CubeSat: The Pico-Satellite Standard for Research and Education

Nugent, Ryan; Munakata, Riki; Chin, Alexander W.; Coelho, Roland; Student, Graduate; Puig‐Suari, Jordi

doi:10.2514/6.2008-7734

Cited by 65 publications

(23 citation statements)

References 1 publication

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“…• The proliferation of new platforms such as CubeSats and drones (Chin et al, 2008). Sensors and analytical tools are rapidly expanding the use of remotely sensed and other data in studying social and socio-environmental systems (e.g.…”

Section: 8mentioning

confidence: 99%

Eight grand challenges in socio-environmental systems modeling

Elsawah

Filatova

Jakeman

et al. 2020

SESMO

131

120

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Modeling is essential to characterize and explore complex societal and environmental issues in systematic and collaborative ways. Socio-environmental systems (SES) modeling integrates knowledge and perspectives into conceptual and computational tools that explicitly recognize how human decisions affect the environment. Depending on the modeling purpose, many SES modelers also realize that involvement of stakeholders and experts is fundamental to support social learning and decision-making processes for achieving improved environmental and social outcomes. The contribution of this paper lies in identifying and formulating grand challenges that need to be overcome to accelerate the development and adaptation of SES modeling. Eight challenges are delineated: bridging epistemologies across disciplines; multi-dimensional uncertainty assessment and management; scales and scaling issues; combining qualitative and quantitative methods and data; furthering the adoption and impacts of SES modeling on policy; capturing structural changes; representing human dimensions in SES; and leveraging new data types and sources. These challenges limit our ability to effectively use SES modeling to provide the knowledge and information essential for supporting decision making. Whereas some of these challenges are not unique to SES modeling and may be pervasive in other scientific fields, they still act as barriers as well as research opportunities for the SES modeling community. For each challenge, we outline basic steps that can be taken to surmount the underpinning barriers. Thus, the paper identifies priority research areas in SES modeling, chiefly related to progressing modeling products, processes and practices.

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Section: 8mentioning

confidence: 99%

Eight grand challenges in socio-environmental systems modeling

Elsawah

Filatova

Jakeman

et al. 2020

SESMO

131

120

View full text Add to dashboard Cite

show abstract

“…Future measurement opportunities will be offered by the continuously increasing capabilities of picoand nanosatellites, e.g. CubeSats, with a mass between 1 and 10 kg, and a size approximately that of a toaster (Chin et al, 2008;Heidt et al, 2000;Puig-Suari et al, 2001;Schilling, 2006;Zurbuchen et al, 2016). Such platforms have many benefits over classic satellites including simpler and cheaper designs, faster build times and, consequently, many more units can be deployed.…”

Section: Introductionmentioning

confidence: 99%

Using picosatellites for 4-D imaging of volcanic clouds: Proof of concept using ISS photography of the 2009 Sarychev Peak eruption

Zakšek

James

Hort

et al. 2018

Remote Sensing of Environment

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A proposed picosatellite formation could provide volcanic plume height measurements. 2 Proof of concept tested using photographs taken from the International Space Station. 3 Astronaut photos of 2009 Sarychev eruption processed using structure-from-motion. 4 Plume height measured to a precision of ~200 m, also with ascent velocity estimates. 5 Results constrained a plume model to suggest a mass eruption rate of 2.6×10 6 kg s-1. 6 *Revised Manuscript with no Changes Highlighted Click here to download Revised Manuscript with no Changes Highlighted: _manuscript-revised_no_track_changes.docx

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“…The antenna performance has been verified by experiment results integrated with 2 U nanosatellite structure. The simulation and design of the antenna have been performed maintaining nanosatellite standards …”

Section: Introductionmentioning

confidence: 99%

Performance analysis of an S‐band antenna for nanosatellite payloads communication system

Alam

Islam

Ullah

et al. 2018

Micro & Optical Tech Letters

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The nanosatellite concept was born from the low‐cost small satellite educational research activities that lead to the nanosatellite revolution. However, in recent years, the development of the nanosatellite is not for just research purpose but commercial opportunities as well. Antenna is very crucial part of the nanosatellite communication system that establishes communication between space to ground. In this paper, an S‐band circular polarized (CP) antenna is presented and investigate the performance compatibility for nanosatellite space mission. The antenna was fabricated on 1.575 mm thick Rogers 5880 substrate material. The measured result shows that the antenna has a −10 dB reflection coefficient bandwidth of 1.64%, 3 dB axial‐ratio bandwidths of 38 MHz and realized gain of around 5.58 dB at the resonant frequency. The antenna was integrated with 2 U nanosatellite structure and investigated the antenna performance.

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CubeSat: The Pico-Satellite Standard for Research and Education

Cited by 65 publications

References 1 publication

Eight grand challenges in socio-environmental systems modeling

Eight grand challenges in socio-environmental systems modeling

Using picosatellites for 4-D imaging of volcanic clouds: Proof of concept using ISS photography of the 2009 Sarychev Peak eruption

Performance analysis of an S‐band antenna for nanosatellite payloads communication system

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