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The research proposed in this contract concerning investigations of existing and planned Earth Science and Applications Division (ESAD) data management systems and research into utilities for the access and display of scientific data products was completed. A summary of this work is provided.
As expanding service offerings and decreasing prices make the cloud increasingly attractive to Earth Science applications, there are nontrivial practical considerations which can hinder its meaningful use. In this talk, we will discuss architectural recommendations and lessons learned while working on EOSDIS' cloud efforts, particularly the NASA-compliant General Application Platform (NGAP) and its associated applications. Prominent in our findings is the importance of 12-factor design patterns and the powerful "wins" they enable in the cloud. We will share our strategies for "fast-tracking" applications to the cloud --whether they be legacy, planned for the future, or somewhere in between.
This presentation the collection and use of user metrics in NASA's Earth Science data systems. A variety of collection methods is discussed, with particular emphasis given to the American Customer Satisfaction Index (ASCI). User sentiment on potential use of cloud computing is presented, with generally positive responses. The presentation also discusses various forms of automatically collected metrics, including an example of the relative usage of different functions within the Giovanni analysis system.
This presentation provides mission operations status for the Earth Observing System (EOS) Aura satellite for the past six-months (June 2018 through November 2018). It only contains information that is of interest to the International Earth Science Constellation (ESC) Mission Operations Working Group (MOWG) member missions.
Advanced new platform technologies are critical to the realization of the Earth Science Vision in the 2020 timeframe. Examples of the platform technology challenges and current state-of-the-art capabilities are present.
This paper's studies were initiated under the NASA program for the purpose of conducting the earth sciences research using the Landsat Thematic Mapper. The goals of the program include studies of the factors influencing the growth, health, condition, and distribution of vegetation on the earth; the processes controlling the evolution of the earth's crust; the earth's water budget and the hydrologic processes that operate at local, regional, and global scales; the physical and chemical interaction between different types of surficial materials; and the interaction between the earth's surface and its atmosphere. Twenty-seven domestic and five foreign investigations were initiated in 1985, with the results from most of them already published (one study was terminated due to the delay in the TDRSS). Twelve of the studies addressed hydrology, snow and ice, coastal processes, and near-shore oceanographic phenomena; seven addressed vegetation, soils, or animal habitat; and twelve addressed geologic subjects.
Synchrotron-radiation sources and their characteristics are overviewed along with recent synchrotron-based research on earth materials and future earth-science applications utilizing the next generation of synchrotron-radiation sources presently under construction. Focus is placed on X-ray scattering studies of earth materials (crystalline and noncrystalline) under ambient conditions, diffraction studies of earth materials at high pressures and/or temperatures, spectroscopic studies, primarily X-ray absorption spectroscopy, and spatially resolved X-ray fluorescence studies of compositional variations in earth materials. It is noted that other synchrotron-based methods, such as X-ray tomography and topography may become important in characterizing earth materials, while soft X-ray/vacuum ultraviolet radiation from synchrotron sources can be applied to problems involving the structural environments of low-atomic-number elements and the characterization of surface reactions of minerals with liquids and gases.
There is a significant interest in the Earth Science research and user remote sensing community to substantially increase the number of useful observations relative to the current frequency of collection. The obvious reason for such a push is to improve the temporal, spectral, and spatial coverage of the area(s) under investigation. However, there is little analysis available in terms of the benefits, costs and the optimal set of sensors needed to make the necessary observations. Classic observing system solutions may no longer be applicable because of their point design philosophy. Instead, a new intelligent data collection system paradigm employing both reactive and proactive measurement strategies with adaptability to the dynamics of the phenomena should be developed. This is a complex problem that should be carefully studied and balanced across various boundaries including: science, modeling, applications, and technology. Modeling plays a crucial role in making useful predictions about naturally occurring or human-induced phenomena In particular, modeling can serve to mitigate the potentially deleterious impacts a phenomenon may have on human life, property, and the economy. This is especially significant when one is interested in learning about the dynamics of, for example, the spread of forest fires, regional to large-scale air quality issues, the spread of the harmful invasive species, or the atmospheric transport of volcanic plumes and ash. This paper identifies and examines these challenging issues and presents architectural alternatives for an integrated sensor web to provide observing scenarios driving the requisite dynamic spatial, spectral, and temporal characteristics to address these key application areas. A special emphasis is placed on the observing systems and its operational aspects in serving the multiple users and stakeholders in providing societal benefits. We also address how such systems will take advantage of technological advancement in small spacecraft and emerging information technologies, and how sensor web options may be realized and made affordable. Specialized detector subsystems and precision flying techniques may still require substantial innovation, development time and cost: we have presented the considerations for these issues. Finally, data and information gathering and compression techniques are also briefly described.
This will be presented at the Earth Science Constellation Mission Operations Work Group meeting June 13-15, 2017 to discuss EOS Aqua status.
These are additional promotional materials in the form of a brochure for the upcoming Earth Science Summer School, which is scheduled for summer 2017.
The Research and Analysis Program is the core of the OSSA program in the space and Earth sciences because it provides the means of identifying the most appropriate missions and ensures that scientific results are fully realized. Consequently, this program must be given a priority in funding that is commensurate with that of flight programs. The goals of the R&A program and its role in meeting present day OSSA objectives; management of the R&A program by NASA Headquarters Discipline Chiefs and Programs Managers; and funding and distribution trends are assessed. Recommendations are advanced for halting the declining support of this program.
This publication contains the summaries for the Sixth Annual JPL Airborne Earth Science Workshop, held in Pasadena, California, on March 4-8, 1996. The main workshop is divided into two smaller workshops as follows: (1) The Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) workshop, on March 4-6. The summaries for this workshop appear in Volume 1; (2) The Airborne Synthetic Aperture Radar (AIRSAR) workshop, on March 6-8. The summaries for this workshop appear in Volume 2.
This demo presents an http-based client/server application prototype that facilitates internet access to Earth Science data.
This presentation provides mission operations status for the Earth Observing System (EOS) Aura satellite for the past six-months (December 2017 through May 2018). It only contains information that is of interest to the International Earth Science Constellation (ESC) Mission Operations Working Group (MOWG) member missions. It will be presented at the bi-annual MOWG Meeting at the USGS EROS Data Center in Sioux Falls, South Dakota on Wednesday, June 12, 2018. These meetings have been occurring twice a year since the MOWG was formed in 2003. The presentation has been reviewed and approved by Eric Moyer, ESMO Deputy Project Manager Technical.
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Despite their wide and successful applications, deep learning (DL) models are prone to overfitting for small training datasets, produce a poor predictive performance for uncertain data, and provide point estimations without any indication of the accuracy and credibility. These limitations of the deterministic DL models hinder their effective application in Earth system science where the labelled data are sparse, noisy and incomplete with large uncertainty and where the predictive uncertainty quantification is needed for scientific understanding and policy decision making. Integration of Bayesian inference into DL models adds an estimate of uncertainty and regularization in the predictions. However, traditional Bayesian methods are computationally unaffordable and inflexible for high-dimensional problems, which limits their application to DL systems that typically have millions of model parameters. In this effort, we propose an efficient and general-purpose Bayesian inference method to advance DL model optimization and uncertainty quantification, so as to facilitate the adoption of DL in Earth sciences. In a demonstration, we integrate the proposed Bayesian method with a feedforward neural network (NN) to build a fast-to-evaluate surrogate of the complex Energy Exascale Earth System Land Model for efficient modeling. The formulated Bayesian NN, using a small number of training data, produces an accurate prediction with high credibility, whereas with the same small training size, the deterministic NN cannot yield a reasonable estimation and does not provide confidence information. The proposed Bayesian method is computationally efficient and flexible, capable of integration with diverse network variants such as convolutional NNs and recurrent NNs to advance the application of DL in Earth sciences.
As projected by IPCC 2007 report, by the end of this century the Middle East North Mrica (MENA) region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. In late 2011, the World Bank, USAID and NASA have joined hands to establishing integrated, modem, up to date NASA developed capabilities for various countries in the MENA region for addressing water resource issues and adapting to climate change impacts for improved decision making for societal benefits. The main focus of this undertaking is to address the most pressing societal issues which can be modeled and solved by utilizing NASA Earth Science remote sensing data products and hydrological models. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. NASA has over fifteen satellites and thirty instruments operating on these space borne platforms and generating over 2000 different science products on a daily basis. Some of these products are soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gasses, ice and snow measurements, and many more. All of the data products, models and research results are distributed via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, drought assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Training is an important component under this activity and adequate level of training will be offered to build basic capacity to work with NASA provided data products, models for their future use. This paper provides a comprehensive introduction to NASA's Earth Science mission for understanding the behavior of our home Planet, projecting its health for future generations and applying research results solving societal issues.
We propose to develop and enhance a workstation based grid analysis and display software system for Earth science data set browsing, sampling and manipulation. The system will be coupled to a super computer in a distributed computing environment for near real-time interaction between scientists and computational results.