An architecture for mitigating near earth object's impact to the earth

Yang, Chaowei; Yu, Manzhu; Xu, Mengchao; Jiang, Yongyao; Qin, Han; Liu, Xinyi; Bambacus, Myra; Leung, Ronald Y.; Barbee, Brent W.; Nuth, Joseph A.; Seery, Bernard D.; Bertini, Nicolas R.; Dearborn, David S. P.; Piccione, Mike; Culbertson, Rob; Plesko, C. S.

doi:10.1109/aero.2017.7943594

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Earth data discovery has been an active research area in the past few years [8]. Many geospatial information data management portals have been deployed across the world to support interactive data access [9,10], e.g., the European space agency's sentinel online data portal-Copernicus Open Access Hub [11], CIESIN, which serves data for climate, population, soil, etc. [12], the FAO GeoNetwork that contains data, like soil, population, and land use data from global to regional scale [13].…”

Section: Related Researchmentioning

confidence: 99%

A Query Understanding Framework for Earth Data Discovery

Jiang

Goldstein

et al. 2020

Applied Sciences

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One longstanding complication with Earth data discovery involves understanding a user’s search intent from the input query. Most of the geospatial data portals use keyword-based match to search data. Little attention has focused on the spatial and temporal information from a query or understanding the query with ontology. No research in the geospatial domain has investigated user queries in a systematic way. Here, we propose a query understanding framework and apply it to fill the gap by better interpreting a user’s search intent for Earth data search engines and adopting knowledge that was mined from metadata and user query logs. The proposed query understanding tool contains four components: spatial and temporal parsing; concept recognition; Named Entity Recognition (NER); and, semantic query expansion. Spatial and temporal parsing detects the spatial bounding box and temporal range from a query. Concept recognition isolates clauses from free text and provides the search engine phrases instead of a list of words. Name entity recognition detects entities from the query, which inform the search engine to query the entities detected. The semantic query expansion module expands the original query by adding synonyms and acronyms to phrases in the query that was discovered from Web usage data and metadata. The four modules interact to parse a user’s query from multiple perspectives, with the goal of understanding the consumer’s quest intent for data. As a proof-of-concept, the framework is applied to oceanographic data discovery. It is demonstrated that the proposed framework accurately captures a user’s intent.

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Section: Related Researchmentioning

confidence: 99%

A Query Understanding Framework for Earth Data Discovery

Jiang

Goldstein

et al. 2020

Applied Sciences

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Planetary Defense Mitigation Gateway: A One-Stop Gateway for Pertinent PD-Related Contents

Shams

Yang

et al. 2019

Data

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Planetary Defense (PD) has become a critical effort of protecting our home planet by discovering potentially hazardous objects (PHOs), simulating the potential impact, and mitigating the threats. Due to the lack of structured architecture and framework, pertinent information about detecting and mitigating near earth object (NEO) threats are still dispersed throughout numerous organizations. Scattered and unorganized information can have a significant impact at the time of crisis, resulting in inefficient processes, and decisions made on incomplete data. This PD Mitigation Gateway (pd.cloud.gmu.edu) is developed and embedded within a framework to integrate the dispersed, diverse information residing at different organizations across the world. The gateway offers a home to pertinent PD-related contents and knowledge produced by the NEO mitigation team and the community through (1) a state-of-the-art smart-search discovery engine based on PD knowledge base; (2) a document archiving and understanding mechanism for managing and utilizing the results produced by the PD science community; (3) an evolving PD knowledge base accumulated from existing literature, using natural language processing and machine learning; and (4) a 4D visualization tool that allows the viewers to analyze near-Earth approaches in a three-dimensional environment using dynamic, adjustable PHO parameters to mimic point-of-impact asteroid deflections via space vehicles and particle system simulations. Along with the benefit of accessing dispersed data from a single port, this framework is built to advance discovery, collaboration, innovation, and education across the PD field-of-study, and ultimately decision support.Data 2019, 4, 47 2 of 15 for NEOs, both for asteroids and comets (such as albedo, brightness, shape, and phase). The scientific interest in comets and asteroids is mainly due to their possible collision with our planet, representing a hazard to life on Earth [1]. As many scientific types of research highlight, impacts of NEOs have contributed to mass extinctions and evolution. Moreover, it is a proven fact that NEOs will continue to hit the Earth at irregular intervals in the future [2]. The impactors range from benign fireballs, through the largest airbursts, to globally disastrous destruction on the ground, which are very unlikely to occur in any given lifetime but are probably randomly distributed in time. For events of harmless fireballs, the methods of civil defense are sufficient for saving human lives. For more massive airbursts, changing the path of the near-Earth objects reaching the Earth's vicinity is the appropriate solution. For the global catastrophic events that cause mass extinctions, there is no current technology capable of avoiding disaster [3].Several studies and explorations have been established in global organizations to mitigate the potential impact of near-Earth objects. Programs like NASA's NEO Survey share necessary information with the public that can be utilized to support decision-making for impact mitigati...

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An architecture for mitigating near earth object's impact to the earth

Cited by 2 publications

References 12 publications

A Query Understanding Framework for Earth Data Discovery

A Query Understanding Framework for Earth Data Discovery

Planetary Defense Mitigation Gateway: A One-Stop Gateway for Pertinent PD-Related Contents

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