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All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Integrating Cloud-Based Workflows in Continental-Scale Cropland Extent Classification

Accurate information on cropland spatial distribution is required for global-scale assessments and agricultural land use policies. Cloud computing platforms such as Google Earth Engine (GEE) provide unprecedented opportunities for large-scale classifications of Landsat data. We developed a novel method to fuse pixel-based random forest classification of continental-scale Landsat data on GEE and an object-based segmentation approach known as recursive hierarchical segmentation (RHSeg). Using our fusion method, we produced a continental-scale cropland extent map for North America at 30m spatial resolution for the nominal year 2010. The total cropland area for North America was estimated at 275.18 million hectares (Mha). The overall accuracies of the map are>90% across the continent. This map also compares well with the United States Department of Agriculture (USDA) cropland data layer (CDL), Agriculture and Agri-food Canada (AAFC) annual crop inventory (ACI), and the Mexican government agency Servicio de Informacion Agroalimentaria y Pesquera (SIAP)'s agricultural boundaries. Furthermore, our map compared well with sub-country statistics including state-wise and county-wise cropland statistics in regression models resulting in R2 > 0.84. This key contribution paves the way for more detailed products such as crop intensity, crop type, and crop irrigation, and provides a method for creating high-resolution cropland extent maps for other countries where spatial information about croplands are not as prevalent.

Massey, Richard↗
NASA NTRS1977

A distributed microprocessor system for spacecraft control and data handling

The specific requirements for spacecraft computing systems are considered. These requirements are partly related to the constraints of limited resources of power, weight, and volume. Another important factor is the requirement of extremely high reliability. These reliability requirements have led to introduction of automated redundancy techniques on board the spacecraft. The various redundant computers check each other and provide recovery procedures when a computer is found to have failed. Past and future capabilities are considered along with distributed processing requirements. System considerations are discussed, taking into account suboptimum computer throughput, sensitivity to software modifications, hierarchic timing, I/O granularity, restricted communications, synchronous functions, hierarchic control, and concurrent error detection. A description is presented of the Unified Data System (UDS), which consists of a set of standard microcomputers connected by several buses. Attention is also given to synchronization and timing, the executive control structure, the programming language, and the executive program.

Rennels, D. A.↗
NASA NTRS2022

A Census of Young Stellar Objects in Two Line-of-Sight Star-Forming Regions Toward IRAS 22147+5948 in the Outer Galaxy

Context. Star formation in the outer Galaxy, namely, outside of the Solar circle, has not been extensively studied in part due to the low CO brightness of the molecular clouds linked with the negative metallicity gradient. Recent infrared surveys provide an overview of dust emission in large sections of the Galaxy, but they suffer from cloud confusion and poor spatial resolution at far-infrared wavelengths. Aims. We aim to develop a methodology to identify and classify young stellar objects (YSOs) in star-forming regions in the outer Galaxy and use it to resolve a long-standing disparity in terms of the distance and evolutionary status of IRAS 22147+5948. Methods. We used a support vector machine learning algorithm to complement standard color–color and color–magnitude diagrams in our search for YSOs in the IRAS 22147 region, based on publicly available data from the Spitzer Mapping of the Outer Galaxy survey. The agglomerative hierarchical clustering algorithm was used to identify clusters. Then the physical properties of individual YSOs were calculated. The distances were determined using CO 1–0 from the Five College Radio Astronomy Observatory survey. Results. We identified 13 Class I and 13 Class II YSO candidates using the color–color diagrams, along with an additional 2 and 21 sources, respectively, using the applied machine learning techniques. The spectral energy distributions of 23 sources were modeled with a star and a passive disk, corresponding to Class II objects. The models of three sources include envelopes that are typical for Class I objects. The objects were grouped into two clusters located at a distance of 2:2 kpc and 5 clusters at 5:6 kpc. The spatial extent of CO, radio continuum, and dust emission confirms the origin of YSOs in two distinct star-forming regions along a similar line of sight. Conclusions. The outer Galaxy may serve as a unique laboratory for exploring star formation across environments, on the condition that complementary methods and ancillary data are used to properly account for cloud confusion and distance uncertainties.

Agata Karska↗
NASA NTRS2008

RHSEG and Subdue: Background and Preliminary Approach for Combining these Technologies for Enhanced Image Data Analysis, Mining and Knowledge Discovery

Under a project recently selected for funding by NASA's Science Mission Directorate under the Applied Information Systems Research (AISR) program, Tilton and Cook will design and implement the integration of the Subdue graph based knowledge discovery system, developed at the University of Texas Arlington and Washington State University, with image segmentation hierarchies produced by the RHSEG software, developed at NASA GSFC, and perform pilot demonstration studies of data analysis, mining and knowledge discovery on NASA data. Subdue represents a method for discovering substructures in structural databases. Subdue is devised for general-purpose automated discovery, concept learning, and hierarchical clustering, with or without domain knowledge. Subdue was developed by Cook and her colleague, Lawrence B. Holder. For Subdue to be effective in finding patterns in imagery data, the data must be abstracted up from the pixel domain. An appropriate abstraction of imagery data is a segmentation hierarchy: a set of several segmentations of the same image at different levels of detail in which the segmentations at coarser levels of detail can be produced from simple merges of regions at finer levels of detail. The RHSEG program, a recursive approximation to a Hierarchical Segmentation approach (HSEG), can produce segmentation hierarchies quickly and effectively for a wide variety of images. RHSEG and HSEG were developed at NASA GSFC by Tilton. In this presentation we provide background on the RHSEG and Subdue technologies and present a preliminary analysis on how RHSEG and Subdue may be combined to enhance image data analysis, mining and knowledge discovery.

Tilton, James C.↗
NASA NTRS1994

Compression of regions in the global advanced very high resolution radiometer 1-km data set

The global advanced very high resolution radiometer (AVHRR) 1-km data set is a 10-band image produced at USGS' EROS Data Center for the study of the world's land surfaces. The image contains masked regions for non-land areas which are identical in each band but vary between data sets. They comprise over 75 percent of this 9.7 gigabyte image. The mask is compressed once and stored separately from the land data which is compressed for each of the 10 bands. The mask is stored in a hierarchical format for multi-resolution decompression of geographic subwindows of the image. The land for each band is compressed by modifying a method that ignores fill values. This multi-spectral region compression efficiently compresses the region data and precludes fill values from interfering with land compression statistics. Results show that the masked regions in a one-byte test image (6.5 Gigabytes) compress to 0.2 percent of the 557,756,146 bytes they occupy in the original image, resulting in a compression ratio of 89.9 percent for the entire image.

Kess, Barbara L.↗
NASA NTRSDate not supplied

Comparing Simulation Results from CHARM and RotCFD to the Multirotor Test Bed Experimental Data

Advanced multirotor vertical flight aircraft concepts are emerging faster than rigorous individualized tests can investigate their utility and performance. There are several analysis tools that predict multirotor performance and flow characteristics, but the accuracy of these predictions is still being debated due to lack of experimental data from multirotor tests that are needed to validate the analyses. The objective of this paper is to simulate multirotor configurations using two different mid-fidelity rotorcraft analysis tools, Comprehensive Hierarchical Aeromechanics Rotorcraft Model (CHARM) and Rotorcraft Computational Fluid Dynamics (RotCFD), and compare the simulation results to experimental data from a wind tunnel test of the Multirotor Test Bed (MTB). The MTB, developed by NASA Ames Research Center, is a new capability for testing a wide array of advanced vertical take-off and landing (VTOL) rotor configurations, with a primary focus on testing in the U.S. Army 7-by 10-Foot Wind Tunnel at NASA Ames Research Center. The MTB was designed to allow adjustment of the vertical, lateral, and longitudinal placement of up to six rotors, as well as allow tilt adjustment of each rotor and pitch adjustment of the whole assembly. The six-axis load cells under each rotor give the MTB the capability of measuring the rotor performance in a wide array of configurations. The overall goal of the MTB project is to help gain a better understanding of the performance, control, interactional aerodynamics, and acoustics of multirotor and tilting-rotor systems. For the work presented here, the MTB data were used to validate RotCFD and CHARM results for several multirotor test configurations. With confidence in both analyses established by the validation exercise, additional simulations were performed to explore quadrotor configurations that will be tested during the MTB’s second wind tunnel entry planned for 2022. This second tunnel entry will examine quadrotor configurations that represent published NASA reference designs for urban air mobility concept vehicles. Results from this paper confirm the ability of RotCFD and CHARM to simulate multirotor aerodynamic interactions on individual rotor performance under edgewise forward-flight conditions.

CHARM↗
NASA NTRS1994

The development and validation of command schedules for SeaWiFS

An automated method for developing and assessing spacecraft and instrument command schedules is presented for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) project. SeaWiFS is to be carried on the polar-orbiting SeaStar satellite in 1995. The primary goal of the SeaWiFS mission is to provide global ocean chlorophyll concentrations every four days by employing onboard recorders and a twice-a-day data downlink schedule. Global Area Coverage (GAC) data with about 4.5 km resolution will be used to produce the global coverage. Higher resolution (1.1 km resolution) Local Area Coverage (LAC) data will also be recorded to calibrate the sensor. In addition, LAC will be continuously transmitted from the satellite and received by High Resolution Picture Transmission (HRPT) stations. The methods used to generate commands for SeaWiFS employ numerous hierarchical checks as a means of maximizing coverage of the Earth's surface and fulfilling the LAC data requirements. The software code is modularized and written in Fortran with constructs to mirror the pre-defined mission rules. The overall method is specifically developed for low orbit Earth-observing satellites with finite onboard recording capabilities and regularly scheduled data downlinks. Two software packages using the Interactive Data Language (IDL) for graphically displaying and verifying the resultant command decisions are presented. Displays can be generated which show portions of the Earth viewed by the sensor and spacecraft sub-orbital locations during onboard calibration activities. An IDL-based interactive method of selecting and testing LAC targets and calibration activities for command generation is also discussed.

Woodward, Robert H.↗
NASA NTRS1983

SPP: A data base processor data communications protocol

The design and implementation of a data communications protocol for the Intel Data Base Processor (DBP) is defined. The protocol is termed SPP (Service Port Protocol) since it enables data transfer between the host computer and the DBP service port. The protocol implementation is extensible in that it is explicitly layered and the protocol functionality is hierarchically organized. Extensive trace and performance capabilities have been supplied with the protocol software to permit optional efficient monitoring of the data transfer between the host and the Intel data base processor. Machine independence was considered to be an important attribute during the design and implementation of SPP. The protocol source is fully commented and is included in Appendix A of this report.

Fishwick, P. A.↗
NASA NTRS2008

Mirador: A Simple, Fast Search Interface for Remote Sensing Data

A major challenge for remote sensing science researchers is searching and acquiring relevant data files for their research projects based on content, space and time constraints. Several structured query (SQ) and hierarchical navigation (HN) search interfaces have been develop ed to satisfy this requirement, yet the dominant search engines in th e general domain are based on free-text search. The Goddard Earth Sci ences Data and Information Services Center has developed a free-text search interface named Mirador that supports space-time queries, inc luding a gazetteer and geophysical event gazetteer. In order to compe nsate for a slightly reduced search precision relative to SQ and HN t echniques, Mirador uses several search optimizations to return result s quickly. The quick response enables a more iterative search strateg y than is available with many SQ and HN techniques.

Lynnes, Christopher↗
NASA NTRS2002

Bayesian Hierarchical Air-Sea Interaction Modeling: Application to the Labrador Sea

The objectives are to: 1) Organize data from 26 MINIMET drifters in the Labrador Sea, including sensor calibration and error checking of ARGOS transmissions. 2) Produce wind direction, barometer, and sea surface temperature time series. In addition, provide data from historical file of 150 SHARP drifters in the Labrador Sea. 3) Work with data interpretation and data-modeling assimilation issues.

Niiler, Pearn P.↗
NASA NTRS1982

Yet another method for triangulation and contouring for automated cartography

An algorithm is presented for hierarchical subdivision of a set of three-dimensional surface observations. The data structure used for obtaining the desired triangulation is also singularly appropriate for extracting contours. Some examples are presented, and the results obtained are compared with those given by Delaunay triangulation. The data points selected by the algorithm provide a better approximation to the desired surface than do randomly selected points.

De Floriani, L.↗
NASA NTRS1991

Void statistics of the CfA redshift survey

Clustering properties of two samples from the CfA redshift survey, each containing about 2500 galaxies, are studied. A comparison of the velocity distributions via a K-S test reveals structure on scales comparable with the extent of the survey. The void probability function (VPF) is employed for these samples to examine the structure and to test for scaling relations in the galaxy distribution. The galaxy correlation function is calculated via moments of galaxy counts. The shape and amplitude of the correlation function roughly agree with previous determinations. The VPFs for distance-limited samples of the CfA survey do not match the scaling relation predicted by the hierarchical clustering models. On scales not greater than 10/h Mpc, the VPFs for these samples roughly follow the hierarchical pattern. A variant of the VPF which uses nearly all the data in magnitude-limited samples is introduced; it accounts for the variation of the sampling density with velocity in a magnitude-limited survey.

Vogeley, Michael S.↗
NASA NTRS2018

ESIP Documentation Cluster Session: GCMD Keyword Update

The Global Change Master Directory (GCMD) Keywords are a hierarchical set of controlled Earth Science vocabularies that help ensure Earth science data and services are described in a consistent and comprehensive manner and allow for the precise searching of collection-level metadata and subsequent retrieval of data and services. Initiated over twenty years ago, the GCMD Keywords are periodically analyzed for relevancy and will continue to be refined and expanded in response to user needs. This talk explores the current status of the GCMD keywords, the value and usage that the keywords bring to different tools/agencies as it relates to data discovery, and how the keywords relate to SWEET (Semantic Web for Earth and Environmental Terminology) Ontologies.

data discover↗
NASA NTRSDate not supplied

Generation of Continental Scale Percent Tree Cover Product Using Deep-learning and Multi-scale Remote Sensing Data

Spatially explicit percent tree cover (TC) estimation is critical for mapping forest aboveground biomass and its dynamics. While various TC products have been developed, there has not been a generalized framework that can be applied to diverse terrestrial ecosystems due to underlain extreme complexities. Deep learning algorithms can learn a spatial pattern and radiometric characteristics of tree canopy as a robust approximation of physical or empirical models, and thus have emerged as promising and efficient tools for large-scale TC mapping. In this study, we synergistically use very high-resolution aerial imageries (National Agriculture Imagery Program, NAIP) and medium resolution Landsat data to map continental-scale TC (CONUS and Mexico) through a hierarchical deep learning approach (Convolutional Neural Network), i.e., NAIP TC generated from a NAIP model is utilized to train a Landsat model. The produced TC product (hereafter, NEX-TC) is able to capture the spatial pattern of TC distribution and its changes driven by natural disturbance and human land management. We further explore and analyze the reliability and potential uncertainty of the NEX-TC by comparing it to lidar- (lidar-TC), National Land Cover Database (NLCD-TC), and MODIS Vegetation Continuous Field (MODIS-TC). This evaluation practice reveals that TC products based on passive optical sensors tend to underestimate TC across all land cover types while Landsat-based TCs (i.e., NEX-TC & NLCD-TC) perform better than the coarser MODIS TC estimate. Our results show that the NEX-TC is generally comparable to NLCD-TC but it particularly outperforms NLCD-TC and MODIS-TC over the dense forests where lidar-TC indicates >80% TC. These results indicate that our hierarchical deep learning approach and TC product will be effective and useful for characterizing large-scale tree cover and possibly associated carbon dynamics.

Landsat↗
NASA NTRSDate not supplied

Keywords for All People: How Keyword Governance and Coordination with the NASA ESDIS Standards Coordination Office (ESCO) Improves GCMD Keywords for Discuvery and Use

The Global Change Master Directory (GCMD) Keywords, initiated over twenty years ago, are a hierarchical set of controlled Earth Science vocabularies that help ensure Earth science data, services, and variables are described in a consistent and comprehensive manner and allow for the precise searching of metadata and subsequent retrieval of data, services, and variables. GCMD keywords are periodically analyzed for relevancy and will continue to be refined and expanded in response to user needs. The periodic analysis is a result of successful coordination with the ESDIS Standards Coordination Office (ESCO), which is responsible for standards activities across ESDIS, and assists with providing valuable stakeholder and subject matter expert (SME) feedback on GCMD vocabularies. The ESCO is also turning to the GCMD to discuss how the keyword review process can be improved and more streamlined. In addition to the ESCO, keyword requests and feedback are also received through the GCMD Keyword Forum.

Tyler Stevens↗
NASA NTRSDate not supplied

MAPL3: A Hierarchical Framework Based on ESMF

MAPL is a hierarchical, ESMF-based, coupling framework developed to support NASA's GEOS data assimilation system, but also now supports some external applications from partner institutions. The framework continues to evolve in response novel coupling requirements and is currently undergoing a substantial re-engineering effort to improve extensibility and maintainability. Some of the major new features that will be provided in the upcoming release of MAPL3 include the following: (1) "weak" NUOPC compliance that expresses a MAPL hierarchy as single NUOPC model, (2) component extensions that represent an improvement over conventional component couplers in many contexts, (3) an expansion of the concept of import and export to include component "services" such as advection, turbulence, etc., (4) automated OpenMP threading of column-based component subtrees, (5) and (5) improved I/O scalability.

GEOS↗
NASA NTRS2020

Bayesian Statistical Models for Community Annoyance Survey Data

This paper demonstrates the use of two Bayesian statistical models to analyze single-event sonic boom exposure and human annoyance data from community response surveys. Each model is fit to data from a NASA pilot study.Unlike many community noise surveys, this study used a panel sample to collect multiple observations per participant instead of a single observation. Thus, a multilevel (also known as hierarchical or mixed-effects) model is used to account for the within-subject correlation in the panel sample data. This paper describes a multilevel logistic regression model and a multilevel ordinal regression model. The paper also proposes a method for calculating a summary dose-response curve from the multilevel models that represents the population. The two models’ summary dose-response curves are visually similar. However, their estimates differ when calculating the noise dose at a fixed percent highly annoyed.

Musical instruments↗
NASA NTRS1981

Generic functional requirements for a NASA general-purpose data base management system

Generic functional requirements for a general-purpose, multi-mission data base management system (DBMS) for application to remotely sensed scientific data bases are detailed. The motivation for utilizing DBMS technology in this environment is explained. The major requirements include: (1) a DBMS for scientific observational data; (2) a multi-mission capability; (3) user-friendly; (4) extensive and integrated information about data; (5) robust languages for defining data structures and formats; (6) scientific data types and structures; (7) flexible physical access mechanisms; (8) ways of representing spatial relationships; (9) a high level nonprocedural interactive query and data manipulation language; (10) data base maintenance utilities; (11) high rate input/output and large data volume storage; and adaptability to a distributed data base and/or data base machine configuration. Detailed functions are specified in a top-down hierarchic fashion. Implementation, performance, and support requirements are also given.

Lohman, G. M.↗