Prof. Daniel Selva Profile

Prof. Daniel Selva

at Texas A&M Univ

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Publications (3)

Proceedings Article | 8 September 2015 Paper

Collaboration pathway(s) using new tools for optimizing ‘operational’ climate monitoring from space

Douglas Helmuth, Daniel Selva, Morgan Dwyer

Proceedings Volume 9607, 96071K (2015) https://doi.org/10.1117/12.2187157

KEYWORDS: Climatology, Environmental sensing, Satellites, Climate change, Systems modeling, Space operations, Sensors, Atmospheric modeling, Rule based systems, Remote sensing

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Consistently collecting the earth’s climate signatures remains a priority for world governments and international scientific organizations. Architecting a long term solution requires transforming scientific missions into an optimized robust ‘operational’ constellation that addresses the collective needs of policy makers, scientific communities and global academic users for trusted data. The application of new tools offers pathways for global architecture collaboration. Recent rule-based expert system (RBES) optimization modeling of the intended NPOESS architecture becomes a surrogate for global operational climate monitoring architecture(s). These rulebased systems tools provide valuable insight for global climate architectures, by comparison/evaluation of alternatives and the sheer range of trade space explored. Optimization of climate monitoring architecture(s) for a partial list of ECV (essential climate variables) is explored and described in detail with dialogue on appropriate rule-based valuations. These optimization tool(s) suggest global collaboration advantages and elicit responses from the audience and climate science community. This paper will focus on recent research exploring joint requirement implications of the high profile NPOESS architecture and extends the research and tools to optimization for a climate centric case study. This reflects work from SPIE RS Conferences 2013 and 2014, abridged for simplification^{30, 32}. First, the heavily securitized NPOESS architecture; inspired the recent research question - was Complexity (as a cost/risk factor) overlooked when considering the benefits of aggregating different missions into a single platform. Now years later a complete reversal; should agencies considering Disaggregation as the answer. We’ll discuss what some academic research suggests. Second, using the GCOS requirements of earth climate observations via ECV (essential climate variables) many collected from space-based sensors; and accepting their definitions of global coverages intended to ensure the needs of major global and international organizations (UNFCCC and IPCC) are met as a core objective. Consider how new optimization tools like rule-based engines (RBES) offer alternative methods of evaluating collaborative architectures and constellations? What would the trade space of optimized operational climate monitoring architectures of ECV look like? Third, using the RBES tool kit (2014) demonstrate with application to a climate centric rule-based decision engine - optimizing architectural trades of earth observation satellite systems, allowing comparison(s) to existing architectures and gaining insights for global collaborative architectures. How difficult is it to pull together an optimized climate case study - utilizing for example 12 climate based instruments on multiple existing platforms and nominal handful of orbits; for best cost and performance benefits against the collection requirements of representative set of ECV. How much effort and resources would an organization expect to invest to realize these analysis and utility benefits?

Proceedings Article | 22 October 2014 Paper

Collaboration pathway(s) using new tools for optimizing operational climate monitoring from space

Douglas Helmuth, Daniel Selva, Morgan Dwyer

Proceedings Volume 9241, 92411R (2014) https://doi.org/10.1117/12.2067427

KEYWORDS: Climatology, Environmental sensing, Satellites, Climate change, Space operations, Systems modeling, Sensors, Atmospheric modeling, Rule based systems, Aerospace engineering

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Proceedings Article | 7 October 2014 Paper

Knowledge-intensive global optimization of Earth observing system architectures: a climate-centric case study

D. Selva

Proceedings Volume 9241, 92411S (2014) https://doi.org/10.1117/12.2067558

KEYWORDS: Space operations, Climatology, Satellites, Spatial resolution, Computer architecture, Temporal resolution, LIDAR, Environmental sensing, Sensors, Fuzzy logic

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