Onboard Instruments Research Articles

Structural Analysis Technique and Its Validation for Large Range Mirror Refocusing System for Spaceborne Deployable Telescopes

Large aperture deployable telescopes with numerous onboard instruments are popular in the space industry for astronomy. Scientific data in various wavelength bands, from 0.6µ to 28µ, is provided by these instruments and is crucial for deep space exploration. The deployment mechanisms handle the alignment and functionality at the telescope level only. At instrument level, there is always a need for a refocusing system which can cater individual need of instrument for focusing independent to other instruments nearby. In this paper, we present a structural analysis technique for such a type of large range mirror refocusing mechanism, similar to the Near Infrared Spectrograph (NIRSpec) payload of the James Webb Space Telescope (JWST). The method relies on geometric non-linearity for large deflection, in which the structure's stiffness matrix changes as a function of loading. We have designed, analyzed structurally, and tested a 4mm range slider crank based compliant mechanism. The outcomes of linear and non-linear static analysis, computed numerically, have been compared. There are noticeable significant variations in one direction between the two analyses' results. The results are validated using appropriately designed and realized test setups, like measurements of displacement, changes in focus and image position of the optical system.

The thermal impact of the self-heating effect on airless bodies. The case of Mercury’s north polar craters

Thermal models are essential for studying airless planetary surfaces, as the interaction between topography and thermophysical properties plays a crucial role in determining a surface’s response to localized illumination. Accurate temperature distribution calculations require a comprehensive investigation of sunlight scattering, a process that, despite its computational challenges, cannot be overlooked, especially when high resolution is necessary. Furthermore, thermal analysis is fundamental for assessing the stability of volatiles in polar regions. In this study, we introduce a novel approach by discretizing the Sun into 100 individual elements, allowing for a highly precise simulation of solar flux—an innovation crucial for accurately capturing temperature distributions in Mercury’s polar craters, given the planet’s proximity to the Sun. This level of discretization significantly enhances the accuracy of the thermal model, ensuring a more realistic depiction of how sunlight interacts with crater topography. We developed a dual-model approach that simulates both direct solar illumination and its scattering on two craters, Laxness and Fuller, located at Mercury’s north pole. The illumination and thermal model predict temperature distribution and heat transfer based on the material’s thermal properties and topography. The study examines the interaction between direct sunlight, causing localized heating, and scattered light, which influences the thermal response of surface materials. Detailed illumination maps and temperature profiles were generated over two Hermean years, revealing the significant impact of the self-heating effect on temperature distribution. The results show that specific regions experience indirect solar flux due to the craters’ morphology, particularly in permanently shadowed regions (PSRs) that are heated exclusively by scattered radiation. Maximum temperature profiles for the Laxness and Fuller craters show a substantial temperature increase within PSRs compared to areas exposed to direct illumination. However, while self-heating does not affect the stability of water ice in the Laxness crater, in the Fuller crater, a section within the radar-bright material reaches temperatures of up to 210 K, potentially threatening the stability of water ice. Further investigation with the onboard SIMBIO-SYS instrument on the BepiColombo mission will help to better understand the current state of these craters and their volatile deposits.

Convolutional-Neural-Network-Based Autonomous Navigation of Hera Mission Around Didymos

The European Space Agency (ESA)’s Hera mission requires autonomous visual-based navigation in order to safely orbit around the target binary asteroid system Didymos and its moon Dimorphos in 2027. Nevertheless, the performance of optical-based navigation systems depends on the intrinsic properties of the image, such as high Sun phase angles, the presence of other bodies, and, especially, the irregular shape of the target. Therefore, to improve the navigation performance, thermal and/or range measurements from additional onboard instruments are usually needed to complement optical measurements. However, this work addresses these challenges by developing a fully visual-based autonomous navigation system using a convolutional-neural-network (CNN)-based image processing (IP) algorithm and applying it to the detailed characterization phase of the proximity operation of the mission. The images taken by the onboard camera are processed by the CNN-based IP algorithm that estimates the position of the geometrical centers of Didymos and Dimorphos, the range from Didymos, and the associated covariances. The results show that the developed algorithm can be used for a fully visual-based navigation for the position of the Hera spacecraft around the target with good robustness and accuracy.

A Multi-Task Convolutional Neural Network Relative Radiometric Calibration Based on Temporal Information

Due to the continuous degradation of onboard satellite instruments over time, satellite images undergo degradation, necessitating calibration for tasks reliant on satellite data. The previous relative radiometric calibration methods are mainly categorized into traditional methods and deep learning methods. The traditional methods involve complex computations for each calibration, while deep-learning-based approaches tend to oversimplify the calibration process, utilizing generic computer vision models without tailored structures for calibration tasks. In this paper, we address the unique challenges of calibration by introducing a novel approach: a multi-task convolutional neural network calibration model leveraging temporal information. This pioneering method is the first to integrate temporal dynamics into the architecture of neural network calibration models. Extensive experiments conducted on the FY3A/B/C VIRR datasets showcase the superior performance of our approach compared to the existing state-of-the-art traditional and deep learning methods. Furthermore, tests with various backbones confirm the broad applicability of our framework across different convolutional neural networks.

Wavelength Cut-Off Error of Spectral Density from MTF3 of SWIM Instrument Onboard CFOSAT: An Investigation from Buoy Data

The Surface Waves Investigation and Monitoring instrument (SWIM) provides the directional wave spectrum within the wavelength range of 23–500 m, corresponding to a frequency range of 0.056–0.26 Hz in deep water. This frequency range is narrower than the 0.02–0.485 Hz frequency range of buoys used to validate the SWIM nadir Significant Wave Height (SWH). The modulation transfer function used in the current version of the SWIM data product normalizes the energy of the wave spectrum using the nadir SWH. A discrepancy in the cut-off frequency/wavelength ranges between the nadir and off-nadir beams can lead to an overestimation of off-nadir cut-off SWHs and, consequently, the spectral densities of SWIM wave spectra. This study investigates such errors in SWHs due to the wavelength cut-off effect using buoy data. Results show that this wavelength cut-off error of SWH is small in general thanks to the high-frequency extension of the resolved frequency range. The corresponding high-frequency cut-off errors are systematic errors amenable to statistical correction, and the low-frequency cut-off error can be significant under swell-dominated conditions. By leveraging the properties of these errors, we successfully corrected the high-frequency cut-off SWH error using an artificial neural network and mitigated the low-frequency cut-off SWH error with the help of a numerical wave hindcast. These corrections significantly reduced the error in the estimated cut-off SWH, improving the bias, root-mean-square error, and correlation coefficient from 0.086 m, 0.111 m, and 0.9976 to 0 m, 0.039 m, and 0.9994, respectively.

Frequency planning for LISA

The Laser Interferometer Space Antenna (LISA) is poised to revolutionize astrophysics and cosmology in the late 2030s by unlocking unprecedented insights into the most energetic and elusive astrophysical phenomena. The mission envisages three spacecraft, each equipped with two lasers, on a triangular constellation with 2.5 million-kilometer arm-lengths. Six interspacecraft laser links are established on a laser-transponder configuration, where five of the six lasers are offset phase locked to another. The need to determine a suitable set of transponder offset frequencies precisely, given the constraints imposed by the onboard metrology instrument and the orbital dynamics, poses an interesting technical challenge. In this paper we describe an algorithm that solves this problem via quadratic programming. The algorithm can produce concrete frequency plans for a given orbit and transponder configuration, ensuring that all of the critical interferometric signals stay within the desired frequency range throughout the mission lifetime, and enabling LISA to operate in science mode uninterruptedly. Published by the American Physical Society 2024

Quaternion-Based Attitude Estimation of an Aircraft Model Using Computer Vision.

Investigating aircraft flight dynamics often requires dynamic wind tunnel testing. This paper proposes a non-contact, off-board instrumentation method using vision-based techniques. The method utilises a sequential process of Harris corner detection, Kanade-Lucas-Tomasi tracking, and quaternions to identify the Euler angles from a pair of cameras, one with a side view and the other with a top view. The method validation involves simulating a 3D CAD model for rotational motion with a single degree-of-freedom. The numerical analysis quantifies the results, while the proposed approach is analysed analytically. This approach results in a 45.41% enhancement in accuracy over an earlier direction cosine matrix method. Specifically, the quaternion-based method achieves root mean square errors of 0.0101 rad/s, 0.0361 rad/s, and 0.0036 rad/s for the dynamic measurements of roll rate, pitch rate, and yaw rate, respectively. Notably, the method exhibits a 98.08% accuracy for the pitch rate. These results highlight the performance of quaternion-based attitude estimation in dynamic wind tunnel testing. Furthermore, an extended Kalman filter is applied to integrate the generated on-board instrumentation data (inertial measurement unit, potentiometer gimbal) and the results of the proposed vision-based method. The extended Kalman filter state estimation achieves root mean square errors of 0.0090 rad/s, 0.0262 rad/s, and 0.0034 rad/s for the dynamic measurements of roll rate, pitch rate, and yaw rate, respectively. This method exhibits an improved accuracy of 98.61% for the estimation of pitch rate, indicating its higher efficiency over the standalone implementation of the direction cosine method for dynamic wind tunnel testing.

Prediction for Arrival Time and Parameters of Corotation Interaction Regions using Earth–Mars Correlated Events from Tianwen-1, MAVEN, and Wind Observations

Using the Stream Interaction Regions list from the Tianwen-1/Mars Orbiter Magnetometer (MOMAG) data between 2021 November and 2021 December and from Wind observations, we present an accurate prediction for the arrival time and in situ parameters of corotating interaction regions (CIRs) when the Earth and Mars have large longitudinal separations. Since CIRs were detected earlier at Earth than at Mars during the period examined, we employ Earth-based CIR detections for predicting CIR observations at Mars. The arrival time is calculated by the Parker spiral model under the assumption of steady corotation of the Sun and coronal holes, while the in situ parameters are derived from Wind data through radial dependent scaling laws. The CIR prediction results are compared to the actual observations obtained from the MOMAG and Mars Ion and Neutral Particle Analyzer instruments onboard Tianwen-1, as well as the Magnetometer and Solar Wind Ion Analyzer instruments onboard MAVEN. The predicted arrival time is close to the observed values with relative errors less than 10%, and the expected in situ data show a good consistency with the Martian measurements. The comparison results indicate that the prediction method has good performance and will be helpful for comparative analysis with Tianwen-1 observations at Mars in the future.

Passive Biotelemetric Detection of Tibial Debonding in Wireless Battery-Free Smart Knee Implants.

Aseptic loosening is the dominant failure mechanism in contemporary knee replacement surgery, but diagnostic techniques are poorly sensitive to the early stages of loosening and poorly specific in delineating aseptic cases from infections. Smart implants have been proposed as a solution, but incorporating components for sensing, powering, processing, and communication increases device cost, size, and risk; hence, minimising onboard instrumentation is desirable. In this study, two wireless, battery-free smart implants were developed that used passive biotelemetry to measure fixation at the implant-cement interface of the tibial components. The sensing system comprised of a piezoelectric transducer and coil, with the transducer affixed to the superior surface of the tibial trays of both partial (PKR) and total knee replacement (TKR) systems. Fixation was measured via pulse-echo responses elicited via a three-coil inductive link. The instrumented systems could detect loss of fixation when the implants were partially debonded (+7.1% PKA, +32.6% TKA, both p < 0.001) and fully debonded in situ (+6.3% PKA, +32.5% TKA, both p < 0.001). Measurements were robust to variations in positioning of the external reader, soft tissue, and the femoral component. With low cost and small form factor, the smart implant concept could be adopted for clinical use, particularly for generating an understanding of uncertain aseptic loosening mechanisms.

Status of atmospheric air pollution in Ukraine prior to the full-scale russian invasion. Part 2: Pollutants total content according to the satellite data

The paper describes the main features of pollutant total content distribution over Ukraine that can be used as baseline air quality data observed before the full-scale russian invasion in Ukraine. The study is based on the data derived from the TROPOspheric Monitoring Instrument (TROPOMI) onboard of the Sentinel-5 Precursor (5P) satellite that indicates nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and formaldehyde (CH2O) levels. We defined the characteristics of pollutants spatial distribution with full coverage of Ukrainian territory. Despite the increasing role of automotive emissions, the most polluted air in Ukraine was still observed over large industrial cities and smaller settlements having the biggest thermal power plants (TPP). The high level of pollutants content over these locations negatively affects air quality in suburban and rural areas by the prevailing wind. They form relatively stable polluted spots over larger areas. Hence, main polluted areas include: Donetsk Region; territories in the central part of Ukraine along the Dnipro River and near the destroyed Kakhovka reservoir; Kharkiv and Zmiiv TPPs; Kyiv and Trypillia TPPs; and the territories in the western part, including Lviv, Dobrotvir and Burshtyn TPPs. The polluted air from these territories determines the air quality depending on a prevailing wind. In case of high wind speeds polluted air can be distributed from urban areas towards relatively clean territories such as Carpathian and Crimean Mountains, northern Polissia, and the Medobory National Park of Podillia. We determined quantitative parameters of wind speed and direction for every pollutant that causes higher total content over relatively clean territories. Pollutants dispersion in the atmosphere varies depending on a boundary layer height (BLH). It was found that NO2, CO and SO2 content significantly increased when the BLH was below 500 m over both urban areas and clean territories with no emission sources available. The inverse dependence on the BLH was identified for CH2O. This can be explained by a more intense photochemical production at higher altitudes. The detected baseline air pollution conditions can be used in order to assess the impact of the war on air quality in Ukraine and come up with relevant post-war development measures.

EXPERIMENTAL STUDY ON DRIVER’S MENTAL LOAD IN HAIRPIN CURVES OF MOUNTAINOUS HIGHWAY

In order to reveal the driving psychological characteristics and influencing factors of drivers under the hairpin curve section, 11 continuous hairpin curves on mountain roads were selected for natural driving test, and the on-board instruments were used to collect the driver’s ElectroCardioGraphy (ECG) under the natural driving habits. Analyse the overall heart rate characteristics, Heart Rate Increase (HRI), Heart Rate Variability (HRV) characteristics of drivers, as well as the relationship between heart rate change and the visual performance of curve corner and slop and curve environment. And compared with the general curve. The results show that: with 180° as the limit, the curve angle of the hairpin curve was divided into 3 types: greater, less or approximate. The 3 types of curve angle have different effects on the driver’s heart rate fluctuations. The overall heart rate distribution can be divided into 2 regions, in which the average heart rate of each driver at the curve, which curve angle ≈ 180°, was higher than the other 2 types of curves. The overall fluctuation range of heart rate in the middle of the curve is at the lowest level in the 3-stage curve segment area. Through the eigenvalue analysis of HRI, it can be seen that the drivers were more susceptible to the external environment when going downhill. When going uphill, the distribution range of the heart rate abnormality value was stable, but the sudden change was obvious. However, during the downhill direction, the overall adjacent heart rate varies greatly, but the abrupt change was small. Take the change trend of the HRI in the curve segment as an indicator, heart rate types were divided into 4 categories, continuous tension, relax gradually, relaxation-tension, and tension-relaxation. The 4 modes have a significant relationship with the difference of curve entrance environment. Compared with the modes shown in general curves, they focus on the modes with greater volatility, while the general curves focus on a more single growth trend.

Technical Overview and Prospect of India’s First Solar Mission - Aditya L1 Spacecraft

The Aditya-L1 mission represents a significant milestone in solar research, aimed at unlocking the mysteries of our closest star, the Sun. This paper provides an overview of the mission's objectives, scientific instruments, and key findings. By placing a spacecraft in a Lagrangian point L1 orbit, Aditya-L1 offers an unprecedented vantage point for continuous solar observations. The primary scientific goals include studying the Sun's dynamic atmosphere, monitoring solar variability, and enhancing our understanding of space weather and its impact on Earth. The paper discusses the advanced instrumentation onboard, such as the Visible Emission Line Coronagraph (VELC), the Solar Ultraviolet Imaging Telescope (SUIT), and the Aditya Solar Wind Particle Experiment (ASPEX), highlighting their contributions to solar science. Furthermore, this paper presents early results and insights obtained from Aditya-L1's observations, shedding light on solar phenomena, solar eruptions, and their influence on Earth's space environment. The Aditya-L1 mission stands as a testament to international collaboration and technological advancements, poised to reshape our understanding of the Sun and its profound effects on our solar system.

Learning structural stress virtual sensors from on-board instrumentation of a commercial aircraft

This work aims to predict the mechanical stress on the structure of a business jet in service phase from flight instrument only. A significant database obtained from test flights using aircraft instrumented with strain gauges has been provided as part of an Artificial Intelligence challenge organized by the French Ile-de-France region and the aircraft manufacturer Dassault Aviation. Learning techniques are considered to train a prediction model of the aircraft structural stress. The proposed baseline includes a clustering step for phase identification in time series and an ensemble model with two stacked regressors. The model is trained on a dataset of 117 flights and its overall performance is evaluated on a validation set of flight sequences from 186 flights. The main advantages of the proposed learning approach are its prediction accuracy, its training frugality and its interpretability. This paper presents a global data science workflow applied to a problem of structural stress prediction. Despite a development in a constrained time period with no direct access to the data, the proposed approach demonstrates the feasibility of the concept of learned virtual sensor of aircraft structural stress and paves the way for applications to other structures.

Accuracy Assessment of Atmospheric Correction of KMSS-2 Meteor-M #2.2 Data over Northern Eurasia

Atmospheric correction of satellite remote sensing data is a prerequisite for a large variety of applications, including time series analysis and quantitative assessment of the Earth’s vegetation cover. It was earlier reported that an atmospherically corrected KMSS-M (Meteor-M #2) dataset was produced for Russia and neighboring countries. The methodology adopted for atmospheric correction was based on localized histogram matching of target KMSS-M and MODIS reference gap-free and date-matching imagery. In this paper, we further advanced the methodology and quantitatively assessed Level-2 surface reflectance analysis-ready datasets, operatively produced for KMSS-2 instruments over continental scales. Quantitative assessment was based on accuracy, precision, and uncertainty (APU) metrics produced for red and near-infrared bands of the KMSS-2 instrument based on a reference derived from a MODIS MOD09 reconstructed surface reflectance. We compared error distributions at 5%, 20%, and 50% levels of cloudiness and indicated that the cloudiness factor has little impact on the robustness of the atmospheric correction regardless of the band. Finally, the spatial and temporal gradients of accuracy metrics were investigated over northern Eurasia and across different seasons. It was found that for the vast majority of observations, accuracy falls within the −0.010–0.035 range, while precision and uncertainty were below 0.06 for any band. With the successful launch of the most recent Meteor-M #2.3 with a new KMSS-2 instrument onboard, the efficiency and interoperability of the constellation are expected to increase.

Additively manufactured high permeability Fe-Ni alloys and novel bi-metallic magnetic shields

The sensitivity and sophistication of spacecraft for Earth Science and Planetary Science missions are increasing with each successive mission. Advances in instrumentation, robotics, remote sensing, avionics and controls are allowing un-crewed missions to be incredibly sophisticated. Effective electromagnetic shielding is critical for high fidelity functioning of the spacecraft and onboard instrumentation. Moreover, the geometrical complexity of the shielding arrangement and the constraints of size and shape, make additive manufacturing (AM) a critical, enabling technology for current and future missions. Two AM approaches - directed energy deposition (DED) and laser powder bed fusion (LPBF) - were used to produce Fe-80Ni-5Mo alloy rings and shields. The microstructure and magnetic properties of the materials produced through these processes are reported in this paper. A mechanism relating the microstructure to the soft magnetic performance of the material is proposed. The AM material produced in this work demonstrated the highest reported magnetic permeability and lowest reported coercivity of any additively manufactured soft magnetic material. Two different combinations of bi-metallic shields, Fe-80Ni-5Mo/FeCo-2V and Fe-80Ni-5Mo/Fe-49Ni, were fabricated using the DED process. The creation of these shields as monoliths in general, and for space-related applications in particular, is a novel aspect of this work. These multi-alloy, multi-layer shields showed a nearly 10 dB increase in shielding performance over Fe-80Ni-5Mo single alloy shielding, a significant improvement. For the DED builds, the coercivity decreases and permeability increases (better soft magnetic performance) with increasing build power. With increasing build power in the DED process, the grain size in the printed part increases. The corresponding reduction in the grain boundary area results in fewer obstacles to the movement of magnetic domain walls.

Characterisation of a self-sustained, water-based condensation particle counter for aircraft cruising pressure level operation

Abstract. Aerosol particle number concentration measurements are a crucial part of aerosol research. Vertical profile measurements and high-altitude/low-pressure performance of the respective instruments become more important for remote sensing validation and a vital tool for the observation of climate variables. This study tests the new, commercially available water condensation particle counter (MAGIC 210-LP) for the deployment at aircraft cruising pressure levels that the European research infrastructure IAGOS (In-service Aircraft for a Global Observing System; http://www.iagos.org, last access: 2 May 2023) is aiming for by operating measurement instrumentation onboard passenger aircraft. We conducted laboratory experiments for conditions to simulate passenger aircraft flight altitude at operation pressure. We demonstrate that this type of water condensation particle counter shows excellent agreement with a butanol-based instrument used in parallel. A Faraday cup aerosol electrometer serves as the reference instrument. Experiments are performed with test aerosol ammonium sulfate and fresh combustion soot at pressure levels ranging from 700 to 200 hPa. For soluble particles like ammonium sulfate, the 50 % detection efficiency cut-off diameter (D50) is around 5 nm and does not differ significantly for all performed experiments. For non-soluble fresh soot particles, the D50 cut-off diameter of approximately 10 nm does not vary substantially as a function of pressure, whereas the 90 % detection efficiency cut-off diameter D90 increases from 19 nm at 700 hPa to 37 nm at 200 hPa. The overall counting efficiency for particles larger than 40 nm reaches 100 % for working pressures of 200 hPa and higher.

Observing lightning and transient luminous events from the international space station during ILAN-ES: An astronaut's perspective

The ILAN-ES (Imaging of Lightning And Nocturnal Emissions from Space) experiment was conducted by Israeli astronaut Eytan Stibbe in April 2022 as part of the Axiom Space company AX-1 private mission to the International Space Station, in the framework of Rakia, a set of experiments selected for flight by the Ramon Foundation and the Israeli Space Agency. The mission objective was to manually record lightning and transient luminous events from the Cupola window in the ISS, based on preliminary thunderstorm forecasts uploaded to the crew 24–36 h in advance. A Nikon D6 camera with a 50 mm lens was used, in a video mode of 60 frames per second. During the 15-day mission, 82 different targets were uploaded to the ISS of which 20 were imaged by the astronauts, yielding a total harvest of 45 TLEs: sprites, Elves and Blue Corona Discharges. The methodology and execution by the ISS astronauts are described and recommendation for future observations by on-board human-operated instruments on the ISS are given.

Microvibration simulation of reaction wheel ball bearings

Microvibrations on board satellites are a well-known problem affecting their pointing accuracy by inducing oscillations to the line-of-sight. Fast rotating devices, such as reaction wheel assemblies (RWAs) are a major cause of these onboard mechanical disturbances. Imbalances in the flywheel, as well as imperfections in the ball-bearing components yield low-amplitude vibrations that are transmitted to the satellite structure, adversely affecting the performance of sensitive onboard instruments. This research focuses on the RWA’s ball bearing microvibration frequency and amplitude characterization. This is achieved by introducing specific geometry imperfections on the ball bearing rotating elements. In addition, variables such as the ball bearing preload, the number of balls and their dimensions are altered to understand how the bearing microvibration changes in order to minimize it. Finally, available physical microvibration test data is used to compare and cross-correlate the microvibration waterfall plots obtained from the transient FEA of the parametrized bearing models introduced herein. This work provides a better understanding of the relation between the main structural ball bearing parameters and the microvibration disturbances emitted by the RWA to minimize its mechanical noise.

The Uncertainty of SNO Cross-Calibration for Satellite Infrared Channels

The on-orbit radiometric calibration is a fundamental task in quantitative remote sensing applications. A widely used calibration method is the cross-calibration based on Simultaneous Nadir Observation (SNO), which involves using high-precision reference instruments to calibrate lower-precision onboard instruments. However, despite efforts to match the observation time, spatial location, field geometry, and instrument spectra, errors can still be introduced during the matching processes and linear regression analysis. This paper focuses on the error generated by sample matching and the error fitting method generated by the sample fitting method. An error propagation analysis is performed to develop a generic model for assessing the uncertainty of the SNO cross-calibration method itself in meteorological satellite infrared channels. The model is validated using the payload parameters of the Hyperspectral Infrared Atmospheric Sounder (HIRAS) and the Medium Resolution Spectral Imager (MERSI) instruments aboard the FengYun-3D (FY-3D). Simulation experiments are performed considering typical bright temperatures, different background fields, and varying matching threshold conditions. The results demonstrate the effectiveness of the proposed model in capturing the error propagation chain in the SNO cross-calibration process. The model provides valuable insight into error analysis in the SNO cross-calibration method and can assist in determining the optimal sample matching threshold for achieving radiometric calibration accuracy.

Flying Laboratory of Imaging Systems: Fusion of Airborne Hyperspectral and Laser Scanning for Ecosystem Research

Synergies of optical, thermal and laser scanning remotely sensed data provide valuable information to study the structure and functioning of terrestrial ecosystems. One of the few fully operational airborne multi-sensor platforms for ecosystem research in Europe is the Flying Laboratory of Imaging Systems (FLIS), operated by the Global Change Research Institute of the Czech Academy of Sciences. The system consists of three commercial imaging spectroradiometers. One spectroradiometer covers the visible and near-infrared, and the other covers the shortwave infrared part of the electromagnetic spectrum. These two provide full spectral data between 380–2450 nm, mainly for the assessment of biochemical properties of vegetation, soil and water. The third spectroradiometer covers the thermal long-wave infrared part of the electromagnetic spectrum and allows for mapping of surface emissivity and temperature properties. The fourth instrument onboard is the full waveform laser scanning system, which provides data on landscape orography and 3D structure. Here, we describe the FLIS design, data acquisition plan and primary data pre-processing. The synchronous acquisition of multiple data sources provides a complex analytical and data framework for the assessment of vegetation ecosystems (such as plant species composition, plant functional traits, biomass and carbon stocks), as well as for studying the role of greenery or blue-green infrastructure on the thermal behaviour of urban systems. In addition, the FLIS airborne infrastructure supports calibration and validation activities for existing and upcoming satellite missions (e.g., FLEX, PRISMA).