Study of Mars geoscience orbiter and lunar geoscience orbiter, revision 1. Volume 1: Technical
The feasibility and efficiency of using an existing Earth orbiter to perform planetary missions was evaluated.
Brodsky, R. F.↗
SEARCH · Engineering Papers
Results for “geosciences”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Mars Geoscience Orbiter and Lunar Geoscience Orbiter
The feasibility of using the AE/DE Earth orbiting spacecraft design for the LGO and/or MGO missions was determined. Configurations were developed and subsystems analysis was carried out to optimize the suitability of the spacecraft to the missions. The primary conclusion is that the basic AE/DE spacecraft can readily be applied to the LGO mission with relatively minor, low risk modifications. The MGO mission poses a somewhat more complex problem, primarily due to the overall maneuvering hydrazine budget and power requirements of the sensors and their desired duty cycle. These considerations dictate a modification (scaling up) of the structure to support mission requirements.
Fuldner, W. V.↗
Coarse-to-fine Task-driven Inpainting for Geoscience Images
The processing and recognition of geoscience images have wide applications. Most of existing researches focus on understanding the high-quality geoscience images by assuming that all the images are clear. However, in many real-world cases, the geoscience images might contain occlusions during the image acquisition. This problem actually implies the image inpainting problem in computer vision and multimedia. As far as we know, all the existing image inpainting algorithms learn to repair the occluded regions for a better visualization quality, they are excellent for natural images but not good enough for geoscience images, and they never consider the following geoscience task when developing inpainting methods. Here, this paper aims to repair the occluded regions for a better geoscience task performance and advanced visualization quality simultaneously, without changing the current deployed deep learning based geoscience models. Because of the complex context of geoscience images, we propose a coarse-to-fine encoder-decoder network with the help of designed coarse-to-fine adversarial context discriminators to reconstruct the occluded image regions. Due to the limited data of geoscience images, we propose a MaskMix based data augmentation method, which augments inpainting masks instead of augmenting original images, to exploit the limited geoscience image data. The experimental results on three public geoscience datasets for remote sensing scene recognition, cross-view geolocation and semantic segmentation tasks respectively show the effectiveness and accuracy of the proposed method. The code is available at: https://github.com/HMS97/Task-driven-Inpainting.
97 MATHEMATICS AND COMPUTING↗
A qualitative study of marginalized students’ academic, physical, and social self-efficacy in a multiweek geoscience field program
Undergraduate summer field programs are valuable experiences that can foster or reduce students’ self-efficacy, an important factor in students’ success and retention in geoscience. Growing research findings show that science field experiences can be hostile and unwelcoming to students with marginalized identities, which may negatively impact their self-efficacy in geoscience, a discipline with a dearth of students from underrepresented, marginalized identities. We conducted an interpretive qualitative study examining how summer geoscience field programs affected two undergraduate, marginalized students’ self-efficacy. Adding to existing theoretical explanations of self-efficacy, we identified three types of self-efficacy impacted positively and negatively by geoscience field experiences: academic, physical, and social self-efficacy. We developed a nuanced understanding of the specific field experiences that influenced the ‘ups and downs’ of students’ self-efficacy and, ultimately, their intent in continuing to pursue a geoscience education or career. Despite negative experiences, including gender discrimination, crude sexual jokes, and a lack of belonging, the students described their intent to persist in geoscience. Here, our findings can assist geoscience educators (and others in field-based sciences) to consider experiences that support and hinder marginalized students’ self-efficacy. Also, our findings can guide efforts to improve geoscience field programs to create more inclusive environments.
case study↗
Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles
The sciences struggle with poor integration across disciplines, the absence of coordination within and across data generation and modeling activities, scarce or disconnected open data, and weaknesses of networks to engage diverse stakeholders within and beyond the scientific community. The American Geophysical Union (AGU) is divided into 25 sections intended to encompass the breadth of the geosciences. Here, we introduce a special collection of commentary articles spanning 19 AGU sections on the challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross-system transferability of science outcomes. This article summarizes the ICON principles; discusses the crowdsourced approach to creating the collection; and explores insights from across the articles. There were multiple common themes among the commentary articles, including the broad agreement that the benefits of using ICON principles outweigh the costs, but that using ICON principles has important risks that need to be understood and mitigated. It was also clear that the ICON principles are not monolithic or static, but should instead be considered a heuristic tool that can and should be modified to meet changing needs. As a whole, the collection is intended as a resource for scientists pursuing ICON science and represents an important inflection point in which the geosciences community has come together around ICON principles as a unified approach for improving how science is done across the geosciences and beyond.
58 GEOSCIENCES↗
Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles
Abstract The sciences struggle to integrate across disciplines, coordinate across data generation and modeling activities, produce connected open data, and build strong networks to engage stakeholders within and beyond the scientific community. The American Geophysical Union (AGU) is divided into 25 sections intended to encompass the breadth of the geosciences. Here, we introduce a special collection of commentary articles spanning 19 AGU sections on challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross‐system transferability of science outcomes. This article (a) summarizes the ICON principles; (b) discusses the crowdsourced approach to creating the collection; (c) explores insights from across the articles; and (d) proposes steps forward. There were common themes among the commentary articles, including broad agreement that the benefits of using ICON principles outweigh the costs, but that using ICON principles has important risks that need to be understood and mitigated. It was also clear that the ICON principles are not monolithic or static, but should instead be considered a heuristic tool that can and should be modified to meet changing needs. As a whole, the collection is intended as a resource for scientists pursuing ICON science and represents an important inflection point in which the geosciences community has come together to offer insights into ICON principles as a unified approach for improving how science is done across the geosciences and beyond.
Goldman, A. E.↗
Planetary geosciences, 1988
Research topics within the NASA Planetary Geosciences Program are presented. Activity in the fields of planetary geology, geophysics, materials, and geochemistry is covered. The investigator's current research efforts, the importance of that work in understanding a particular planetary geoscience problem, the context of that research, and the broader planetary geoscience effort is described. As an example, theoretical modelling of the stability of water ice within the Martian regolith, the applicability of that work to understanding Martian volatiles in general, and the geologic history of Mars is discussed.
Zuber, Maria T.↗
Field Camp for Astronauts: NASA's Geoscience Training Program for Planetary Exploration
Fifty years ago Apollo astronauts walked on the Moon to explore the geology and collect samples for Earth return. Several authors have discussed the strategic planning and training that enabled the Apollo successes, and assembled recommendations regarding today’s lunar science objectives and astronaut training required to achieve those science goals. Since the 1980s, geoscience training for astronauts focused on observing the Earth from orbit. Today, we are building a geoscience training program to support informed Earth observations as well as the exploration culture for future human missions to the Moon and Mars. Our team partnered with JSC’s crew training and astronaut offices to develop our 4-week geoscience program for the 2017 astronaut class. Because the astronauts have a variety of professional backgrounds, we provide a broad introduction to Earth and planetary sciences. But our prime focus is 2 weeks of intensive field work, a methodology introduced with the 2013 astronaut class. We completed the first half of the training – a field trip to observe hurricane deposits along Galveston Bay; keynotes by Apollo colleagues highlighting Apollo experiences; a tightly-integrated week of introductory geology in the classroom followed by a week of fieldwork in the Rio Grande del Norte National Monument. The classroom included interactive map exercises that allowed the students to progressively build a base map of the field area that they used as a starting point for their week-long mapping exercise. We divided the class into small mapping groups to conduct their observations, mapping and interpretation of the geology. In addition to learning geological field work, our field training provided the platform for practicing expeditionary leadership, a key skill set valued by NASA for astronaut crews. Next summer the capstone fieldwork for the 2017 astronauts will include both mapping and rock sampling. Throughout the mapping, the class will collect additional data to help inform field and sampling decisions using diagnostic field instruments that are being tested in analog settings for their operational efficacy for future planetary exploration.
Evans, Cynthia A.↗
Differentiable modelling to unify machine learning and physical models for geosciences
Process-based modelling offers interpretability and physical consistency in many domains of geosciences but struggles to leverage large datasets efficiently. Machine-learning methods, especially deep networks, have strong predictive skills yet are unable to answer specific scientific questions. Here, in this Perspective, we explore differentiable modelling as a pathway to dissolve the perceived barrier between process-based modelling and machine learning in the geosciences and demonstrate its potential with examples from hydrological modelling. ‘Differentiable’ refers to accurately and efficiently calculating gradients with respect to model variables or parameters, enabling the discovery of high-dimensional unknown relationships. Differentiable modelling involves connecting (flexible amounts of) prior physical knowledge to neural networks, pushing the boundary of physics-informed machine learning. It offers better interpretability, generalizability, and extrapolation capabilities than purely data-driven machine learning, achieving a similar level of accuracy while requiring less training data. Additionally, the performance and efficiency of differentiable models scale well with increasing data volumes. Under data-scarce scenarios, differentiable models have outperformed machine-learning models in producing short-term dynamics and decadal-scale trends owing to the imposed physical constraints. Differentiable modelling approaches are primed to enable geoscientists to ask questions, test hypotheses, and discover unrecognized physical relationships. Future work should address computational challenges, reduce uncertainty, and verify the physical significance of outputs.
58 GEOSCIENCES↗
Perceived Costs and Benefits of ICON Science and Foundational Documents associated with “Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles"
This data package is associated with the publication "Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles" in Earth and Space Science (Goldman et al. 2022; https://doi.org/10.1029/2021EA002099). The manuscript is an introductory article for a special collection of commentary articles across 19 geoscience disciplines that explore the challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross-system transferability of science outcomes. This data package contains data, figures, and R scripts associated with the cost/benefit analysis presented in the manuscript. The writing teams involved in the special collection placed each letter of ICON on a plot with perceived cost on one axis and perceived benefit on the other to summarize their perceptions of pursuing each principle of ICON science. These data were subsequently quantified and analyzed. Files are saved as .csv, .R, and .pdf. This data package also contains (1) the public foundational and instructional documents that enabled the crowdsourced creation of the special collection; (2) file-level metadata (flmd) that lists each file in the data package with a description; (3) data dictionary (dd) that defines column headers that appear in csv files. Files are saved as .pdf and .csv.
54 ENVIRONMENTAL SCIENCES↗
Embracing the Intersections of Environmental Science, Engineering, and Geosciences to Solve Grand Challenges of the 21st Century
The U.S. National Academies report on Environmental Engineering for the 21st Century identified five grand challenges of sustainably supplying food, water, and energy; curbing climate change and adapting to its impacts; designing a future without pollution and waste; creating efficient, healthy, resilient cities; and fostering informed decisions and actions. (1) Addressing many of the grand challenges will require embracing the intersections of environmental science, engineering, and geosciences. These three fields are inherently interdisciplinary, and they naturally intersect with each other (Figure 1). Geosciences, or Earth sciences, study the dynamics of different spheres of Earth. One of its missions is to detect the availability of mineral, water, and fuel resources, for sustainable development, and new research opportunities were identified in “coevolution of life, environment, and climate” and “biogeochemical and water cycles in terrestrial environments and impacts of global change” by the U.S. National Research Council. (2) Environmental science and engineering focus on the spheres that intersect with human activities. Environmental science puts an emphasis on understanding the migration of naturally occurring and anthropogenic contaminants in the environment and their impact on ecosystem and human health, and environmental engineering centers on developing technologies for water supply, mineral exploration, and environmental remediation to mitigate adverse impacts.
54 ENVIRONMENTAL SCIENCES↗
Geoscience instrumentation
Geoscience instrumentation systems are considered along with questions of geoscience environment, signal processing, data processing, and design problems. Instrument platforms are examined, taking into account ground platforms, airborne platforms, ocean platforms, and space platforms. In situ and laboratory sensors described include acoustic wave sensors, age sensors, atmospheric constituent sensors, biological sensors, cloud particle sensors, electric field sensors, electromagnetic field sensors, precision geodetic sensors, gravity sensors, ground constituent sensors, horizon sensors, humidity sensors, ion and electron sensors, magnetic field sensors, tide sensors, and wind sensors. Remote sensors are discussed, giving attention to sensing techniques, acoustic echo-sounders, gamma ray sensors, optical sensors, radar sensors, and microwave radiometric sensors.
Wolff, E. A.↗
An outline of planetary geoscience
A philosophy for planetary geoscience is presented to aid in addressing a number of major scientific questions; answers to these questions should constitute the basic geoscientific knowledge of the solar system. However, any compilation of major questions or basic knowledge in planetary geoscience involves compromises and somewhat arbitrary boundaries that reflect the prevalent level of understanding at the time.
Source record↗
Planetary geosciences, 1989-1990
NASA's Planetary Geosciences Programs (the Planetary Geology and Geophysics and the Planetary Material and Geochemistry Programs) provide support and an organizational framework for scientific research on solid bodies of the solar system. These research and analysis programs support scientific research aimed at increasing our understanding of the physical, chemical, and dynamic nature of the solid bodies of the solar system: the Moon, the terrestrial planets, the satellites of the outer planets, the rings, the asteroids, and the comets. This research is conducted using a variety of methods: laboratory experiments, theoretical approaches, data analysis, and Earth analog techniques. Through research supported by these programs, we are expanding our understanding of the origin and evolution of the solar system. This document is intended to provide an overview of the more significant scientific findings and discoveries made this year by scientists supported by the Planetary Geosciences Program. To a large degree, these results and discoveries are the measure of success of the programs.
Zuber, Maria T.↗
The Geoscience Spaceborne Imaging Spectroscopy Technical Committees Calibration and Validation Workshop
Calibration is the process of quantitatively defining a system's responses to known, controlled signal inputs, and validation is the process of assessing, by independent means, the quality of the data products derived from those system outputs [1]. Similar to other Earth observation (EO) sensors, the calibration and validation of spaceborne imaging spectroscopy sensors is a fundamental underpinning activity. Calibration and validation determine the quality and integrity of the data provided by spaceborne imaging spectroscopy sensors and have enormous downstream impacts on the accuracy and reliability of products generated from these sensors. At least five imaging spectroscopy satellites are planned to be launched within the next five years, with the two most advanced scheduled to be launched in the next two years [2]. The launch of these sensors requires the establishment of suitable, standardized, and harmonized calibration and validation strategies to ensure that high-quality data are acquired and comparable between these sensor systems. Such activities are extremely important for the community of imaging spectroscopy users. Recognizing the need to focus on this underpinning topic, the Geoscience Spaceborne Imaging Spectroscopy (previously, the International Spaceborne Imaging Spectroscopy) Technical Committee launched a calibration and validation initiative at the 2013 International Geoscience and Remote Sensing Symposium (IGARSS) in Melbourne, Australia, and a post-conference activity of a vicarious calibration field trip at Lake Lefroy in Western Australia.
Ong, Cindy↗
(abstract) Mars Balloon Trajectory Model for Mars Geoscience Aerobot Development
The Mars Geoscience Aerobot (MGA) is a proposed Mars aerobot (robotic aerovehicle) mission featuring advanced capabilities for surface imagimg and atmospheric science. Development of the MGA mission has been catalyzed by science objectives that include surface geology and atmospheric measurements. The MGA consists of a superpressure balloon that is reflective on top and white on the bottom to avoid condensation CO&sub2; frost during the night. The MGA also features a
balloons↗
PubDAS: A PUBlic Distributed Acoustic Sensing Datasets Repository for Geosciences
During the past few years, distributed acoustic sensing (DAS) has become an invaluable tool for recording high-fidelity seismic wavefields with great spatiotemporal resolutions. However, the considerable amount of data generated during DAS experiments limits their distribution with the broader scientific community. Such a bottleneck inherently slows down the pursuit of new scientific discoveries in geosciences. Here, we introduce PubDAS—the first large-scale open-source repository where several DAS datasets from multiple experiments are publicly shared. PubDAS currently hosts eight datasets covering a variety of geological settings (e.g., urban centers, underground mines, and seafloor), spanning from several days to several years, offering both continuous and triggered active source recordings, and totaling up to ~90 TB of data. Here this article describes these datasets, their metadata, and how to access and download them. Some of these datasets have only been shallowly explored, leaving the door open for new discoveries in Earth sciences and beyond.
54 ENVIRONMENTAL SCIENCES↗
Energy Transition and Geoscience in the US
A discussion of Energy Transition and Geoscience in the US as to how it relates to the sedimentary geology community.
energy transition↗