scholarly journals Low-cost thermal-IR imager for an Earth observation microsatellite

2017 ◽  
Author(s):  
Brian D. Oelrich ◽  
Craig I. Underwood
Keyword(s):  
Low Cost ◽  
Earth Observation ◽  
Ir Imager

scholarly journals Contemporaneous Monitoring of the Whole Dynamic Earth System from Space, Part I: System Simulation Study Using GEO and Molniya Orbits

2021 ◽  
Vol 13 (5) ◽  
pp. 878
Author(s):  
Christopher Cullingworth ◽  
Jan-Peter Muller
Keyword(s):  
Climate Models ◽  
Low Cost ◽  
Earth Observation ◽  
Earth System ◽  
Specific Knowledge ◽  
Educational Value ◽  
Weather Forecasts ◽  
The Public ◽  
Global View ◽  
Disaster Monitoring

Despite the wealth of data produced by previous and current Earth Observation platforms feeding climate models, weather forecasts, disaster monitoring services and countless other applications, the public still lacks the ability to access a live, true colour, global view of our planet, and nudge them towards a realisation of its fragility. The ideas behind commercialization of Earth photography from space has long been dominated by the analytical value of the imagery. What specific knowledge and actionable intelligence can be garnered from these evermore frequent revisits of the planet’s surface? How can I find a market for this analysis? However, what is rarely considered is what is the educational value of the imagery? As students and children become more aware of our several decades of advance in viewing our current planetary state, we should find mechanisms which serve their curiosity, helping to satisfy our children’s simple quest to explore and learn more about what they are seeing. The following study describes the reasons why current GEO and LEO observation platforms are inadequate to provide truly global RGB coverage on an update time-scale of 5-min and proposes an alternative, low-cost, GEO + Molniya 3U CubeSat constellation to perform such an application.

The COCONUDS Concept: a Low-cost, Distributed Network Approach to Satellite Earth Observation

2002 ◽  
pp. 173-177
Author(s):  
F. F. Verduijn ◽  
T. Algra ◽  
W. A. Brokx ◽  
G. J. Close ◽  
C. Lee ◽  
...  
Keyword(s):  
Low Cost ◽  
Earth Observation ◽  
Distributed Network ◽  
Network Approach

scholarly journals First aircraft test results of a compact, low cost hyperspectral imager for earth observation from space

2017 ◽  
Author(s):  
B. T. G. de Goeij ◽  
J. M. O. van Wakeren ◽  
J. P. Veefkind ◽  
T. Vlemmix ◽  
X. Ge ◽  
...  
Keyword(s):  
Low Cost ◽  
Earth Observation ◽  
Test Results

BILSAT-1: A low-cost, agile, earth observation microsatellite for Turkey

2003 ◽  
Vol 53 (4-10) ◽  
pp. 761-769 ◽  
Author(s):  
Andy Bradford ◽  
Luis M. Gomes ◽  
Martin Sweeting ◽  
Gokhan Yuksel ◽  
Cem Ozkaptan ◽  
...  
Keyword(s):  
Low Cost ◽  
Earth Observation

scholarly journals Effective, Low-cost Methods of Applying Computer Vision to Public Earth Observation Data

2020 ◽  
Author(s):  
Michael Evans ◽  
Taylor Minich
Keyword(s):  
Wildlife Conservation ◽  
Low Cost ◽  
Ground Truth ◽  
Google Earth ◽  
Earth Observation ◽  
Learning Technologies ◽  
Observation Data ◽  
Solar Arrays ◽  
Observation Systems ◽  
Earth Observation Data

We have an unprecedented ability to analyze and map the Earth’s surface, as deep learning technologies are applied to an abundance of Earth observation systems collecting images of the planet daily. In order to realize the potential of these data to improve conservation outcomes, simple, free, and effective methods are needed to enable a wide variety of stakeholders to derive actionable insights from these tools. In this paper we demonstrate simple methods and workflows using free, open computing resources to train well-studied convolutional neural networks and use these to delineate objects of interest in publicly available Earth observation images. With limited training datasets (<1000 observations), we used Google Earth Engine and Tensorflow to process Sentinel-2 and National Agricultural Imaging Program data, and use these to train U-Net and DeepLab models that delineate ground mounted solar arrays and parking lots in satellite imagery. The trained models achieved 81.5% intersection over union between predictions and ground-truth observations in validation images. These images were generated at different times and from different places from those upon which they were trained, indicating the ability of models to generalize outside of data on which they were trained. The two case studies we present illustrate how these methods can be used to inform and improve the development of renewable energy in a manner that is consistent with wildlife conservation.

The Earthnet Data Assessment Pilot Project: Paving the Way for New Space Players

2020 ◽  
Author(s):  
Samuel Hunt ◽  
Nigel Fox ◽  
Kevin Halsall ◽  
Andrea Melchiorre ◽  
Sébastien Saunier ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Low Cost ◽  
Pilot Project ◽  
Earth Observation ◽  
Data Availability ◽  
Observation Data ◽  
Satellite Mission ◽  
Satellite Systems ◽  
Data Assessment ◽  
Data Products

<p>In recent years, the increasing range of applications of Earth Observation data products and availability of low-cost satellites has resulted in an increasing number of commercial satellite systems. These services may provide complementary capabilities to those of Space Agencies.  Adoption of these data products for many applications requires that they meet an assured level of quality that is fit for the given purpose.  For the most efficient exploitation of EO data,  therefore,  assessment of data quality, calibration and validation are indispensable tasks,  forming  the basis for reliable scientific conclusions.  </p><p> </p><p>In this context, the European Space  Agency has established the Earthnet  Data Assessment Pilot  (EDAP) project, which aims to enable maximum exploitation of growing data availability by performing early data assessment for various missions that fall into one of the following instrument domains number of  missions, in the Optical, SAR and atmospheric  domains. These assessments are intended to evaluate and report the quality of a satellite mission with respect to what is “fit for purpose” within the context of the its stated performance and application. This activity compliments similar activities from other international partners, including NASA. </p><p> </p><p>Such quality information is often  communicated to users  in an ill-defined or incomplete manner.  We show the development of a generic satellite mission quality assessment framework, developed within EDAP, which is designed  provide a  thorough  review  of  all important  aspects of  mission quality. The assessment results are  conveye d ata top  level  to the user  as a quality assessment matrix diagram. The framework  itself  is based on  the principles of CEOS QA4EO (Quality Assurance for Earth Observation)  and  builds  on the experience  of  several  European projects that worked towards  practically  implementing them. </p><p> </p><p>In a wider context,  such a  framework has  potential for  more general use  in both institutional and commercial Earth Observation  –  helping  mission providers  to understand  the  information their  users  need and  empowering  users  to make informed decisions about which data is fit for their purpose.  As such, there is potential for international collaboration, between space agencies, to synergise quality assessment approaches and to work towards the development of a common standard.</p>

A low-cost thermal IR hyperspectral imager for Earth observation

SPIE Newsroom ◽  
2011 ◽  
Author(s):  
Sarah T. Crites ◽  
Paul Lucey ◽  
Robert Wright ◽  
Harold Garbeil ◽  
Keith Horton
Keyword(s):  
Low Cost ◽  
Earth Observation
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