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At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

NASA NTRS2012

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid. This record will be elevated in status to a CDR when at least nine more years of data become available either from MODIS Terra or Aqua, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Our ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the VIIRS era. Differences in the APP and MODIS cloud masks have so far precluded the current 1ST records from spanning both the APP and MODIS time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The complete MODIS 1ST daily and monthly data record is available online.

Hall, Dorothy K.↗

DOE OSTI2024

Hydra: computer vision for data quality monitoring

Hydra, initially developed for Hall-D in 2019, is a system that utilizes computer vision to perform near real time data quality monitoring. Since then, it has been deployed across all experimental halls at Jefferson Lab, with the CLAS12 collaboration in Hall-B being the first outside of GlueX to fully utilize Hydra. The system comprises back end processes that manage the models, their inferences, and the data flow. Finally, the front-end components, accessible via web pages, allow detector experts and shift crews to view and interact with the system.

47 OTHER INSTRUMENTATION↗

NASA NTRS1998

Data Quality of the JERS-1 SAR Global Rain Forest Mapping (GRFM) Project

The National Space Development Agency of Japan's (NASDA) JERS-1 SAR began collecting data in 1995 for the Global Rain Forest Mapping Project (GRFM). The GRFM data quality has been examined for products resulting from both the NASDA and Alaska SAR facility's (ASF) processing facilities.

JERS-1 SAR Rain Forest Mapping↗

NASA NTRS2018

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

The NASA Space Launch System Block 1 launch vehicle is equipped with an Inertial Navigation System (INS) and multiple Rate Gyro Assemblies (RGA) that are used in the Guidance, Navigation, and Control (GN&C) algorithms. The INS provides the inertial position, velocity, and attitude of the vehicle along with both angular rate and specific force measurements. Additionally, multiple sets of co-located rate gyros supply angular rate data. The collection of angular rate data, taken along the launch vehicle, is used to separate out vehicle motion from flexible body dynamics. Since the system architecture uses redundant sensors, the capability was developed to evaluate the health (or validity) of the independent measurements. A suite of Sensor Data Quality (SDQ) algorithms is responsible for assessing the angular rate data from the redundant sensors. When failures are detected, SDQ will take the appropriate action and disqualify or remove faulted sensors from forward processing. Additionally, the SDQ algorithms contain logic for down-selecting the angular rate data used by the GNC software from the set of healthy measurements. This paper explores the trades and analyses that were performed in selecting a set of robust fault-detection algorithms included in the GN&C flight software. These trades included both an assessment of hardware-provided health and status data as well as an evaluation of different algorithms based on time-to-detection, type of failures detected, and probability of detecting false positives. We then provide an overview of the algorithms used for both fault-detection and measurement down selection. We next discuss the role of trajectory design, flexible-body models, and vehicle response to off-nominal conditions in setting the detection thresholds. Lastly, we present lessons learned from software integration and hardware-in-the-loop testing.

Park, Thomas↗

NASA NTRS2018

Sensor Data Quality and Angular Rate Down-Selection Algorithms on SLS EM-1

Park, Thomas↗

DOE OSTI2024

Characterization of Non-Science Grade DESI CCDs and Creating Additional ICARUS Monitoring Metrics for Data Quality

DESI, otherwise known as the Dark Energy Spectroscopic Instrument, is an astronomical project measuring millions of optical spectra to characterize Dark Energy. The survey has been running for 3 years. My work delves into the data taking/analysis side of the DESI CCDs (Charge-Coupled Devices) which will help in swapping out broken CCDs on the instrument. Additionally, I worked on making new metrics for ICARUS, Imaging Cosmic and Rare Underground Signals for their monitoring of run data. This paper will talk about the types of characterizations done for DESI and additional metrics for data quality and tools used for ICARUS monitoring.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

PMU Data Quality and Sensor Health Monitoring

Phasor Measurement Units (PMUs) play a critical role in the evolution of the electric power industry by providing high-precision, real-time monitoring of essential power system metrics. However, effectively detecting abnormalities and critical events from PMU data is a complex task, complicated by intricate temporal patterns, a scarcity of labeled data for training algo- rithms, and constraints on online computational power. In this study, we apply TranAD, an innovative algorithm that combines transformer architectures with the refinement of adversarial learning, to both synthetic and real-world PMU datasets for developing a data quality and sensor online health monitoring platform for utilities. Our findings reveal that TranAD not only provides efficient detection and localization but also enhances the detail with which abnormalities are detected, marking a a significant step forward in the field of clean data acquisition processes for power system monitoring

deep neural network, machine learning (ML)↗

NASA NTRSDate not supplied

Creating and Using Open Global and Local Air Quality Data at NASA GMAO

Air quality is the leading environmental health concern.

air quality↗

NASA NTRS1985

LANDSAT TM image data quality analysis for energy-related applications

This project represents a no-cost agreement between National Aeronautic Space Administration Goddard Space Flight Center (NASA GSFC) and the Pacific Northwest Laboratory (PNL). PNL is a Department of Energy (DOE) national laboratory operted by Battelle Memorial Institute at its Pacific Northwest Laboratories in Richland, Washington. The objective of this investigation is to evaluate LANDSAT's thematic mapper (TM) data quality and utility characteristics from an energy research and technological perspective. Of main interest is the extent to which repetitive TM data might support DOE efforts relating to siting, developing, and monitoring energy-related facilities, and to basic geoscientific research. The investigation utilizes existing staff and facility capabilities, and ongoing programmatic activities at PNL and other DOE national laboratories to cooperatively assess the potential usefulness of the improved experimental TM data. The investigation involves: (1) both LANDSAT 4 and 5 TM data, (2) qualitative and quantitative use consideration, and 3) NASA P (corrected) and A (uncorrected) CCT analysis for a variety of sites of DOE interest. Initial results were presented at the LANDSAT Investigator's Workshops and at specialized LANDSAT TM sessions at various conferences.

Wukelic, G. E.↗

NASA NTRS1986

Multi-station lunar laser ranging - An analysis of data quality and earth rotation results

The lunar laser ranging (LLR) results obtained from the MERIT period (Sept. 1983 through Oct. 1984) as well as from the post-MERIT period (Nov. 1, 1984 through Aug. 12, 1985) are presented. The ranging targets on the moon include the Apollo 11, 14, and 15 reflectors and a reflector on Lunokhod 2; the LLR network includes McDonald, Texas; CERGA, France; Haleakala, Hawaii; Orroral, Australia; and Crimea, USSR, stations. Data acquired with these systems are reported, and the data quality is assessed, with particular emphasis on recent ranges. During the MERIT period, sixty-five earth rotation values (UTO) were derived from LLR data, with the best accuracy being 0.25 msec; during the post-MERIT period, 115 determinations of UTO were calculated with the best inherent accuracy of about 0.1 msec. The results are compared with those from other techniques.

Dickey, J. O.↗

NASA NTRS1998

Data Quality Assessment Methods for the Eastern Range 915 MHz Wind Profiler Network

The Eastern Range installed a network of five 915 MHz Doppler Radar Wind Profilers with Radio Acoustic Sounding Systems in the Cape Canaveral Air Station/Kennedy Space Center area to provide three-dimensional wind speed and direction and virtual temperature estimates in the boundary layer. The Applied Meteorology Unit, staffed by ENSCO, Inc., was tasked by the 45th Weather Squadron, the Spaceflight Meteorology Group, and the National Weather Service in Melbourne, Florida to investigate methods which will help forecasters assess profiler network data quality when developing forecasts and warnings for critical ground, launch and landing operations. Four routines were evaluated in this study: a consensus time period check a precipitation contamination check, a median filter, and the Weber-Wuertz (WW) algorithm. No routine was able to effectively flag suspect data when used by itself. Therefore, the routines were used in different combinations. An evaluation of all possible combinations revealed two that provided the best results. The precipitation contamination and consensus time routines were used in both combinations. The median filter or WW was used as the final routine in the combinations to flag all other suspect data points.

Lambert, Winifred C.↗

NASA NTRS1975

LANDSAT-1 data as it has been applied for land use and water quality data by the Virginia State Water Control Board. 1: The state project. 2: Monitoring water quality from LANDSAT

LANDSAT-1 imagery has been used for water quality and land use monitoring in and around the Swift Creek and Lake Chesdin Reservoirs in Virginia. This has proved useful by (1) helping determine valid reservoir sampling stations, (2) monitoring areas not accessible by land or water, (3) giving the State a viable means of measuring Secchi depth readings in these inaccessible areas, (4) giving an overview of trends in changing sedimentation loadings over a given time period and classifying these waters into various categories, (5) enabling the State to inventory all major lakes and reservoirs and computing their acreage, (6) monitoring land use changes in any specific area, (7) evaluating possible long-term environmental effects of nearby developments, and (8) monitoring and predicting population shifts with possible impact on water quality problems. The main problems in the long-term use of such imagery appear to be cost and lack of consistency due to cloud cover limitations.

Trexler, P. L.↗

NASA NTRS2011

Effects of Data Quality on the Characterization of Aerosol Properties from Multiple Sensors

Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.

Petrenko, Maksym↗

NASA NTRS2010

Ares I-X Launch Vehicle Modal Test Measurements and Data Quality Assessments

The Ares I-X modal test program consisted of three modal tests conducted at the Vehicle Assembly Building at NASA s Kennedy Space Center. The first test was performed on the 71-foot 53,000-pound top segment of the Ares I-X launch vehicle known as Super Stack 5 and the second test was performed on the 66-foot 146,000- pound middle segment known as Super Stack 1. For these tests, two 250 lb-peak electro-dynamic shakers were used to excite bending and shell modes with the test articles resting on the floor. The third modal test was performed on the 327-foot 1,800,000-pound Ares I-X launch vehicle mounted to the Mobile Launcher Platform. The excitation for this test consisted of four 1000+ lb-peak hydraulic shakers arranged to excite the vehicle s cantilevered bending modes. Because the frequencies of interest for these modal tests ranged from 0.02 to 30 Hz, high sensitivity capacitive accelerometers were used. Excitation techniques included impact, burst random, pure random, and force controlled sine sweep. This paper provides the test details for the companion papers covering the Ares I-X finite element model calibration process. Topics to be discussed include test setups, procedures, measurements, data quality assessments, and consistency of modal parameter estimates.

Templeton, Justin D.↗

NASA NTRS2021

From Low-Cost Sensors to High-Quality Data: A Review of Challenges and Summary of Best Practices for Effectively Using Low-Cost Particulate Matter Mass Sensors

Low-cost sensors for particulate matter mass (PM) enable spatially dense, high temporal resolution measurements of air quality that traditional reference monitoring cannot. Low-cost PM sensors are especially beneficial in low and middle-income countries where few, if any, reference grade measurements exist and in areas where the concentration fields of air pollutants have significant spatial gradients. Unfortunately, low-cost PM sensors also come with a number of challenges that must be addressed if their data products are to be used for anything more than a qualitative characterization of air quality. The various PM sensors used in low-cost monitors are all subject to biases and calibration dependencies, corrections for which range from relatively straightforward(e.g. meteorology, age of sensor) to complex (e.g. aerosol source, composition, refractive index). The methods for correcting and calibrating these biases and dependencies that have been used in the literature likewise range from simple linear and quadratic models to complex machine learning algorithms. Here we review the needs and challenges when trying to get high-quality data from low-cost sensors. We also present a set of best practices to follow to obtain high-quality data from these low-cost sensors.

low-cost sensors↗

NASA NTRS1971

An assessment of remote sensor imagery in the determination of housing quality data

Selected census tracts in the metropolitan Washington area were examined using varying scales of aerial photography. Observable characteristics of housing and neighborhoods were assessed to determine feasibility of providing data on housing stock and quality and neighborhood condition from the imagery. Small scale imagery is shown to be of relatively marginal value in providing much of the data in the detail required, but can be useful for general survey purposes.

Mallon, H. J.↗

NASA NTRSDate not supplied

Air Quality Data Fusion with Sensors, Satellites, and Models

Poor air quality is a major global public health concern, which is only projected to get worse in coming years. A comprehensive understanding of current and potential future air quality and its key drivers spanning from local to global scales is needed to tackle this important problem. This presentation will outline the sources of information that we use to understand air quality, including ground-based measurements, satellites, and models. After giving an overview of these data sources and outlining their strengths and limitations, we will take a look at how they can be used together to give us a better picture of air quality locally and globally with data fusion techniques.

Carl Malings↗

NASA NTRS1986

Seven years of total ozone from the TOMS instrument - A report on data quality

Seven years of TOMS total ozone data are currently available. Recently a new ozone retrieval algorithm based on improved ozone absorption cross section was implemented that has introduced 6-7 percent discontinuity in the archived data sets at the end of the fifth year of instrument operation. Until all data are reprocessed with the new algorithm users can use a table of correction factors given in this paper to make the data set internally consistent. This paper also presents a comparison of TOMS results with Amundsen Scott Dobson station. Though the agrement in most years is good, in 1983-84 the Dobson station reported unusually high values of ozone while TOMS saw the very low ozone values associated with the Antarctica ozone hole.

Fleig, Albert J.↗