MODIS science algorithms and data systems lessons learned
Robert E. Wolfe,Bill L. Ridgway,Frederick S. Patt,Edward J. Masuoka +3 more
- 12 Jul 2009
- Vol. 5, pp 473-476
TL;DR: For almost 10 years, standard global products from NASA's Earth Observing System's (EOS) two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors are being used world-wide for earth science research and applications.
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Abstract: For almost 10 years, standard global products from NASA's Earth Observing System's (EOS) two Moderate Resolution Imaging Spectroradiometer (MODIS) sensors are being used world-wide for earth science research and applications. This paper discusses the lessons learned in developing the science algorithms and the data systems needed to produce these high quality data products for the earth sciences community. Strong science team leadership and communication, an evolvable and scalable data system, and central coordination of QA and validation activities enabled the data system to grow by two orders of magnitude from the initial at-launch system to the current system able to reprocess data from both the Terra and Aqua missions in less than a year. Many of the lessons learned from MODIS are already being applied to follow-on missions.
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Citations
Assessing the coupling between surface albedo derived from MODIS and the fraction of diffuse skylight over spatially-characterized landscapes
Miguel O. Román,Miguel O. Román,Crystal B. Schaaf,Philip Lewis,Feng Gao,Gail P. Anderson,Gail P. Anderson,Jeffrey L. Privette,Alan H. Strahler,Curtis E. Woodcock,M.J. Barnsley +10 more
TL;DR: In this article, the authors used the BRDF algorithm to retrieve instantaneous surface albedo at a point in time and under specific atmospheric conditions, which was then used to study the role that the fraction of diffuse skylight plays under realistic scenarios of anisotropic diffuse illumination and multiple scattering between the surface and atmosphere.
186
Scaling the pipe: NASA EOS Terra data systems at 10
Robert E. Wolfe,Hampapuram Ramapriyan +1 more
- 25 Jul 2010
TL;DR: The evolution of the Terra data systems over the last decade is described in which the distributed systems that produce, archive and distribute high quality Terra data products were scaled by two orders of magnitude.
Exploring the benefits of satellite remote sensing for flood prediction across scales
L. Cunha
- 01 May 2012
TL;DR: In this article, the authors explored the benefits of using satellite-light remote sensing for flood prediction across scales in the field of Civil and Environmental Engineering at the University of Iowa. But their work was submitted in partial fulfillment of the requirements for the Doctor of Philosophy degree in civil and environmental engineering.
References
An overview of MODIS Land data processing and product status
Christopher O. Justice,John R. Townshend,Eric Vermote,Edward J. Masuoka,Robert E. Wolfe,Nazmi Saleous,David P. Roy,Jeffrey T. Morisette +7 more
TL;DR: In this article, the authors provide a summary of the MODIS instrument performance and status, the data production system, the products, their status and availability for land studies, and a partnership between Science Team members and MODIS Science Data Support Team is producing data sets of unprecedented volume and number for the land research and applications.
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The MODIS Land product quality assessment approach
TL;DR: In this paper, the authors describe a new approach for assessing and ensuring the performance of land remote sensing products that are generated on a systematic basis, and describe the QA approach adopted by the MODIS Land (MODLAND) Science Team.
317
A framework for the validation of MODIS Land products
TL;DR: The MODIS Land team is producing a suite of global land products whose uncertainty will be estimated through validation activities as mentioned in this paper, which will be derived from a combination of in situ data and imagery from airborne and spaceborne sensors.
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