Search Results (23)

As a result of progress in space technology, more scientific missions are benefiting from using CubeSats equipped with radiometers. CubeSat constellations are especially effective in overcoming obstacles in cost, weight, and power. However, these benefits have certain significant downsides, including the difficulty in calibration due to the increased sensitivity of instruments to ambient conditions. Such limitations prevent conventional calibration methods from being reliably applied to CubeSat radiometers. A novel, constellation-level calibration framework called “Adaptive Calibration of CubeSat Radiometer Constellations (ACCURACy)” is being developed to address this issue. ACCURACy, in its current version, uses telemetry data obtained from thermistors in each CubeSat to cluster constellation members into time-adaptive groups of radiometers in similar states. Each radiometer is assigned membership to a cluster and this status is updated as in-orbit measurements shift in the clustering model. This paper introduces the ACCURACy framework, discusses its theoretical background, and presents a MATLAB prototype with performance and uncertainty analyses using synthetic radiometer data in comparison with traditional radiometer calibration methods. Full article

Landsat data correction using the Land Surface Reflectance Code (LaSRC) has been proposed as the basis for the atmospheric correction of smallsats. While atmospheric correction can enhance smallsat data, the Landsat/LaSRC pathway delays output and may constrain accuracy and utility. The alternative, the Closed-form Method for Atmospheric Correction (CMAC), developed for smallsat application, provides surface reflectance derived solely from scene statistics. In a prior paper, CMAC closely agreed with LaSRC software for correction of the four VNIR bands of Landsat-8/9 images for conditions of low to moderate atmospheric effect over quasi-invariant warehouse-industrial targets. Those results were accepted as surrogate surface reflectance to support analysis of CMAC and LaSRC reliability for surface reflectance retrieval in two contrasting environments: shortgrass prairie and barren desert. Reliability was defined and tested through a null hypothesis: the same top-of-atmosphere reflectance under the same atmospheric condition will provide the same estimate of surface reflectance. Evaluated against the prior surrogate surface reflectance, the results found decreasing error with increasing wavelength for both methods. From 58 comparisons across the four bands, the LaSRC average absolute error ranged from 0.59% (NIR) to 50.30% (blue). CMAC provided reliable results: error was well constrained from 0.01% (NIR) to 0.98% (blue). Full article

This research aims to contribute to the development of the Eco-LeanSat concept by focusing on a sustainable approach to satellite manufacturing and the repurposing of remaining satellite capabilities after failure. Despite satellites no longer being suitable for their original purposes, these remaining capabilities can find new applications. The study begins by identifying relevant innovative eco-design applications. Subsequently, it examines sustainability within the satellite lifecycle supply chain, categorizing it into four methods: (1) active debris removal, (2) transport logistics, (3) mission extension, and (4) repair and construction. Aligned with emerging trends in space activities, the study also considers future developments to maximize satellites’ potential to provide new services. Additionally, the research includes a description of a potential lean manufacturing process that encompasses logistic chains to support the development of a more sustainable space economy. Finally, the study concludes with a technological survey tracing the evolution of the development of the SmallSat and CubeSat platforms that identifies relevant innovative designs for a sustainable space environment. Full article

Closed-form Method for Atmospheric Correction (CMAC) is software that overcomes radiative transfer method problems for smallsat surface reflectance retrieval: unknown sensor radiance responses because onboard monitors are omitted to conserve size/weight, and ancillary data availability that delays processing by days. CMAC requires neither and retrieves surface reflectance in near real time, first mapping the atmospheric effect across the image as an index (Atm-I) from scene statistics, then reversing these effects with a closed-form linear model that has precedence in the literature. Five consistent-reflectance area-of-interest targets on thirty-one low-to-moderate Atm-I images were processed by CMAC and LaSRC. CMAC retrievals accurately matched LaSRC with nearly identical error profiles. CMAC and LaSRC output for paired images of low and high Atm-I were then compared for three additional consistent-reflectance area-of-interest targets. Three indices were calculated from the extracted reflectance: NDVI calculated with red (standard) and substitutions with blue and green. A null hypothesis for competent retrieval would show no difference. The pooled error for the three indices (n = 9) was 0–3% for CMAC, 6–20% for LaSRC, and 13–38% for uncorrected top-of-atmosphere results, thus demonstrating both the value of atmospheric correction and, especially, the stability of CMAC for machine analysis and AI application under increasing Atm-I from climate change-driven wildfires. Full article

This study introduces a prototype end-to-end Simulator software tool for simulating two-dimensional satellite multispectral imagery for a variety of satellite instrument models in aquatic environments. Using case studies, the impact of variable sensor configurations on the performance of value-added products for challenging applications, such as coral reefs and cyanobacterial algal blooms, is assessed. This demonstrates how decisions regarding satellite sensor design, driven by cost constraints, directly influence the quality of value-added remote sensing products. Furthermore, the Simulator is used to identify situations where retrieval algorithms require further parameterization before application to unsimulated satellite data, where error sources cannot always be identified or isolated. The application of the Simulator can verify whether a given instrument design meets the performance requirements of end-users before build and launch, critically allowing for the justification of the cost and specifications for planned and future sensors. It is hoped that the Simulator will enable engineers and scientists to understand important design trade-offs in phase 0/A studies easily, quickly, reliably, and accurately in future Earth observation satellites and systems. Full article

High-cadence Earth observation smallsat images offer potential for near real-time global reconnaissance of all sunlit cloud-free locations. However, these data must be corrected to remove light-transmission effects from variable atmospheric aerosol that degrade image interpretability. Although existing methods may work, they require ancillary data that delays image output, impacting their most valuable applications: intelligence, surveillance, and reconnaissance. Closed-form Method for Atmospheric Correction (CMAC) is based on observed atmospheric effects that brighten dark reflectance while darkening bright reflectance. Using only scene statistics in near real-time, CMAC first maps atmospheric effects across each image, then uses the resulting grayscale to reverse the effects to deliver spatially correct surface reflectance for each pixel. CMAC was developed using the European Space Agency’s Sentinel-2 imagery. After a rapid calibration that customizes the method for each imaging optical smallsat, CMAC can be applied to atmospherically correct visible through near-infrared bands. To assess CMAC functionality against user-applied state-of-the-art software, Sen2Cor, extensive tests were made of atmospheric correction performance across dark to bright reflectance under a wide range of atmospheric aerosol on multiple images in seven locations. CMAC corrected images faster, with greater accuracy and precision over a range of atmospheric effects more than twice that of Sen2Cor. Full article

This paper proposes a novel approach for hydrometeor classification using passive microwave observations. The use of passive measurements for this purpose has not been extensively explored, despite being available for over four decades. We utilize the Micro-Wave Humidity Sounder-2 (MWHS-2) to relate microwave brightness temperatures to hydrometeor types derived from the global precipitation measurement’s (GPM) dual-frequency precipitation radar (DPR), which are classified into liquid, mixed, and ice phases. To achieve this, we utilize a convolutional neural network model with an attention mechanism that learns feature representations of MWHS-2 observations from spatial and temporal dimensions. The proposed algorithm classified hydrometeors with 84.7% accuracy using testing data and captured the geographical characteristics of hydrometeor types well in most areas, especially for frozen precipitation. We then evaluated our results by comparing predictions from a different year against DPR retrievals seasonally and globally. Our global annual cycles of precipitation occurrences largely agreed with DPR retrievals with biases being 8.4%, −11.8%, and 3.4%, respectively. Our approach provides a promising direction for utilizing passive microwave observations and deep-learning techniques in hydrometeor classification, with potential applications in the time-resolved observations of precipitation structure and storm intensity with a constellation of smallsats (TROPICS) algorithm development. Full article

High spatiotemporal flood monitoring is critical for flood control, mitigation, and management purposes in areas where tectonic and geological events significantly exacerbate flood disasters. For example, the rapid lake shrinkage resulting from the transformations of enclosed seas into lakes by the rapid land movement in the collision zone dramatically increases the flood risks in Indonesia, which requires frequent and detailed monitoring and assessment. This study primarily quantified the detailed flood disasters associated with the rapid lake shrinkage in Gorontalo Regency in Gorontalo Province, Indonesia using high spatiotemporal monitoring with a combination of PlanetScope smallsat constellations, Sentinel-1, and surface water datasets. Based on the findings that indicated its volume, distribution, pace, and pattern, the flood event that occurred in Gorontalo in November 2022 was demonstrated within a short interval of 2–12 days. The results also indicate both direct and indirect floodwater overflow from different water resources. Combining these results with the surface water occurrences from 1984 to 2021, our findings reveal the historical major flood-prone areas associated with the rapid lake shrinkage. These findings are expected to aid in the timely high spatiotemporal monitoring of rapid environmental change-induced flood disasters, even in tropical regions with high cloud coverage. Furthermore, these are also expected to be integrated into the flood hazard mitigation and management strategies associated with local-specific tectonic and geological systems. Full article

Potentially toxic elements (PTEs) from natural and anthropogenic activities threaten the environment and human health. The associations of PTEs with natural hazards can be powerful and prominent mechanisms to release PTEs, considerably hastening their multiple contaminations and widespread distribution. This study primarily aimed to investigate the enhanced potential distribution of PTE contaminations (arsenic, lead, and mercury) from coexisting gold mining operations combined with massive riverbank erosion in Indonesia from 2002 to 2022, where soil and water are highly contaminated naturally, using PlanetScope smallsat constellations, Google Earth imagery, and hydrographic datasets. According to the findings, increased barren extents were found because of mining deposits and road network developments. Enhanced natural and anthropogenic PTE runoffs would be transported across two different sub-basins, affecting broader parts of the Bone River. Between 2002 and 2022, 139.3% of river expansion was identified, eroding a maximum of 3,436,139.4 m³ of contaminated soil. Particularly land surfaces were repeatedly transformed from rivers to agricultural lands in the low Bone River, possibly contaminated by fertilizer spills. The combination of PTE potentials from different sources would further exacerbate the contamination level at an estuary. These findings are expected to aid in the timely monitoring of and assuming volumes, rates, and distribution of PTEs from various natural and anthropogenic activities and alert PTE contamination risks to ecosystems and human health. Future work in this area should aim to investigate contamination levels at the estuary, where contaminated materials from both natural and anthropogenic activities are accumulated. Full article

Using large constellations of smallsats, mission designers can improve sampling density and coverage. We develop performance metrics that characterize key sampling properties for applications in numerical weather prediction and optimize orbit design parameters of the constellation with respect to those metrics. Orbits are defined by a set of Keplerian elements, and the relationship between those elements and the spatial and temporal coverage metrics are examined in order to maximize global and zonal (latitude-dependent) coverage. Additional optimization is performed by dividing a constellation into multiple orbit planes. An iterative method can be applied to this design process to compare the performance of current and previous designs. The main objective of this work is the design of optimized configurations of satellites in low Earth orbiting constellations to maximize the spatial and temporal sampling and coverage provided by its sensors. The key innovations developed are a new cost function which measures the temporal sampling properties of a satellite constellation, and the use of it together with existing cost functions for spatial sampling to design satellite constellations that optimize performance with respect to both performance metrics. Full article

The population of satellites in Low Earth Orbit is predicted to growth exponentially in the next decade due to the proliferation of small-sat constellations. Consequently, the probability of collision is expected to increase dramatically, possibly leading to a potential Kessler syndrome situation. It is therefore necessary to strengthen all the technologies required for collision avoidance and end-of-life disposal of new satellites, together with active debris removal of current and potential future dead satellites. Both situations require the lowering of the altitude of a satellite up to re-entry. In this paper several de-orbiting technologies are evaluated: natural decay, chemical propulsion (solid and liquid), electric propulsion, drag sail, electrodynamic tether, and combinations of the previous ones. The comparison considers the initial altitude, system mass, de-orbiting time, collision probability during descent, reliability, and technological limits. Differences between active debris removal and satellite end-of-life self-disposal are taken into account. Moreover, the different types of re-entry, controlled vs. non-controlled, expendable vs. reusable system, demisable vs. non-demisable system are also discussed. Finally, the possibility to operate the satellite in Very Low Earth Orbits with a propulsion system for drag compensation and passive re-entry at end of life is investigated. Full article

On 1 April 2022, the AlfaCrux CubeSat was launched by the Falcon 9 Transporter-4 mission, the fourth SpaceX dedicated smallsat rideshare program mission, from Space Launch Complex 40 at Cape Canaveral Space Force Station in Florida into a Sun-synchronous orbit at 500 km. AlfaCrux is an amateur radio and educational mission to provide learning and scientific benefits in the context of small satellite missions. It is an opportunity for theoretical and practical learning about the technical management, systems design, communication, orbital mechanics, development, integration, and operation of small satellites. The AlfaCrux payload, a software-defined radio hardware, is responsible for two main services, which are a digital packet repeater and a store-and-forward system. In the ground segment, a cloud-computing-based command and control station has been developed, together with an open access online platform to access and visualize the main information of the AlfaCrux telemetry and user data and experiments. It also becomes an in-orbit database reference to be used for different studies concerned with, for instance, radio propagation, attitude reconstruction, data-driven calibration algorithms for satellite sensors, among others. In this context, this paper describes the AlfaCrux mission, its main subsystems, and the achievements obtained in the early orbit phase. Scientific and engineering assessments conducted with the spacecraft operations to tackle unexpected behaviors in the ground station and also to better understand the space environment are also presented and discussed. Full article

Assembly, Integration, and Verification/Testing (AIV or AIT) is a standardized guideline for projects to ensure consistency throughout spacecraft development phases. The goal of establishing such a guideline is to assist in planning and executing a successful mission. While AIV campaigns can help reduce risk, they can also take years to complete and be prohibitively costly for smaller new space programs, such as university CubeSat teams. This manuscript outlines a strategic approach to the traditional space industry AIV campaign through demonstration with a 6U CubeSat mission. The HYPerspectral Smallsat for Ocean observation (HYPSO-1) mission was developed by the Norwegian University of Science and Technology’s (NTNU) SmallSatellite Laboratory in conjunction with NanoAvionics (the platform provider). The approach retains critical milestones of traditional AIV, outlines tailored testing procedures for the custom-built hyperspectral imager, and provides suggestions for faster development. A critical discussion of de-risking and design-driving decisions, such as imager configuration and machining custom parts, highlights the consequences that helped, or alternatively hindered, development timelines. This AIV approach has proven key for HYPSO-1’s success, defining further development within the lab (e.g., already with the second-generation, HYPSO-2), and can be scaled to other small spacecraft programs throughout the new space industry. Full article

Increasing the density of Global Navigation Satellite System radio occultation (RO) with commercial Smallsats and the next generation COSMIC-2 constellation is expected to improve analyses of the state of atmosphere, which is essential for numerical weather prediction. High vertical resolution RO profiles could be useful to observe atmospheric rivers (ARs) over the ocean, which transport water vapor in shallow, elongated corridors that frequently impact the west coasts of continents. The multi-year AR Reconnaissance campaign has extensively sampled ARs over the northeastern Pacific with dropsondes, providing an invaluable dataset to evaluate the reliability of RO retrievals. These dropsondes, and a reanalysis product that assimilates them, are compared to three RO datasets: (1) established operational missions, (2) COSMIC-2, and (3) the commercial Spire constellation. Each RO dataset has biases relative to reanalyses of less than 0.5% N in the upper troposphere and negative biases in the lower troposphere. Direct colocations with dropsondes indicate that vertical refractivity gradients present within ARs may be contributing to negative biases at higher altitudes inside than outside ARs, where the greatest variability and vertical gradients are at the well-defined boundary layer top. Observations from Spire are overly smooth, affecting the ability to resolve the low-level structure of an AR. Surprisingly, the depth of penetration into the lower troposphere is greater inside an AR than outside for all datasets. The results indicate that the observation errors used for assimilation of RO within ARs should consider the height dependent biases that are associated with the structure of the atmosphere. Full article

Gold mining is a significant strategic sector for local, regional, and national economies. The rapid development of coexisting camp-type artisanal and small-scale gold mining (C-ASGM) and large-scale mining (LSM) accelerates the environmental and health risks associated with mercury pollution; however, transformations of coexisting sites have not been well quantified. This study used remote sensing (the PlanetScope smallsat constellations systems) to investigate the development of coexisting C-ASGM and LSM sites in Gorontalo, Indonesia, from 2019 to 2022. The results show a positive increase in the extent of barren land across all study zones, resulting from a road network construction connecting the southern port to major mining sites. Notably, greater landcover transformations in the C-ASGM sites after 2020 were attributed to the dumping of underground soils excavated using a shaft-mining method. The findings of this study expand our understanding of the rapid development of coexisting mining operations and quantify significant mining-induced environmental changes. These findings are anticipated to assist in timely monitoring and identification of development areas, rates, and volumes, together with the existing C-AGSM’s reactions associated with LSM’s massive developments. This also helps to detect possible local-level socioenvironmental impacts from massive land shape changes, leading to human disasters, including landslides and floods. Full article