAD-3D, a fast automated method as an alternative for 3D autoradiography from coupes based on ultra-high resolution microSPECT technology. MethodsEXIRAD-3D uses a very small bore focusing multi-pinhole collimator mounted in a SPECT system with stationary detectors (U-SPECT/CT, MILabs B.V. The Netherlands) using a sample holder with integrated tissue cooling to avoid activity leaking or tissue deformation during the scan. The system performance was experimentally evaluated using various phantoms and tissue samples of animals in vivo injected with technetium-99m and iodine-123. ResultsThe reconstructed spatial resolution obtained with a Derenzo hot rod phantom was 120 μm (or 1.7 nl). The voxel values of a syringe phantom image appear to be uniform and scale linearly with activity. Uptake in tiny details of the mouse knee joint, thyroid, and kidney could be clearly visualized. ConclusionEXIRAD-3D opens up the possibility for fast and quantitative 3D imaging of radiolabelled molecules at a resolution far better than in vivo microSPECT and saves tremendous amounts of work compared to obtaining 3D data from a set of 2D autoradiographs. Advances in knowledge and implications for patient careEXIRAD-3D offers superior image resolution over microSPECT, and it can be a very efficient alternative for autoradiography in pharmaceutical and biological studies.

Duality in the dynamics of Unruh-DeWitt detectors in conformally related spacetimes

We prove a nonperturbative duality concerning the dynamics of harmonic-oscillator-type Unruh-DeWitt detectors in curved spacetimes. Concretely, using the Takagi transformation we show that the action of a harmonic oscillator Unruh-DeWitt detector with one frequency in a spacetime is equal to that of a detector with a different frequency in a conformally related spacetime. As an example, we show that the dynamics of simple stationary detectors in flat spacetime is dual to that of detectors in a cosmological scenario. The nonperturbative duality enables us to investigate entanglement harvesting in new scenarios in curved spacetime by using results obtained in simpler, conformally related spacetimes.

New Test of the Gravitational 1/r^{2} Law at Separations down to 52 μm.

We tested the gravitational 1/r^{2} law using a stationary torsion-balance detector and a rotating attractor containing test bodies with both 18-fold and 120-fold azimuthal symmetries that simultaneously tests the 1/r^{2} law at two different length scales. We took data at detector-attractor separations between 52 μm and 3.0mm. Newtonian gravity gave an excellent fit to our data, limiting with 95%confidence any gravitational-strength Yukawa interactions to ranges <38.6 μm.

Estimating population density of insectivorous bats based on stationary acoustic detectors: A case study.

Automated recording units are commonly used by consultants to assess environmental impacts and to monitor animal populations. Although estimating population density of bats using stationary acoustic detectors is key for evaluating environmental impacts, estimating densities from call activity data is only possible through recently developed numerical methods, as the recognition of calling individuals is impossible.We tested the applicability of generalized random encounter models (gREMs) for determining population densities of three bat species (Common pipistrelle Pipistrellus pipistrellus, Northern bat Eptesicus nilssonii, and Natterer's bat Myotis nattereri) based on passively collected acoustical data. To validate the results, we compared them to (a) density estimates from the literature and to (b) Royle–Nichols (RN) models of detection/nondetection data.Our estimates for M. nattereri matched both the published data and RN‐model results. For E. nilssonii, the gREM yielded similar estimates to the RN‐models, but the published estimates were more than twice as high. This discrepancy might be because the high‐altitude flight of E. nilssonii is not accounted for in gREMs. Results of gREMs for P. pipistrellus were supported by published data but were ~10 times higher than those of RN‐models. RN‐models use detection/nondetection data, and this loss of information probably affected population estimates of very active species like P. pipistrellus.gREM models provided realistic estimates of bat population densities based on automatically recorded call activity data. However, the average flight altitude of species should be accounted for in future analyses. We suggest including flight altitude in the calculation of the detection range to assess the detection sphere more accurately and to obtain more precise density estimates.

Optimized sampling for high resolution multi-pinhole brain SPECT with stationary detectors

Brain perfusion SPECT can be used in the diagnosis of various neurologic or psychiatric disorders, e.g. stroke, epilepsy, dementia and posttraumatic stress disorder. As traditional SPECT provides limited resolution and sensitivity, we recently proposed a high resolution focusing multi-pinhole clinical SPECT scanner dubbed G-SPECT-I (Beekman et al 2015, Eur. J. Nucl. Med. Mol. Imaging 42 S209). G-SPECT-I achieves data completeness in the scan region of interest (ROI) by making small translations of the patient bed while using projections from all bed positions together for image reconstruction. A strategy to restrict the number of bed translations is desired to minimize overhead time. Previously we presented optimized bed translation paths for focused partial brain imaging, while here we focus on whole brain imaging which is the common procedure in perfusion studies. Thus, a series of noise-free scans using a reduced number of bed positions were simulated and compared to an oversampled reference scan acquired with 128 bed positions. Noisy simulations were included to validate the utility of the optimized sequences in more realistic situations. Brain uptake ratios (BURs) and left–right Asymmetry Indices (AIs) in 51 selected regions of interest (ROIs) were calculated for assessment. Results show that images were barely affected by decreasing the number of bed positions from 128 down to 18 (mean deviation from the reference of only 2.2% and 1.5% for the BUR and AI, respectively) while slightly larger deviations (2.9% and 2.7%, respectively) were obtained when using 12 positions. For both 18- and 12-position sequences these deviations due to sampling were much smaller than those induced by noise (mean deviation of 6.5% and 8.6%, respectively). Given an associated total overhead for bed movement of half a minute (18 positions) or 20 s (12 positions), G-SPECT-I can be a clinical platform that brings new protocols for fast (dynamic) whole brain SPECT and motion correction into reach.

Influence of floating car data quality on congestion identification

This paper explores the usability of floating car data (FCD) of mixed quality in congestion analysis on motorways. The specific data quality aspects that we are investigating are the number and density of trajectories, the GPS interval, and the fleet representativeness. We use a dataset provided by the German Automobile Club ADAC covering the Tyrolean road network in 2016. From this dataset, trajectories along the A12 motorway were extracted for congestion analysis. These data are characterized by high GPS time interval, low number of trajectories, and are not representative for total traffic due to overrepresentation of trucks. The influence of these quality parameters on congestion identification is explored by analyzing the parameter distribution among different congestion types. In addition, we validate the results by comparing them with congestion incidents obtained from the stationary detector data (SDD) and examining the impact of quality parameters on the validation results. We find that the given data set does not allow short-term congestion patterns to be identified due to quality flaws. Especially the low number of trajectories proved problematic, whereas the influence of other parameters was less distinct. Despite these flaws, for large-scale congestion incidents, floating car data provide outcomes similar to those derived from stationary detectors.

Simulation-based Evaluation of Using Variable Speed Limit in Traffic Incidents

Abstract Variable Speed Limit (VSL) systems are used to improve the traffic conditions on road by adjusting the speed limits according to current traffic situations. The variable speed limit system usually comprises of stationary detectors to estimate the traffic condition and dynamic variable message signs at predefined locations for the application of new speed limits. In connected environment, the system can recognize bottlenecks due to the incident and, further, it is possible to use direct control of the connected vehicles to adjust vehicle speeds towards the new traffic situation. In this study, we propose a variable speed limit framework based on connected vehicles environment to improve the management of non-recurrent congestion. The proposed framework is evaluated in terms of traffic efficiency, safety, and environmental impact using microscopic traffic simulation. Furthermore, economic evaluation of these strategies is performed to determine the financial feasibility of their implementation. The results indicate that the VSL system manage to improve traffic efficiency, safety and environmental impact during the incidents. However, it is found that the results depend on incident location and incident severity (number of lanes blocked, and the incident duration).

Novel Drift Reduction Methods in Foot-Mounted PDR System.

The zero-velocity update (ZUPT)-aided extended Kalman filter (EKF) is commonly used in the traditional inertial navigation system (INS)-based foot-mounted pedestrian dead reckoning (PDR) system, which can effectively suppress the error growth of the inertial-based pedestrian navigation systems. However, in the realistic test, the system still often suffers from drift, which is commonly caused by two reasons: failed detection of the stationary phase in the dynamic pedestrian gait and heading drift, which is a poorly observable variable of the ZUPT method. In this paper, firstly, in order to improve the initial heading alignment accuracy, a novel method to calibrate the PDR system’s initial absolute heading is proposed which is based on the geometric method. By using a calibration line rather than only using the heading of the starting point, the method can calibrate the initial heading of the PDR system more accurately. Secondly, for the problem of failed detection of the stationary phase in the dynamic pedestrian gait, a novel stationary phase detection method is proposed, which is based on foot motion periodicity rather than the threshold comparison principle in the traditional method. In an experiment, we found that the zero-speed state points always occur around the minimum value of the stationary detector in each gait cycle. By taking the minimum value in each gait cycle as the zero-speed state point, it can effectively reduce the failed detection of the zero-speed interval. At last, in order to reduce the heading drifts during walking over time, a new motion constraint method is exploited based on the range constraint principle. During pedestrian walking, the distance between the foot position estimates of the current moment and the previous stationary period is within the maximum stride length. Once the distance is greater than the maximum stride length, the constraint method is used to confine the current estimated foot position to the sphere of the maximum stride length relative to the previous stationary foot position. Finally, the effectiveness of all proposed methods is verified by the experiments.

Running measurement protocol for the quantum first-detection problem

The problem of the detection statistics of a quantum walker has received increasing interest. We investigate the effect of employing a moving detector, using a projective measurement approach with fixed sampling time , with the detector moving right before every detection attempt. For a tight-binding quantum walk on the line, the moving detector allows one to target a specific range of group velocities of the walker, qualitatively modifying the behavior of the quantum first-detection probabilities. We map the problem to that of a stationary detector with a modified unitary evolution operator and use established methods for the solution of that problem to study the first-detection statistics for a moving detector on a finite ring and on an infinite 1D lattice. On the line, the system exhibits a dynamical phase transition at a critical value of , from a state where the probability of detection decreases exponentially in time and the total detection probability is very small, to a state with power-law decay and a significantly higher total probability to detect the particle. The exponent describing the power-law decay of the detection probability at this critical is 10/3, as opposed to 3 for every larger . In addition, the moving detector strongly modifies the Zeno effect.

Asymptotic states for stationary Unruh-DeWitt detectors

We study the late-time asymptotic state of a stationary Unruh-DeWitt detector interacting with a field in a thermal state. We work in an open system framework, where the field plays the role of an environment for the detector. The long-time interaction between the detector and the field is modelled with the aid of a one-parameter family of switching functions that turn on and off the interaction Hamiltonian between the two subsystems, such that the long-time interaction limit is reached as the family parameter goes to infinity. In such limit, we show that if the field is in a Kubo-Martin-Schwinger (KMS) state and the detector is stationary with respect to the notion of positive frequency of the field, in the Born-Markov approximation, the asymptotic state of the detector is a Gibbs state at the KMS temperature. We then relax the KMS condition for the field state, and require only that a frequency-dependent version of the detailed balance condition for the Wightman function pulled back to the detector worldline hold, in the sense that the inverse temperature appearing in the detailed balance relation need not be constant. In this setting, we show that the late-time asymptotic state of the detector has the form of a thermal density matrix, but with a frequency-dependent temperature. We present examples of these results, which include the classical Unruh effect and idealised Hawking radiation (for fields in the HHI state), and also the study of the late-time behaviour of detectors following stationary "cusped" and circular motions in Minkowski space interacting with a massless Klein-Gordon field in the Minkowski vacuum. In the cusped motion case, a frequency-dependent, effective temperature for the asymptotic late-time detector state is obtained analytically. In the circular motion case, such effective temperature is obtained numerically.

Approximative Network Partitioning for MFDs from Stationary Sensor Data

The macroscopic fundamental diagram (MFD) measures network-level traffic performance of urban road networks. Large-scale networks are normally partitioned into homogeneous regions in relation to road network topology and traffic dynamics. Existing partitioning algorithms rely on unbiased data. Unfortunately, widely available stationary traffic sensors introduce a spatial bias and may fail to identify meaningful regions for MFD estimations. Thus, it is crucial to revisit and develop stationary-sensor-based partitioning algorithm. This paper proposes an alternative two-step partitioning algorithm for MFD estimations based on information collected solely from stationary sensors. In a first step, possible partitioning outcomes are generated in the road networks using random walks. In a second step, the regions’ MFDs are estimated under every possible partitioning outcome. Based on previous work, an indicator is proposed to evaluate the traffic heterogeneity in regions. The proposed partitioning approach is tested with an abstract grid network and empirical data from Zurich. In addition, the results are compared with an algorithm that disregards stationary detectors’ biases. The results demonstrate that the proposed approach performs well for obtaining the quasi-optimal network partitions yielding the lowest heterogeneity among all possible partition outcomes. The presented approach not only complements existing literature, but also offers practice-oriented solutions for transport authorities to estimate the MFDs with their available data.

Mesoscopic modelling and analysis of traffic flow based on stationary observations

Stationary detectors are widely used in the urban area, such as loops and traffic cameras, providing with aggregated macroscopic quantities as well as individual pass-by records that could reveal the cluster features of the traffic flow. The paper proposes a multi-lane platoon based (MLP) model that can be calibrated with stationary data. A steady-state analysis is conducted to derive the model’s internal capacity constraints (ICC). It is proved in the validation that the ICC mechanism could effectively decrease 60% of the unnatural boundary controls in the simulation system.

Response functions for detectors in cosmic ray neutron sensing

Cosmic-Ray Neutron Sensing (CRNS) is a novel technique for determining environmental water content by measuring albedo neutrons in the epithermal to fast energy range with moderated neutron detectors. We have investigated the response function of stationary and mobile neutron detectors typically used for environmental research in order to improve the model accuracy for neutron transport studies. Monte Carlo simulations have been performed in order to analyze the detection probability in terms of energy-dependent response and angular sensitivity for different variants of CRNS detectors and converter gases. Our results reveal the sensor’s response to neutron energies from 0.1 eV to 106 eV and highest sensitivity to vertical fluxes. The detector efficiency shows good agreement with reference data from the structurally similar Bonner Spheres. The relative probability of neutrons contributing to the overall integrated signal is especially important in regions with non-uniform albedo fluxes, such as complex terrain or heterogeneous distribution of hydrogen pools.