Future Satellite Missions Research Articles

Lab-on-PCB solid propellant microthruster with multi-mode thrust capabilities.

In the realm of nano/microsatellite clustering, the demand for microthrusters is steadily growing. Solid propellant microthrusters, recognized for their lightweight build and structural simplicity, carry significant commercial promise. However, existing solid propellant microthrusters manufactured using MEMS technology encounter notable issues such as inconsistent thrust generation positions, limited thrust profiles, and issues related to productivity, scalability, and durability. In this study, we propose a novel shared-chamber solid-propellant microthruster design that consistently produces thrust at a designated position and accommodates multiple thrust modes. The components and fabrication of this thruster were developed using lab-on-printed-circuit-board (PCB) technology and PCB surface mount technology, showcasing enhanced structural stability, scalability, and potential for mass production. Our ignition and combustion experiments confirmed the repeatability of the unit operation, a fundamental feature of this innovative microthruster. Furthermore, we successfully implemented and evaluated the power mode for increased thrust and the continuous mode for prolonged operational duration. Integrating the lab-on-PCB-based shared-chamber solid propellant microthruster with propulsion and electronic control systems holds promising potential for future satellite missions.

PHILIPPINE EARTH OBSERVATION SATELLITE MISSIONS AND APPLICATIONS: A DECADAL SURVEY

Abstract. The Decadal Survey was conducted to generate recommendations for integrated and sustainable conduct of space-based environmental monitoring and Earth observation (EO) science programs. Inputs from members of the scientific community and various stakeholders were synthesized to gain an in-depth understanding of the current status and gaps in our space- and non-space-based observation systems in addressing challenges that may persist or arise in this decade. The Decadal Survey is conducted in two phases. The first phase is the Request for Information 1 (RFI-1), where 29 experts from the scientific community were asked to describe the most pressing challenges in their field and the corresponding objectives to address these challenges. A total of 54 challenges and 94 objectives were identified across six focus areas. The second phase consisted of the Delphi Survey where stakeholders from the government, academe, private sector, and non-government organization were asked to rank the challenges and objectives identified from Phase 1. A Request for Information 2 (RFI-2) is conducted to gather information on current programs and projects and institutional capabilities in relation to space science & technology applications (SSTA). Six focus areas (FAs) were identified to adequately cover the components of Earth observation. The assessment and validation of the prioritization of the challenges and objectives resulted in the identification of the top challenges per focus area. These priority challenges and objectives were then compared with the current SSTA technology capabilities of the agencies and institutions to identify common initiatives and gaps or areas for improvement. The results provided a glimpse of how the country’s current SSTA capabilities and initiatives are implemented to solve different scientific challenges and objectives. Looking at the list of previous and ongoing projects, much focus has been made on addressing challenges in resource management and disaster risk reduction and management. Fewer programs and projects center on climate and Earth processes studies. Although most of the identified challenges were matched with at least one ongoing project, there is also concern about the continuity and sustainability of these projects. The Decadal Survey provided information regarding the priority objectives, the target observables, and the mission specifications and timelines from the program of record. The collated information was used to conduct a mission gap analysis that eventually determined the satellite payloads needed to address most of the priority challenges and objectives. The performed gap analysis led to the identification of three instrument gaps that will serve as the basis of future EO satellite missions.

Performance evaluation of three bio-optical models in aerosol and ocean color joint retrievals

Abstract. Multi-angle polarimeters (MAPs) are powerful instruments to perform remote sensing of the environment. Joint retrieval algorithms of aerosols and ocean color have been developed to extract the rich information content of MAPs. These are optimization algorithms that fit the sensor measurements with forward models, which include radiative transfer simulations of the coupled atmosphere and ocean systems (CAOSs). The forward model consists of sub-models to represent the optics of the atmosphere, ocean water surface and ocean body. The representativeness of these models for observed scenes and the number of retrieval parameters are important for retrieval success. In this study, we have evaluated the impact of three different ocean bio-optical models with one, three and seven optimization parameters on the accuracy of joint retrieval algorithms of MAPs. The Multi-Angular Polarimetric Ocean coLor (MAPOL) joint retrieval algorithm was used to process data from the airborne Research Scanning Polarimeter (RSP) instrument acquired in different field campaigns. We performed ensemble retrievals along three RSP legs to evaluate the applicability of bio-optical models in geographically varying water of clear to turbid conditions. The average differences between the MAPOL aerosol optical depth (AOD) and spectral remote sensing reflectance (Rrs(λ)) retrievals and the MODerate resolution Imaging Spectroradiometer (MODIS) products were also reported. We studied the distribution of retrieval cost function values obtained for the three bio-optical models. For the one-parameter model, the spread of retrieval cost function values is narrow regardless of the type of water even if it fails to converge over coastal water. For the three- and seven-parameter models, the retrieval cost function distribution is water type dependent, showing the widest distribution over clear, open water. This suggests that caution should be used when using the spread of the cost function distribution to represent the retrieval uncertainty. We observed that the three- and seven-parameter models have similar MAP retrieval performances in all cases, though they are prone to converge at local minima over open-ocean water. It is necessary to develop a screening algorithm to divide open and coastal water before performing MAP retrievals. Given the computational efficiency and the algorithm stability requirements, we recommend the three-parameter bio-optical model as the coastal-water bio-optical model for future MAPOL studies. This study provides important practical guides on the joint retrieval algorithm development for current and future satellite missions such as NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission and ESA's Meteorological Operational-Second Generation (MetOp-SG) mission.

Sun-induced fluorescence spectrum as a tool for assessing peatland vegetation productivity in the framework of warming and reduced precipitation experiment

Northern peatlands store a large amount of carbon in the form of partially decomposed organic matter. Because the majority of northern peatlands are located in remote areas, remote sensing serves as a suitable alternative to traditional surveys, enabling to enhance our understanding of peatland vegetation. Among various optical remote sensing signals, sun-induced fluorescence (SIF) is the most directly connected to carbon assimilation by plants, making it a promising early-response indicator for assessing the impact of climate change on natural ecosystems. However, the behavior of SIF throughout the season and the strength of the relationship between SIF and carbon assimilation for peatland vegetation, which consists of peat mosses and vascular plants with diverse anatomy, morphology, physiology, and phenology, have not yet been studied. Therefore, we conducted the first comprehensive assessment of the full spectrum SIF, reflectance, and gross primary production (GPP) for two distinct peatland vegetation communities under control (C), warming (W), and warming with reduced precipitation (WP) conditions throughout an entire season. While we could detect clear differences in SIF and reflectance between the two vegetation communities for original, C, vegetation during the main growing season, these differences diminished when W and WP were applied. The W and WP conditions caused a more pronounced change in plant biomass for vegetation characterized by a higher proportion of peat mosses and low creeping shrubs, which resulted in significant changes in the SIF and reflectance spectrum. Our findings demonstrate that the domination of peatland by vascular plants that is expected due to future warmer conditions causes stronger seasonal variation of SIF, reflectance, and GPP. We observed that far-red SIF and the spectrally integrated full SIF spectrum strongly correlate (r2 > 0.85) with GPP regardless of vegetation community, temperature, and precipitation regime. However, the use of a novel multiple wavelength regression model using ten bands from the full SIF spectrum allowed for higher accuracy in the estimation of GPP compared to the use of single bands or integrated total SIF value. Moreover, such a model has a more stable performance when transferring from one vegetation community to another. Conversely, the correlation strength of traditional vegetation indices like the Normalized Difference Vegetation Index or MERIS Terrestrial Chlorophyll Index depends on the peatland vegetation community. While the SIF:GPP relationship exhibits similar r2 values for vegetation communities with different ratios of planophile and electrophile leaves, the slope of the linear model depends on this ratio. This study performed at the ground level shows for the first time the importance of full spectrum SIF for the monitoring of a heterogeneous ecosystem like peatland, which will help to better utilize the SIF products obtained through current and future satellite missions.

Biomass Burning Plume from Simultaneous Observations of Polarization and Radiance at Different Viewing Directions with SGLI

The Earth Observation Satellite Global Change Observation Mission—Climate (GCOM)-C (SHIKISAI in Japanese), carrying a second-generation global imager (SGLI), was launched in 2017 by the Japan Aerospace Exploration Agency. The SGLI performs wide-swath multi-spectral measurements in 19 channels, from near-ultraviolet to thermal infrared (IR), including the red (674 nm; PL1 channel) and near-IR (869 nm; PL2 channel) polarization channels. This work aimed to demonstrate the advantages of SGLI, particularly the significance of simultaneous off-nadir polarized and nadir multi-spectral observations. The PL1 and PL2 channels were tilted at 45° for the off-nadir measurements, whereas the other channels took a straight downward view for the nadir measurements. As a result, the SGLI provided two-directional total radiance data at two wavelengths (674 and 869 nm) that were included in both off-nadir and nadir observations. Using these bidirectional data, an algorithm was applied to derive the altitude of the aerosol plume. Furthermore, because of the significance of the simultaneous observation of polarized and non-polarized light, the sensitivity difference between the radiance and polarized radiance was demonstrated. Severe wildfire events in Indonesia and California were considered as examples of specific applications. Herein, we present the results of our analysis of optically thick biomass-burning aerosol events. The results of the satellite-based analysis were compared with those of a chemical transport model. Exploring the SGLI’s unique capability and continuous 5-year global record paves the way for advanced data exploitation from future satellite missions as a number of multi-directional polarization sensors are programmed to fly in the late 2020s.

Evaluation of total ozone measurements from Geostationary Environmental Monitoring Spectrometer (GEMS)

Abstract. The continued interest in air pollution and stratospheric ozone variability has motivated the development of a Geostationary Environmental Monitoring Spectrometer (GEMS) for hourly ozone monitoring. This paper provides the atmospheric science community with the world's first assessment of GEMS total column ozone (TCO) retrieval performance and diurnal ozone variation. The algorithm used for GEMS is a more advanced version of its predecessor, the Total Ozone Mapping Spectrometer (TOMS) V8, that incorporates several improvements, including a new lookup table, a simple Lambertian-equivalent reflectivity model, and a spectral dependence correction. The GEMS algorithm also uses the optimal estimation method (OEM) to make error analysis more accessible and robust. The estimated retrieval errors range from 1.5 to 2 DU in September and 2 DU in December, with a constant degree of freedom of the signal (DFS) of 1 in September and a variable DFS of 1.25 to 1.4 in December throughout the day, depending on solar zenith angle (SZA). To assess the performance of the GEMS algorithm, the hourly GEMS total ozone was compared with ground-based measurements from Pandora instruments and other satellite platforms from TROPOMI (TROPOspheric Monitoring Instrument) and OMPS (Ozone Mapping and Profiler Suite Nadir Mapper). GEMS has a high correlation of 0.97 and small RMSE values compared to Pandora TCO at Busan and Seoul in South Korea. It is notable that despite exhibiting seasonal dependence in the mean bias of GEMS with Pandora, GEMS is capable of observing daily variations in ozone that are highly consistent with Pandora measurements, with a bias of approximately 1 %. The comparison of GEMS TCO data with TROPOMI and OMPS TCO data shows a high correlation of 0.99 and low RMSE compared to TROPOMI and OMPS TCO data, but the data have a negative bias of −2.38 % and −2.17 %, with standard deviations of 1.33 % and 1.57 %, respectively. Similar to OMPS, the influence of SO2 from volcanic eruptions is not properly removed in some regions, leading to GEMS overestimating TCO in those areas. The mean biases of GEMS TCO data with TROPOMI and OMPS TCO are within ±1 % at low latitudes but become negative at midlatitudes, with an increasingly negative dependence on latitude. Furthermore, this dependence becomes more prominent from summer to winter. The empirical correction applied to the GEMS irradiance data improves the dependence of the mean bias on season and latitude, but a consistent bias still remains, and a marginal positive trend was observed in December. Therefore, further investigation into correction methods is needed. The results are a meaningful scientific advance by providing the first validated, hourly UV ozone retrievals from a satellite in geostationary orbit. This experience can be used to advance research with future geostationary environmental satellite missions, including the incoming TEMPO (Tropospheric Emissions: Monitoring of Pollution) and Sentinel-4.

Thermoelectromagnetic SmallSat propellant positioning

Low gravity fluid management is key to a variety of spaceflight applications, from life support aboard the International Space Station to propellant management in satellite tanks. Capillary devices are traditionally employed to position fluids in a microgravity environment, but they fail to induce effective phase separation in the conformal tank geometries and saturated two-phase propellants adopted in modern CubeSat propulsion. In order to meet the stringent requirements of future small satellite missions, this paper explores the application of capillary, magnetic positive positioning, thermal, and dielectrophoretic fluid management devices to conformal propellant tanks. The electromagnetic and capillary devices rely upon body and surface forces, respectively, while the proposed thermal approach exploits phase change in saturated liquid–gas mixtures to position the fluid. Each concept is evaluated based on its ability to reorient the propellant and maintain its position during operation, as well as the resulting volume, mass, and power requirements. Ultimately, thermomagnetic and thermodielectrophoretic devices are deemed to be best suited for the case under analysis because of their low size, weight, and power demand in combination with their reliability and performance. These new systems offer a novel and robust solution to small satellite propellant management, a key enabling technology for the future of maneuverable CubeSats.

Constraining Plant Hydraulics With Microwave Radiometry in a Land Surface Model: Impacts of Temporal Resolution

AbstractVegetation water content (VWC) plays a key role in transpiration, plant mortality, and wildfire risk. Although land surface models now often contain plant hydraulics schemes, there are few direct VWC measurements to constrain these models at global scale. One proposed solution to this data gap is passive microwave remote sensing, which is sensitive to temporal changes in VWC. Here, we test that approach by using synthetic microwave observations to constrain VWC and surface soil moisture within the Climate Modeling Alliance Land model. We further investigate the possible utility of sub‐daily observations of VWC, which could be obtained through a satellite in geostationary orbit or combinations of multiple satellites. These high‐temporal‐resolution observations could allow for improved determination of ecosystem parameters, carbon and water fluxes, and subsurface hydraulics, relative to the currently available twice‐daily sun‐synchronous observational patterns. We find that incorporating observations at four different times in the diurnal cycle (such as could be available from two sun‐synchronous satellites) provides a significantly better constraint on water and carbon fluxes than twice‐daily observations do. For example, the root mean square error of projected evapotranspiration and gross primary productivity during drought periods was reduced by approximately 40%, when using four‐times‐daily relative to twice‐daily observations. Adding hourly observations of the entire diurnal cycle did not further improve the inferred parameters and fluxes. Our comparison of observational strategies may be informative in the design of future satellite missions to study plant hydraulics, as well as when using existing remotely sensed data to study vegetation water stress response.

Modeling forest canopy surface retrievals using very high-resolution spaceborne stereogrammetry: (II) optimizing acquisition configurations

The optimal configurations for very high-resolution (VHR, <2 m) spaceborne imagery collection to support stereogrammetry over complex forested terrain remain uncertain. We conducted a comprehensive sensitivity study of digital surface models (DSMs) derived from thousands of simulated along-track VHR stereopairs over two lidar-reconstructed forested scenes of closed and open canopies using the discrete anisotropic radiative transfer (DART) model. We evaluated the influence of convergence angle (CA), solar illumination, and image resolution on the derived DSM accuracy relative to the reference DSM and digital terrain model (DTM) products from airborne lidar data. Our results confirmed that the CA is the most critical acquisition parameter for DSM accuracy. Compared to the frequently used CA of ∼35∘ for along-track stereopair acquisitions by WorldView satellites, a smaller CA can provide better accuracy for forest canopy shape estimation by reducing occlusions and mitigating radiometric variance caused by the bidirectional reflectance characteristics of vegetation. For forested scenes over relatively flat terrain, oblique solar zenith angles (50−70∘) yielded more consistent DSMs with better accuracy, whereas images with a hotspot configuration generated elevations that were closer to the DTM. Image pairs with smaller ground sample distance (GSD) improved the DSM accuracy, and combinations of small (nadir) and large (off-nadir) GSDs had accuracy between those derived from homogeneous GSDs. These simulation results suggest that available global archives of DSMs from VHR stereo imagery collected under a range of acquisition configurations will yield inconsistent estimates of canopy surfaces. This study also provides a benchmark dataset and configuration guide for 1) selecting existing data to retrieve the forest canopy surface shape, and 2) defining requirements for future satellite missions to characterize the forest canopy surface using stereogrammetry.

Assessing potential of the Geostationary Littoral Imaging and Monitoring Radiometer (GLIMR) for water quality monitoring across the coastal United States

The Geostationary Littoral Imaging and Monitoring Radiometer (GLIMR) will provide unique high temporal frequency observations of the United States coastal waters to quantify processes that vary on short temporal and spatial scales. The frequency and coverage of observations from geostationary orbit will improve quantification and reduce uncertainty in tracking water quality events such as harmful algal blooms and oil spills. This study looks at the potential for GLIMR to complement existing satellite platforms from its unique geostationary viewpoint for water quality and oil spill monitoring with a focus on temporal and spatial resolution aspects. Water quality measures derived from satellite imagery, such as harmful algal blooms, thick oil, and oil emulsions are observable with glint <0.005 sr−1, while oil films require glint >10−5 sr−1. Daily imaging hours range from 6 to 12 h for water quality measures, and 0 to 6 h for oil film applications throughout the year as defined by sun glint strength. Spatial pixel resolution is 300 m at nadir and median pixel resolution was 391 m across the entire field of regard, with higher spatial resolution across all spectral bands in the Gulf of Mexico than existing satellites, such as MODIS and VIIRS, used for oil spill surveillance reports. The potential for beneficial glint use in oil film detection and quality flagging for other water quality parameters was greatest at lower latitudes and changed location throughout the day from the West and East Coasts of the United States. GLIMR scan times can change from the planned ocean color default of 0.763 s depending on the signal-to-noise ratio application requirement and can match existing and future satellite mission regions of interest to leverage multi-mission observations.

Increasing the Observability of Near Inertial Oscillations by a Future ODYSEA Satellite Mission

Increasing the Observability of Near Inertial Oscillations by a Future ODYSEA Satellite Mission

First Nighttime Light Spectra by Satellite—By EnMAP

For the first time, nighttime VIS/NIR—SWIR (visible and near-infrared—shortwave infrared) spectra from a satellite mission have been analyzed using the EnMAP (Environmental Mapping and Analysis Program) high-resolution imaging spectrometer. This article focuses on the spectral characteristics. Firstly, we checked the spectral calibration of EnMAP using sodium light emissions. Here, By applying a newly devised general method, we estimated shifts of +0.3nm for VIS/NIR and −0.2nm for SWIR; the uncertainties were found to be within the range of [−0.4nm,+0.2nm] for VIS/NIR and [−1.2nm,+1.0nm] for SWIR. These results emphasize the high accuracy of the spectral calibration of EnMAP and illustrate the feasibility of methods based on nighttime Earth observations for the spectral calibration of future nighttime satellite missions. Secondly, by employing a straightforward general method, we identified the dominant lighting types and thermal emissions in Las Vegas, Nevada, USA, on a per-pixel basis, and we considered the consistency of the outcomes. The identification and mapping of different types of LED (light-emitting diode) illuminations were achieved—with 75% of the identified dominant lighting types identified in VIS/NIR—as well as high- and low-pressure sodium and metal halide, which made up 22% of the identified dominant lighting types in VIS/NIR and 29% in SWIR and other illumination sources, as well as high temperatures, where 33% of the identified dominant emission types in SWIR were achieved from space using EnMAP due to the elevated illumination levels in the observed location. These results illustrate the feasibility of the precise identification of lighting types and thermal emissions based on nighttime high-resolution imaging spectroscopy satellite products; moreover, they support the specification of spectral characteristics for upcoming nighttime missions.

Correcting Gain Drift in TES Detectors for Future X-Ray Satellite Missions

Changes in the operating environment of transition-edge sensor (TES) microcalorimeters can cause variations in the detector gain function over time. If not corrected, this can degrade the spectral resolution, and cause systematic errors in the knowledge of the absolute energy. The non-linear nature of the TES energy scale function and the potential for multiple, simultaneous sources of drift can make effective corrections extremely challenging. Satellite instruments typically employ an on-board calibration source to provide known reference X-ray lines. This allows real-time monitoring of the detector gain stability and provides information that can be used to correct for drifts. Here we discuss progress towards demonstrating that the energy scale requirements can be met for future instruments such as Athena X-IFU. We present measurements (from ∼ 1-12 keV) on ∼ 200 pixels in a prototype X-IFU array. We use a non-linear drift correction algorithm that uses two fiducial calibration lines (5.4 keV and 8.0 keV) to track gain and interpolate a new, corrected gain between a set of three pre-calibrated gain functions that span the anticipated range of induced drifts. We demonstrate this algorithm is effective at correcting the full gain scale in the presence of multiple sources of environmental drift.

Development and Test of High-Temperature Superconductor Harness for Cryogenic Instruments on Satellites

Extremely sensitive x-ray or infrared detectors that have to be cooled to temperatures well below 1 Kelvin will be used in a number of future satellite missions within ESA's Cosmic Vision and Voyage 2050 program, e.g. ATHENA. To provide sufficient cooling power at different temperature levels, complex cryogenic chains are being developed with different types of coolers. Adiabatic demagnetization refrigerators (ADRs) can be used to reach the lowest temperatures in the range of 50 mK – 100 mK. Due to the limited electrical power available on satellites and other space constraints, superconducting ADR magnets are usually operated with dc currents of only a few Amps. Despite the low currents, the current leads connecting the power supply at a higher temperature stage to the magnet at the cold stage contribute with a high heat load to the limited thermal budget. In this paper we present the design, manufacturing and first tests of a high-temperature superconducting current lead harness which is designed to operate up to a temperature as high as 85 K with a nominal current of 2 A and a maximum current of 5 A. Design choices based on characterization of laser-cut <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RE</i> BCO tapes from different suppliers, characterization of structure materials and on thermal and mechanical simulations are presented. First test results for the assembled harness are discussed. They include current and bending tests, as well as insulation resistance tests.

Analysis of PlanetScope Dove Digital Surface Model Accuracy Using Geometrically Simulated Images

Many objectives in geoscience and engineering require Earth surface elevations at greater temporospatial resolution and coverage than are currently available. This may be achieved with stereo imagery from large constellations of “small sats”, such as PlanetScope Doves. Obtaining Digital Surface Models (DSMs) of sufficient quality from these images is challenging due to their lower resolution and weaker stereo geometry relative to stereo mode satellites such as WorldView. The quality can be improved by utilizing their much larger numbers of repeat images, but this requires effective stereopair selection. To determine the stereo geometries required for obtaining quality DSMs from PlanetScope Dove imagery, we apply a new methodology for generating simulated stereo images of varying geometries using adjusted orientation parameters obtained by a self-calibrating bundle adjustment and validated by comparing the resulting rigorous sensor and rational function models. The accuracies of simulated stereo and multi-pair DSMs are then assessed through comparison to a reference DSM, providing the relationship between specific imaging geometries and DSM quality. Our results provide a basis for automated stereo imagery selection to enable large-scale DSM production from PlanetScope Dove imagery. Our methodology can be applied to other sources of stereo imagery and designing future satellite missions. In the future, we will further develop multi-pair matching algorithms for generating DSMs with Dove Classic images to improve both accuracy and quality that are otherwise limited by the weak stereo geometry of single stereo pairs.

Choice of Solar Spectral Irradiance Model for Current and Future Remote Sensing Satellite Missions

The accuracy of surface reflectance estimation for satellite sensors using radiance-based calibrations can depend significantly on the choice of solar spectral irradiance (or solar spectrum) model used for atmospheric correction. Selecting an accurate solar spectrum model is also important for radiance-based sensor calibration and estimation of atmospheric parameters from irradiance observations. Previous research showed that Landsat 8 could be used to evaluate the quality of solar spectrum models. This paper applies the analysis using five previously evaluated and three more recent solar spectrum models using both Landsat 8 (OLI) and Landsat 9 (OLI2). The study was further extended down to 10 nm resolution and a wavelength range from Ultraviolet A (UVA) to shortwave infrared (SWIR) (370–2480 nm) using inversion of field irradiance measurements. The results using OLI and OLI2 as well as the inversion of irradiance measurements were that the more recent Chance and Kurucz (SA2010), Meftah (SOLAR-ISS) and Coddington (TSIS-1) models performed better than all of the previous models. The results were illustrated by simulating dark and bright surface reflectance signatures obtained by atmospheric correction with the different solar spectrum models. The results showed that if the SA2010 model is assumed to be the “true” solar irradiance, using the TSIS-1 or the SOLAR-ISS model will not significantly change the estimated ground reflectance. The other models differ (some to a large extent) in varying wavelength areas.

Comparison of Soil Moisture Content Retrieval Models Utilizing Hyperspectral Goniometer Data and Hyperspectral Imagery From an Unmanned Aerial System

AbstractTo understand surface biogeophysical processes, accurately evaluating the geographical and temporal fluctuations of soil moisture is crucial. It is well known that the surface soil moisture content (SMC) affects soil reflectance at all solar spectrum wavelengths. Therefore, future satellite missions, such as the NASA Surface Biology and Geology mission, will be essential for mapping and monitoring global soil moisture changes. Our study compares two widely used moisture retrieval models: the multilayer radiative transfer model of soil reflectance (MARMIT) and the soil water parametric (SWAP)‐Hapke model. We evaluated the SMC retrieval accuracy of these models using unmanned aerial systems (UAS) hyperspectral imagery and goniometer hyperspectral data. Laboratory analysis employed hyperspectral goniometer data of sediment samples from four locations reflecting diverse environments, while field validation used hyperspectral UAS imaging and coordinated ground truth collected in 2018 and 2019 from a barrier island beach at the Virginia Coast Reserve Long‐Term Ecological Research site. The (SWAP)‐Hapke model achieves comparable accuracy to MARMIT using laboratory hyperspectral data but is less accurate when applied to UAS hyperspectral imagery than the MARMIT model. We proposed a modified version of the (SWAP)‐Hapke model, which achieves better results than MARMIT when applied to laboratory spectral measurements; however, MARMIT's performance is still more accurate when applied to UAS imagery. These results are likely due to differences in the models' descriptions of multiply‐scattered light and MARMIT's more detailed description of air‐water interactions.

Knowledge Gaps and Impact of Future Satellite Missions to Facilitate Monitoring of Changes in the Arctic Ocean

Polar-orbiting satellite observations are of fundamental importance to explore the main scientific challenges in the Arctic Ocean, as they provide information on bio-geo-physical variables with a denser spatial and temporal coverage than in-situ instruments in such a harsh and inaccessible environment. However, they are limited by the lack of coverage near the North Pole (Polar gap), the polar night, and frequent cloud cover or haze over the ocean and sea ice, which prevent the use of optical satellite instruments, as well as by the limited availability of external validation data. The satellite sensors’ coverage and repeat cycles may also have limitations in properly identifying and resolving the dominant spatial and temporal scales of atmospheric, ocean, cryosphere and land variability and their interactive processes and feedback mechanisms. In this paper, we provide a state of the art of contribution of satellite observations to the understanding of the polar environment and climate scientific challenges tackled within the Arktalas Hoavva project funded by the European Space Agency. We identify the current limitations to the wider use of polar orbiting remote sensing data, as well as the observational gaps of the existing satellite missions. A comprehensive overview of all satellite missions and applications is given provided with a primary focus on the European satellites. Finally, we assess the expected capability of the approved future satellite missions to answer today’s scientific challenges in the Arctic Ocean.

Aeolus winds impact on volcanic ash early warning systems for aviation

Forecasting volcanic ash atmospheric pathways is of utmost importance for aviation. Volcanic ash can interfere with aircraft navigational instruments and can damage engine parts. Early warning systems, activated after volcanic eruptions can alleviate the impacts on aviation by providing forecasts of the volcanic ash plume dispersion. The quality of these short-term forecasts is subject to the accuracy of the meteorological wind fields used for the initialization of regional models. Here, we use wind profiling data from the first high spectral resolution lidar in space, Aeolus, to examine the impact of measured wind fields on regional NWP and subsequent volcanic ash dispersion forecasts, focusing on the case of Etna’s eruption on March 2021. The results from this case study demonstrate a significant improvement of the volcanic ash simulation when using Aeolus-assimilated meteorological fields, with differences in wind speed reaching up to 8 m/s when compared to the control run. When comparing the volcanic ash forecast profiles with downwind surface-based aerosol lidar observations, the modeled field is consistent with the measurements only when Aeolus winds are assimilated. This result clearly demonstrates the potential of Aeolus and highlights the necessity of future wind profiling satellite missions for improving volcanic ash forecasting and hence aviation safety.

On‐board energy scheduling optimization algorithm for nanosatellites

SummaryThis work proposes a real‐time and online energy scheduling optimization algorithm for nanosatellites operating with a direct energy transfer (DET) architecture. The goal of the algorithm is to optimize energy utilization by maximizing energy harvesting, meeting task deadlines and priorities, and ensuring a minimum quality of service (QoS) for the system. The algorithm is composed of a modified perturb and observe algorithm to reach the best energy efficiency point of the solar panels, a task prioritization algorithm to guarantee their times and minimum QoS, and a backpack optimization problem to maximize the energy efficiency of the satellite. To demonstrate the effectiveness of the proposed algorithm, simulations of a nanosatellite operating in a given orbit, attitude, and thermal parameters were conducted and compared to other task scheduling strategies. The results showed that the proposed energy scheduling algorithm had the best performance in terms of energy balance and average power consumption, with an energy balance up to 16% higher compared to the other tested strategies. This demonstrates the ability of the proposed algorithm to optimize power consumption and energy utilization, as well as efficiently schedule tasks to maximize energy harvesting. The proposed energy scheduling optimization algorithm has the potential to be a useful tool for the design and optimization of future satellite missions and could potentially guide the design of electrical power systems for new CubeSat missions operating with a DET architecture. The algorithm's ability to optimize energy utilization and ensure a minimum QoS for the system could improve the overall efficiency and performance of the satellite.