Improved Orbital Propagator Integrated with SGP4 and Machine Learning

The current industry standard orbital propagator, the Simplified General Perturbation Model-4 (SPG4), relies completely on physics-based orbital mechanics, can only provide accurate orbital predictions ~12 hours in advance. We developed a novel hybrid model, combining the SGP4 baseline with two machine learning estimators, autoencoder and random forest, in order to reduce the errors of the SGP4 propagator. The sources of errors in SGP4 propagators come from incomplete perturbation calculations and low-order of series expansions. The time-series nature of these error patterns are modeled by our machine learning estimators and then are used to make corrections to the SGP4 propagation, which result in more accurate orbit predictions. We tested our hybrid model on 3 satellite objects with the corresponding TLE (Two Line Element) data. The improvement on orbit prediction achieved 20-30% over the future 30 days period. The limitation of this hybrid approach is the requirement of at least 3 years of historical TLE data for the machine learning models, but could be overcome by creating synthetic orbital data from a similar space object. This hybrid model can be easily packaged into a software tool for space mission operation planning and facilitate mission autonomy

Alluvial and fluvial fans on Saturn's moon Titan reveal processes, materials and regional geology

International audienceFans, landforms that record the storage and transport of sediment from uplands to depositional basins, are found on Saturn's moon Titan, a body of significantly different process rates and material compositions from Earth. Images obtained by the Cassini spacecraft's synthetic aperture radar reveal morphologies, roughness, textural patterns and other properties consistent with fan analogues on Earth also viewed by synthetic aperture radar. The observed fan characteristics on Titan reveal some regions of high relative relief and others with gentle slopes over hundreds of kilometres, exposing topographic variations and influences on fan formation. There is evidence for a range of particle sizes across proximal to distal fan regions, from c. 2 cm or more to fine-grained, which can provide details on sedimentary processes. Some features are best described as alluvial fans, which implies their proximity to high-relief source areas, while others are more likely to be fluvial fans, drawing from larger catchment areas and frequently characterized by more prolonged runoff events. The presence of fans corroborates the vast liquid storage capacity of the atmosphere and the resultant episodic behaviour. Fans join the growing list of landforms on Titan derived from atmospheric and fluvial processes similar to those on Earth, strengthening comparisons between these two planetary bodies

Alluvial Fans on Titan Reveal Atmosphere and Surface Interactions and Material Transport

Alluvial fans, important depositional systems that record how sediment is stored and moved on planetary surfaces, are found on the surface of Titan, a body of significantly different materials and process rates than Earth. As seen by Cassini’s Synthetic Aperture Radar (SAR) images at 350 m resolution, fans on Titan are found globally and are variable in size, shape and relationship to adjacent landforms. Their morphologies and SAR characteristics, which reveal roughness, textural patterns and other material properties, show similarities with fans in Death Valley seen by SAR and indicate there are regions of high relative relief locally, in the Ganesa, Xanadu and equatorial mountain belt regions. The Leilah Fluctus fans near Ganesa are ~30 km x 15 km, similar to the largest Death Valley fans, and revealing mountainous topography adjacent to plains. Others have gentle slopes over hundreds of kilometers, as in the high southern latitude lakes regions or the Mezzoramia southern midlatitudes, where a fan system is 200 km x 150 km, similar to the Qarn Alam fan emerging into the Rub al Khali in Oman. Additionally, there is evidence for a range of particle sizes, from relatively coarse (~2 cm or more) to fine, revealing long-term duration and variability in erosion by methane rainfall and transport. Some features have morphologies consistent with proximality to high-relief source areas and highly ephemeral runoff, while others appear to draw larger catchment areas and are perhaps characterized by more prolonged episodes of flow. The presence of many fans indicates the longevity of rainfall and erosion in Titan’s surface processes and reveals that sediment transport and the precipitation that drives it are strongly episodic. Alluvial fans join rivers, lakes, eroded mountains, sand dunes and dissolution features in the list of surface morphologies derived from atmospheric and fluvial processes similar to those on Earth, strengthening comparisons between the two planetary bodies

Alluvial and fluvial fans on Saturn’s moon Titan reveal processes, materials and regional geology

International audienceFans, landforms that record the storage and transport of sediment from uplands to depositional basins, are found on Saturn's moon Titan, a body of significantly different process rates and material compositions from Earth. Images obtained by the Cassini spacecraft's synthetic aperture radar reveal morphologies, roughness, textural patterns and other properties consistent with fan analogues on Earth also viewed by synthetic aperture radar. The observed fan characteristics on Titan reveal some regions of high relative relief and others with gentle slopes over hundreds of kilometres, exposing topographic variations and influences on fan formation. There is evidence for a range of particle sizes across proximal to distal fan regions, from c. 2 cm or more to fine-grained, which can provide details on sedimentary processes. Some features are best described as alluvial fans, which implies their proximity to high-relief source areas, while others are more likely to be fluvial fans, drawing from larger catchment areas and frequently characterized by more prolonged runoff events. The presence of fans corroborates the vast liquid storage capacity of the atmosphere and the resultant episodic behaviour. Fans join the growing list of landforms on Titan derived from atmospheric and fluvial processes similar to those on Earth, strengthening comparisons between these two planetary bodies

Alluvial and fluvial fans on Saturn’s moon Titan reveal processes, materials and regional geology

Fans, landforms that record the storage and transport of sediment from uplands to depositional basins, are found on Saturn's moon Titan, a body of significantly different process rates and material compositions from Earth. Images obtained by the Cassini spacecraft's synthetic aperture radar reveal morphologies, roughness, textural patterns and other properties consistent with fan analogues on Earth also viewed by synthetic aperture radar. The observed fan characteristics on Titan reveal some regions of high relative relief and others with gentle slopes over hundreds of kilometres, exposing topographic variations and influences on fan formation. There is evidence for a range of particle sizes across proximal to distal fan regions, from c. 2 cm or more to fine-grained, which can provide details on sedimentary processes. Some features are best described as alluvial fans, which implies their proximity to high-relief source areas, while others are more likely to be fluvial fans, drawing from larger catchment areas and frequently characterized by more prolonged runoff events. The presence of fans corroborates the vast liquid storage capacity of the atmosphere and the resultant episodic behaviour. Fans join the growing list of landforms on Titan derived from atmospheric and fluvial processes similar to those on Earth, strengthening comparisons between these two planetary bodies

Improving rural health care reduces illegal logging and conserves carbon in a tropical forest.

Tropical forest loss currently exceeds forest gain, leading to a net greenhouse gas emission that exacerbates global climate change. This has sparked scientific debate on how to achieve natural climate solutions. Central to this debate is whether sustainably managing forests and protected areas will deliver global climate mitigation benefits, while ensuring local peoples' health and well-being. Here, we evaluate the 10-y impact of a human-centered solution to achieve natural climate mitigation through reductions in illegal logging in rural Borneo: an intervention aimed at expanding health care access and use for communities living near a national park, with clinic discounts offsetting costs historically met through illegal logging. Conservation, education, and alternative livelihood programs were also offered. We hypothesized that this would lead to improved health and well-being, while also alleviating illegal logging activity within the protected forest. We estimated that 27.4 km2 of deforestation was averted in the national park over a decade (∼70% reduction in deforestation compared to a synthetic control, permuted P = 0.038). Concurrently, the intervention provided health care access to more than 28,400 unique patients, with clinic usage and patient visitation frequency highest in communities participating in the intervention. Finally, we observed a dose-response in forest change rate to intervention engagement (person-contacts with intervention activities) across communities bordering the park: The greatest logging reductions were adjacent to the most highly engaged villages. Results suggest that this community-derived solution simultaneously improved health care access for local and indigenous communities and sustainably conserved carbon stocks in a protected tropical forest

Deep Learning Segmentation of Satellite Imagery Identifies Aquatic Vegetation Associated with Snail Intermediate Hosts of Schistosomiasis in Senegal, Africa

Schistosomiasis is a debilitating parasitic disease of poverty that affects more than 200 million people worldwide, mostly in sub-Saharan Africa, and is clearly associated with the construction of dams and water resource management infrastructure in tropical and subtropical areas. Changes to hydrology and salinity linked to water infrastructure development may create conditions favorable to the aquatic vegetation that is suitable habitat for the intermediate snail hosts of schistosome parasites. With thousands of small and large water reservoirs, irrigation canals, and dams developed or under construction in Africa, it is crucial to accurately assess the spatial distribution of high-risk environments that are habitat for freshwater snail intermediate hosts of schistosomiasis in rapidly changing ecosystems. Yet, standard techniques for monitoring snails are labor-intensive, time-consuming, and provide information limited to the small areas that can be manually sampled. Consequently, in low-income countries where schistosomiasis control is most needed, there are formidable challenges to identifying potential transmission hotspots for targeted medical and environmental interventions. In this study, we developed a new framework to map the spatial distribution of suitable snail habitat across large spatial scales in the Senegal River Basin by integrating satellite data, high-definition, low-cost drone imagery, and an artificial intelligence (AI)-powered computer vision technique called semantic segmentation. A deep learning model (U-Net) was built to automatically analyze high-resolution satellite imagery to produce segmentation maps of aquatic vegetation, with a fast and robust generalized prediction that proved more accurate than a more commonly used random forest approach. Accurate and up-to-date knowledge of areas at highest risk for disease transmission can increase the effectiveness of control interventions by targeting habitat of disease-carrying snails. With the deployment of this new framework, local governments or health actors might better target environmental interventions to where and when they are most needed in an integrated effort to reach the goal of schistosomiasis elimination