Analysis of multi-sensor data, 12 September - 11 December 1968
Analysis of multi-sensor data obtained by Earth Resources Aircraft Program
Bay, C. A.↗
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Analysis of remote sensing data collected for detection and mapping of oil spills: Reduction and analysis of multi-sensor airborne data of the NASA Wallops oil spill exercise of November 1978
Airborne, remotely sensed data of the NASA Wallops controlled oil spill were corrected, reduced and analysed. Sensor performance comparisons were made by registering data sets from different sensors, which were near-coincident in time and location. Multispectral scanner images were, in turn, overlayed with profiles of correlation between airborne and laboratory-acquired fluorosensor spectra of oil; oil-thickness contours derived (by NASA) from a scanning fluorosensor and also from a two-channel scanning microwave radiometer; and synthetic aperture radar X-HH images. Microwave scatterometer data were correlated with dual-channel (UV and TIR) line scanner images of the oil slick.
Source record↗
Geographic analysis of multiple sensor data from the NASA/USGS earth resources program
Qualitative and quantitative analyses were made of multi-sensor data acquired during aircraft missions. While the principal analysis effort was concentrated on imagery taken over test sites in Southern California, data were also studied from records acquired on missions over test sites at Phoenix, Chicago, Asheville, and New Orleans. The objectives of the analyses were: (1) to determine the capabilities of ten remote sensors in identifying the elements of information necessary in conducting geographic investigations in land use analysis, urban problems, surface energy budget, and soil moisture; (2) to determine the feasibility of using these sensors for these purposes at orbital altitudes; and (3) to collate and analyze ground and air data previously collected and assemble it in a format useful in the accomplishment of cost effectiveness studies.
Pascucci, R. F.↗
Training site statistics from Landsat and Seasat satellite imagery registered to a common map base
Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.
Clark, J.↗
Sea ice-atmosphere interaction: Application of multispectral satellite data in polar surface energy flux estimates
The application of multi-spectral satellite data to estimate polar surface energy fluxes is addressed. To what accuracy and over which geographic areas large scale energy budgets can be estimated are investigated based upon a combination of available remote sensing and climatological data sets. The general approach was to: (1) formulate parameterization schemes for the appropriate sea ice energy budget terms based upon the remotely sensed and/or in-situ data sets; (2) conduct sensitivity analyses using as input both natural variability (observed data in regional case studies) and theoretical variability based upon energy flux model concepts; (3) assess the applicability of these parameterization schemes to both regional and basin wide energy balance estimates using remote sensing data sets; and (4) assemble multi-spectral, multi-sensor data sets for at least two regions of the Arctic Basin and possibly one region of the Antarctic. The type of data needed for a basin-wide assessment is described and the temporal coverage of these data sets are determined by data availability and need as defined by parameterization scheme. The titles of the subjects are as follows: (1) Heat flux calculations from SSM/I and LANDSAT data in the Bering Sea; (2) Energy flux estimation using passive microwave data; (3) Fetch and stability sensitivity estimates of turbulent heat flux; and (4) Surface temperature algorithm.
Steffen, K.↗
Hybrid approach to data reduction for multi-sensor hot wires
A hybrid approach to implementing the calibration equations for a multisensor hot-wire probe is discussed. The approach combines some of the speed of a look-up approach with the moderate storage requirements of direct calculation based on functional fitting. Particular attention is given to timing and storage comparisons for an X-wire probe. The method depends on the oft-employed concept of an effective cooling velocity which is a function only of the bridge output voltage.
Hooper, C. L.↗
A multi-sensor analysis of Nimbus 5 data on 22 January 1973
The Nimbus 5 meteorological satellite carried aloft a full complement of radiation sensors, the data from which were analyzed and intercompared during orbits 569-570 on 22 January 1973. The electrically scanning microwave radiometer (ESMR) which sensed passive microwave radiation in the 19.35 GHz region, delineated rain areas over the ocean off the U.S. east coast, in good agreement with WSR-57 and FPS-77 radar imagery and permitted the estimation of rainfall rates in this region. Residual ground water in the lower Mississippi Valley, which resulted from abnormal rainfall in previous months, was indicated under clear sky conditions by soil brightness temperature values in the Nimbus 5 ESMR and U.S. Air Force Data Acquisition and Processing Program (DAPP) IR data. The temperature-humidity infrared radiometer showed the height and spatial configuration of frontal clouds along the east coast and outlined the confluence of a polar jet stream with a broad sub-tropical jet stream along the U.S. Gulf Coast. Temperature profiles from three vertical temperature sounders, the infrared temperature profile radiometer (ITPR), the Nimbus E microwave spectrometer (NEMS) and the selective chopper radiometer (SCR) were found to be in good agreement with related radiosonde ascents along orbit 569 from the sub-tropics to the Arctic Circle.
Allison, L. J.↗
Filtering algorithms for processing prefiltered measurements
The filtering algorithm for processing integral measurements is extended to include analog type prefilters with infinite memory, and to include sequential processing of prefiltered data in multi-sensor, multi-sample rate systems. The extension to infinite memory prefilters requires serial decorrelation of the prefilter output prior to state estimation. These algorithms provide a technique for investigation of prefilter parameter sensitivities, and provide optimal compensation for any information loss due to prefiltering.
Warren, A. W.↗
Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder
Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.
Mahyar Garshasbi↗
The response function of modulated grid Faraday cup plasma instruments
Modulated grid Faraday cup plasma analyzers are a very useful tool for making in situ measurements of space plasmas. One of their great attributes is that their simplicity permits their angular response function to be calculated theoretically. An expression is derived for this response function by computing the trajectories of the charged particles inside the cup. The Voyager Plasma Science (PLS) experiment is used as a specific example. Two approximations to the rigorous response function useful for data analysis are discussed. The theoretical formulas were tested by multi-sensor analysis of solar wind data. The tests indicate that the formulas represent the true cup response function for all angles of incidence with a maximum error of only a few percent.
Barnett, A.↗
Reliability measurement during software development
Measurement of software reliability was carried out during the development of data base software for a multi-sensor tracking system. Every run made during this project was scored as success or failure, and supporting data were collected on forms for further analysis. The failure ratio (number of failures per calendar interval divided by total number of runs) and failure rate (number of failures divided by CPU time for the interval) were found to be consistent measures, on a month-to-month basis as well as from module to module, and therefore considered valid indicators of reliability in this environment. Trend lines could be established from these measurements that provide good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the specific run submission rather than with the code proper.
Hecht, H.↗
The determination of measures of software reliability
Measurement of software reliability was carried out during the development of data base software for a multi-sensor tracking system. The failure ratio and failure rate were found to be consistent measures. Trend lines could be established from these measurements that provide good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the individual run submission rather than with the code proper. Possible application of these findings for line management, project managers, functional management, and regulatory agencies is discussed. Steps for simplifying the measurement process and for use of these data in predicting operational software reliability are outlined.
Maxwell, F. D.↗
Reliability measurement during software development
During the development of data base software for a multi-sensor tracking system, reliability was measured. The failure ratio and failure rate were found to be consistent measures. Trend lines were established from these measurements that provided good visualization of the progress on the job as a whole as well as on individual modules. Over one-half of the observed failures were due to factors associated with the individual run submission rather than with the code proper. Possible application of these findings for line management, project managers, functional management, and regulatory agencies is discussed. Steps for simplifying the measurement process and for use of these data in predicting operational software reliability are outlined.
Hecht, H.↗
Intelligent multi-sensor integrations
Growth in the intelligence of space systems requires the use and integration of data from multiple sensors. Generic tools are being developed for extracting and integrating information obtained from multiple sources. The full spectrum is addressed for issues ranging from data acquisition, to characterization of sensor data, to adaptive systems for utilizing the data. In particular, there are three major aspects to the project, multisensor processing, an adaptive approach to object recognition, and distributed sensor system integration.
Volz, Richard A.↗
Agricultural requirements for precipitation measurements
The requirements for precipitation measurements from space for hydrologic forecasting applications are discussed. The structure of the hydrologic forecasting service of the National Weather Service (NWS) is described, and an attempt is made to estimate the sampling and accuracy requirements for a range of spatial and temporal averaging scales corresponding to various NWS hydrologic applications. Finally, the data base requirements are addressed. The critical point is made that for the data source to be most useful operationally at the NWS River Forecast Centers, the data must be available on-line in a format compatible with computer processing. Several data base systems are illustrated in a scenario for a multi-sensor rainfall analysis system (MSRANS). Actually, MSRANS is the software existing within the various computer environments required to preprocess, process, and analyze rainfall information from multiple sources.
Strommen, N. D.↗
Geologic mapping in Death Valley, California/Nevada using NASA/JPL airborne systems (AVIRIS, TIMS, and AIRSAR)
A multi-sensor aircraft campaign called the Geologic Remote Sensing Field Experiment (GRSFE) conducted during 1989 resulted in acquisition of high quality multispectral images in the visible, near infrared, shortwave infrared, thermal infrared, and microwave regions of the electromagnetic spectrum. The airborne data sets include the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), the Thermal Infrared Multispectral Scanner (TIMS), and the Airborne Synthetic Aperture Radar (SAR). Ancillary data include Landsat Thematic Mapper, laboratory and field spectral measurements, and traditional geologic mapping. The GRSFE data for a site in the northern Death Valley, (California and Nevada) region were calibrated to physical units and geometrically registered to a map base. Various aspects of this experiment are briefly discussed.
Kruse, Fred A.↗
L band push broom microwave radiometer: Soil moisture verification and time series experiment Delmarva Peninsula
The verification of a multi-sensor aircraft system developed to study soil moisture applications is discussed. This system consisted of a three beam push broom L band microwave radiometer, a thermal infrared scanner, a multispectral scanner, video and photographic cameras and an onboard navigational instrument. Ten flights were made of agricultural sites in Maryland and Delaware with little or no vegetation cover. Comparisons of aircraft and ground measurements showed that the system was reliable and consistent. Time series analysis of microwave and evaporation data showed a strong similarity that indicates a potential direction for future research.
Jackson, T. J.↗
Space shuttle post-entry and landing analysis. Volume 1: Candidate system evaluations
The general purpose of this study is to aid in the evaluation and design of multi-sensor navigation schemes proposed for the orbiter. The scope of the effort is limited to the post-entry, energy management, and approach and landing mission phases. One candidate system based on conventional navigation aids is illustrated including two DME (Distance Measuring Equipment) stations and ILS (Instrument Landing System) glide slope and localizer antennas. Some key elements of the system not shown are the onboard IMUs (Inertial Measurement Units), altimeters, and a computer. The latter is programmed to mix together (filter) the IMU data and the externally-derived data. A completely automatic, all-weather landing capability is required. Since no air-breathing engines will be carried on orbital flights, there will be no chance to go around and try again following a missed approach.
Crawford, B. S.↗