Results for “geosciences” — Page 27

NASA NTRS2016

Snow Grain Size Retrieval over the Polar Ice Sheets with the Ice, Cloud and Land Elevation Satellite (ICESat) Observations

Snow grain size is an important parameter for cryosphere studies. As a proof of concept, this paper presents an approach to retrieve this parameter over Greenland, East and West Antarctica ice sheets from surface reflectances observed with the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation Satellite (ICESat) at 1064 nanometers. Spaceborne lidar observations overcome many of the disadvantages in passive remote sensing, including difficulties in cloud screening and low sun angle limitations; hence tend to provide more accurate and stable retrievals. Results from the GLAS L2A campaign, which began on 25 September and lasted until 19 November, 2003, show that the mode of the grain size distribution over Greenland is the largest (approximately 300 microns) among the three, West Antarctica is the second (220 microns) and East Antarctica is the smallest (190 microns). Snow grain sizes are larger over the coastal regions compared to inland the ice sheets. These results are consistent with previous studies. Applying the broadband snow surface albedo parameterization scheme developed by Garder and Sharp (2010) to the retrieved snow grain size, ice sheet surface albedo is also derived. In the future, more accurate retrievals can be achieved with multiple wavelengths lidar observations.

ice↗

NASA NTRS2016

Scaling Estimates of Vegetation Structure in Amazonian Tropical Forests Using Multi-Angle MODIS Observations

Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r(exp 2)= 0.54, RMSE= 0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy(0.52 less than or equal to r(exp 2) less than or equal to 0.61; p less than 0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (sigma(sup 0)) from SeaWinds/QuikSCAT presented an r(exp 2) of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon.

MODIS↗

NASA NTRS2017

Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes over 180 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies.

Data Systems↗

NASA NTRS2017

ICESAT GLAS Altimetry Measurements: Received Signal Dynamic Range and Saturation Correction

NASAs Ice, Cloud, and land Elevation Satellite (ICESat), which operated between 2003 and 2009, made the first satellite-based global lidar measurement of earths ice sheet elevations, sea-ice thickness, and vegetation canopy structure. The primary instrument on ICESat was the Geoscience Laser Altimeter System (GLAS), which measured the distance from the spacecraft to the earth's surface via the roundtrip travel time of individual laser pulses. GLAS utilized pulsed lasers and a direct detection receiver consisting of a silicon avalanche photodiode and a waveform digitizer. Early in the mission, the peak power of the received signal from snow and ice surfaces was found to span a wider dynamic range than anticipated, often exceeding the linear dynamic range of the GLAS 1064-nm detector assembly. The resulting saturation of the receiver distorted the recorded signal and resulted in range biases as large as approximately 50 cm for ice- and snow-covered surfaces. We developed a correction for this saturation range bias based on laboratory tests using a spare flight detector, and refined the correction by comparing GLAS elevation estimates with those derived from Global Positioning System surveys over the calibration site at the salar de Uyuni, Bolivia. Applying the saturation correction largely eliminated the range bias due to receiver saturation for affected ICESat measurements over Uyuni and significantly reduced the discrepancies at orbit crossovers located on flat regions of the Antarctic ice sheet.

Sun, Xiaoli↗

NASA NTRS2017

Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes over 180 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies.The talk will present an overview of current efforts in ESI, the role members of IEEE GRSS play, and discuss recent developments in data preservation and provenance.

Remote Sensing↗

NASA NTRS2017

Collaborative Data Publication Utilizing the Open Data Repository's (ODR) Data Publisher

Introduction: For small communities in diverse fields such as astrobiology, publishing and sharing data can be a difficult challenge. While large, homogenous fields often have repositories and existing data standards, small groups of independent researchers have few options for publishing standards and data that can be utilized within their community. In conjunction with teams at NASA Ames and the University of Arizona, the Open Data Repository's (ODR) Data Publisher has been conducting ongoing pilots to assess the needs of diverse research groups and to develop software to allow them to publish and share their data collaboratively. Objectives: The ODR's Data Publisher aims to provide an easy-to-use and implement software tool that will allow researchers to create and publish database templates and related data. The end product will facilitate both human-readable interfaces (web-based with embedded images, files, and charts) and machine-readable interfaces utilizing semantic standards. Characteristics: The Data Publisher software runs on the standard LAMP (Linux, Apache, MySQL, PHP) stack to provide the widest server base available. The software is based on Symfony (www.symfony.com) which provides a robust framework for creating extensible, object-oriented software in PHP. The software interface consists of a template designer where individual or master database templates can be created. A master database template can be shared by many researchers to provide a common metadata standard that will set a compatibility standard for all derivative databases. Individual researchers can then extend their instance of the template with custom fields, file storage, or visualizations that may be unique to their studies. This allows groups to create compatible databases for data discovery and sharing purposes while still providing the flexibility needed to meet the needs of scientists in rapidly evolving areas of research. Research: As part of this effort, a number of ongoing pilot and test projects are currently in progress. The Astrobiology Habitable Environments Database Working Group is developing a shared database standard using the ODR's Data Publisher and has a number of example databases where astrobiology data are shared. Soon these databases will be integrated via the template-based standard. Work with this group helps determine what data researchers in these diverse fields need to share and archive. Additionally, this pilot helps determine what standards are viable for sharing these types of data from internally developed standards to existing open standards such as the Dublin Core (http://dublincore.org) and Darwin Core (http://rs.twdg.org) metadata standards. Further studies are ongoing with the University of Arizona Department of Geosciences where a number of mineralogy databases are being constructed within the ODR Data Publisher system. Conclusions: Through the ongoing pilots and discussions with individual researchers and small research teams, a definition of the tools desired by these groups is coming into focus. As the software development moves forward, the goal is to meet the publication and collaboration needs of these scientists in an unobtrusive and functional way.

easy to use and implement software tool↗

NASA NTRS2017

Earth Science Informatics - Overview

Over the last 10-15 years, significant advances have been made in information management, there are an increasing number of individuals entering the field of information management as it applies to Geoscience and Remote Sensing data, and the field of informatics has come to its own. Informatics is the science and technology of applying computers and computational methods to the systematic analysis, management, interchange, and representation of science data, information, and knowledge. Informatics also includes the use of computers and computational methods to support decision making and applications. Earth Science Informatics (ESI, a.k.a. geoinformatics) is the application of informatics in the Earth science domain. ESI is a rapidly developing discipline integrating computer science, information science, and Earth science. Major national and international research and infrastructure projects in ESI have been carried out or are on-going. Notable among these are: the Global Earth Observation System of Systems (GEOSS), the European Commissions INSPIRE, the U.S. NSDI and Geospatial One-Stop, the NASA EOSDIS, and the NSF DataONE, EarthCube and Cyberinfrastructure for Geoinformatics. More than 18 departments and agencies in the U.S. federal government have been active in Earth science informatics. All major space agencies in the world, have been involved in ESI research and application activities. In the United States, the Federation of Earth Science Information Partners (ESIP), whose membership includes over 180 organizations (government, academic and commercial) dedicated to managing, delivering and applying Earth science data, has been working on many ESI topics since 1998. The Committee on Earth Observation Satellites (CEOS)s Working Group on Information Systems and Services (WGISS) has been actively coordinating the ESI activities among the space agencies.The talk will present an overview of current efforts in ESI, the role members of IEEE GRSS play, and discuss recent developments in data preservation and provenance.

Remote Sensing↗

NASA NTRS2017

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.

Kuo, Kwo-Sen↗

NASA NTRS2018

Climatespark: an In-Memory Distributed Computing Framework for Big Climate Data Analytics

The unprecedented growth of climate data creates new opportunities for climate studies, and yet big climate data pose a grand challenge to climatologists to efficiently manage and analyze big data. The complexity of climate data content and analytical algorithms increases the difficulty of implementing algorithms on high performance computing systems. This paper proposes an in-memory, distributed computing framework, ClimateSpark, to facilitate complex big data analytics and time-consuming computational tasks. Chunking data structure improves parallel I/O efficiency, while a spatiotemporal index is built for the chunks to avoid unnecessary data reading and preprocessing. An integrated, multi-dimensional, array-based data model (ClimateRDD) and ETL operations are developed to address big climate data variety by integrating the processing components of the climate data lifecycle. ClimateSpark utilizes Spark SQL and Apache Zeppelin to develop a web portal to facilitate the interaction among climatologists, climate data, analytic operations and computing resources (e.g., using SQL query and Scala/Python notebook). Experimental results show that ClimateSpark conducts different spatiotemporal data queries/analytics with high efficiency and data locality. ClimateSpark is easily adaptable to other big multiple- dimensional, array-based datasets in various geoscience domains.

Hu, Fei↗

NASA NTRS2018

Phase Heritage: Deciphering Evidence of Pre-Existing Phases via Inherited Crystallographic Orientations

The concept of 'phase heritage' (e.g., Timms et al., 2017a) involves microstructural recognition of the former presence of a phase that has since transformed to another via evidence encoded in crystallographic orientations. Phase heritage relies on the phenomenon that newly grown (daughter) phases nucleate with particular crystallographic orientation relationships with the preceding (parent) phase. This phenomenon is common for displacive (i.e., shear or martensitic) transformations, well documented in the metals and ceramics literature, but is relatively uncommon in geosciences. This presentation outlines the concepts behind this approach, showcases results from software for automated analysis of EBSD data, and illustrates examples of polymorphic and dissociation phase transformations in the ZrSiO4-ZrO2-SiO2 system, which has particularly useful applications for 'extreme thermobarometry' in impact environments (Timms et al., 2017a).

Timms, Nicholas E.↗

NASA NTRS2018

Understanding Climate-Vegetation Interactions in Global Rainforests Through a GP-Tree Analysis

The tropical rainforests are the largest reserves of terrestrial carbon and, therefore, the future of these rainforests is a question that is of immense importance in the geoscience research community. With the recent severe Amazonian droughts in 2005 and 2010 and on-going drought in the Congo region for more than two decades, there is growing concern that these forests could succumb to precipitation reduction, causing extensive carbon release and feedback to the carbon cycle. However, there is no single ecosystem model that quantifies the relationship between vegetation health in these rainforests and climatic factors. Small scale studies have used statistical correlation measure and simple linear regression to model climate-vegetation interactions, but suffer from the lack of comprehensive data representation as well as simplistic assumptions about dependency of the target on the covariates. In this paper we use genetic programming (GP) based symbolic regression for discovering equations that govern the vegetation climate dynamics in the rainforests. Expecting micro-regions within the rainforests to have unique characteristics compared to the overall general characteristics, we use a modified regression-tree based hierarchical partitioning of the space to build individual models for each partition. The discovery of these equations reveal very interesting characteristics about the Amazon and the Congo rainforests. Our method GP-tree shows that the rainforests exhibit tremendous resiliency in the face of extreme climatic events by adapting to changing conditions.

genetic programming↗

NASA NTRS2015

Science Training History of the Apollo Astronauts

Following President Kennedy’s initiation of Project Apollo, NASA underwent substantial changes in personnel, organization, and programs and faced a major question: what to do on the Moon after landing. Once a decision that science activities, particularly geoscience, should be pursued, considerable debate ensued over how to accomplish this. Questions arose over instruments and tools required, samples and photos to be returned, landing site selection, and crew composition. Answers to these questions required major efforts for planning traverses on the Moon and training the astronauts in the extensive procedures necessary in low gravity to use tools, set up instruments, take adequate photos, collect and document samples, and provide proper descriptions. In addition to astronauts on the surface, an astronaut in lunar orbit managed additional instruments, photography and verbal descriptions. Training for these activities averaged nearly one hundred hours per month for over a year for each crew. There were many problems as the training progressed: adjusting groups and backgrounds of the training personnel for the best combination of personalities and skills, overcoming logistical troubles, revising awkward procedures, determining optimum means of communications between all involved groups, and devising contingency procedures for real-time problems. By the last mission these problems were overcome.

Phinney, William C.↗

NASA NTRS2017

International Challenges of GRACE Follow-On

The Gravity Recovery and Climate Experiment - Follow-On (GRACE-FO) Mission is a NASA directed mission to continue the goals of the original GRACE mission and provide continuity for the GRACE data set. The GRACE-FO mission is the result of an international cooperation to develop a concept and approach that minimizes cost and risk and maximizes the probability of success through limited changes to the original GRACE system design. The result is a system architecture in which maintenance of heritage is paramount, including heritage derived through the partnership with the German Research Centre for Geosciences (GFZ) in Germany. As a secondary goal, GRACE-FO will carry a Laser Ranging Interferometer (LRI) as a technology demonstration, which will provide laser interferometry measurements of inter-satellite range, complementary to the K/Ka-Band microwave link to demonstrate laser-ranging technology in support of future GRACE-like missions. Another secondary objective is the continuation of GRACE radio occultation measurements.

Kayali, Sammy↗

NASA NTRS2019

Using Big Data Technologies with Earth Science Data in HDF5: HDF5 Scalable Solutions

HDF5 (Hierarchical Data Format 5) is open-source, high-performance software that consists of an abstract data model, library, and fileformat used for storing and managing extremely large and/or complex data collections. NASA Earth Observing System (EOS) Data and Information Systems use HDF5 as an archival format to store remote sensing data from EOS satellites. HDF5 is also used to store other types of Geoscience and Strophysical data, e.g., seismic data and data from Low-Frequency Array (LOFAR) radio telescopes. Data stored in HDF5 has reached tens of petabytes and is growing at an accelerated rate.With the growing amout of HDF5 Earth Science data to analyze and process, scientists need to adopt big data technologies including new storage paradigms such as cloud and object storage. To run models and perform data analysis they also need to utilizied efficient and diverse ways to access data, from high-performance computing's (HPC) Message Passing Interface (MPI) I/O and deep memory hierarchies (DMH) to non-HPC frameworks such as Apache Hadoop, Spark, and Drill. The HDF Group continually works to enable usage of big data technologies in HDF software.

Knox, Larry↗

NASA NTRS2020

Recommended Laboratory and Field Studies ahead of Future Mercury Exploration

Data from Mariner 10, MESSENGER, and ground-based telescopic observations have facilitated great advancements towards understanding the geochemistry, geology, internal structure, and space environment (exosphere/magnetosphere) of Mercury. Future exploration efforts by BepiColombo, landed science, and sample return will revolutionize our understanding of this planet. However, to enhance the scientific return of past, present, and future data collection at Mercury, it is imperative that laboratory and field-based studies be conducted over the next decade. This white paper gives examples of laboratory and field studies, including instrument testing, which should take place over the next decade to facilitate the interpretation of data and preparation of future missions to the inner-most planet. By no means are the topics in this paper exhaustive, but rather are meant to demonstrate the immense amount of work that needs to be completed ahead of, or in conjunction with, current and future exploration efforts of Mercury. This work would amplify the benefits from additional data obtained from the planet’s surface to the fullest extent possible, and to aid in decision making of future instrument payloads. We have chosen to focus our inputs here on geochemistry, geology, and space environment related efforts, but we emphasize that extensive research in the areas of geophysics and other geosciences-related disciplines will benefit from additional studies.

Kathleen E. Vander Kaaden↗

NASA NTRSDate not supplied

Evidence of Participation in the Advancement of Knowledge from 25 Years of Publications for the GLOBE Program

The Global Learning and Observations to Benefit the Environment (GLOBE) Program was announced on Earth Day 1994 and began on Earth Day 1995. Over the first 25 years of its operation, there have been more than 600 formal publications and 340 conference presentations about the program, in at least 15 languages. As the 25th anniversary of the program approached, we began a focused effort to find and characterize those publications in order to better understand GLOBE’s impact to date as well as its future potential. GLOBE was envisioned from the beginning as a science and education program, so GLOBE publications cover a wide range of topics across Earth system science as well as in education and evaluation topics. To characterize the collection, a large set of dimensions was first identified from the literature, across science and education. These include codes related to: motivation and conception of the research investigation, educator practices and training, education outcomes & demonstration that these outcomes were achieved, data and study scope, characteristics of the investigation or its findings. Application of these codes was first tested by three raters (the first three authors) on a subset of the publications, then refined to capture missing aspects. The full set of publications was then rated on the full set of criteria. As a second step, subsets of the collection with particularly in depth discussion of The GLOBE Program are now being analyzed in more detail. This poster will summarize various attributes of the GLOBE bibliography and identify areas of potential for further geoscience investigations.

Lin Chambers↗

NASA NTRS1993

Field Observations Using AOTF Polarimetric Imaging Spectrometer

This paper reports preliminary results of recent field observations using a prototype acousto-optic tunable filter (AOTF) polarimetric imaging spectrometer. The data illustrate application potentials for geoscience.

Field↗

NASA NTRSDate not supplied

Assimilating Lessons Learned – From URGE to NASA's Student Airborne Science Activation (SaSa) Project

In the first half of 2021, formal and informal pods at several universities and NASA Center affiliates participated in the Unlearning Racism in Geosciences (URGE) curriculum and deliverables. As a result, several members from different URGE pods are propagating and applying the URGE lessons learned to the new 5-year NASA Student Airborne Science Activation project (SaSa). Starting in the Summer of 2022, SaSa will provide an 8-week summer Earth Science research experience focused on attracting and retaining early undergraduate students from historically underrepresented groups from minority-serving institutions (MSIs). The multicenter and field-based research experience will provide the students access to and experience with NASA airborne resources. Additionally, integrating NASA material into the MSI curricula and providing student mentorship at both MSIs and NASA Centers will enhance students' exposure to Earth Science research. The objectives of URGE and SaSa are highly compatible with one another, and the project timing allows for the integration of URGE lessons early in the SaSa curriculum design phase. As of December 2021, the first SaSa summer program application will be open and the first SaSa semester at the host MSIs will be completed. This presentation will discuss the assimilation of URGE lessons learned from our respective pods into the first SaSa academic semester and into the preparations for the first SaSa summer cohort. We will welcome additional feedback from the broader URGE community in advance of SaSa's first summer session.

Kristina Pistone↗