SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Near-simultaneous AIRSAR and Landsat TM data are used, along with radar scattering models and optical regression-based models, to estimate vegetation variables for a mixed old-growth dense forest in the US Pacific Northwest.
Explore the source record for details and available documents.
Bidirectional respiratory flowmeters and electronic instrumentation technology for measurement and analysis of metabolic quantities
A hardware interface which allows both digital and analog data output from the JOLT microcomputer is described in the context of a software-based Omega Navigation receiver. The interface hardware described is designed for output of six (or eight with simple extensions) bits of binary output in response to a memory store command from the microcomputer. The interface was produced in breadboard form and is operational as an evaluation aid for the software Omega receiver.
The LANDSAT Follow-On (LFO) data was simulated to demonstrate the mineral exploration capability of this system for segregating different types of hydrothermal alteration and to compare this capability with that of the existing LANDSAT system. Multispectral data were acquired for several test sites with the Bendix 24-channel MSDS scanner. Contrast enhancements, band ratioing, and principal component transformations were used to process the simulated LFO data for analysis. For Red Mountain, Arizona, the LFO data allowed identification of silicified areas, not identifiable with LANDSAT 1 and 2 data. The improved LFO resolution allowed detection of small silicic outcrops and of a narrow silicified dike. For Cuprite - Ralston, Nevada, the LFO spectral bands allowed discrimination of argillic and opalized altered areas; these could not be spectrally discriminated using LANDSAT 1 and 2 data. Addition of data from the 1.3- and 2.2- micrometer regions allowed better discriminations of hydrothermal alteration types.
Techniques and software developed to characterize the Washington, D.C. scene were improved and are being systematically applied to an Imperial Valley, CA scene. Digital elevation files are being acquired. One hundred seventy-two tiepoints were located in the Imperial Valley scene. They were digitized from USGS maps to determine their lat-long coordinates. A least squares fit is currently being performed between line-sample image data and the lat-long positions of the tiepoints. Thematic mapper scanner sweeps were determined for the Imperial Valley P-data. VICAR jobs are currently under way to analyze sample-direction offsets between sweeps in the data, as well as band to band registration offsets. Tiepoint location is about to begin in the Harrisburg, PA scene.
In order to verify that the LANDSAT-4 sensors are operating within specifications, it is useful to estimate the system parameters by analysis of the measured data. One parameter of particular interest is the sensor point-spread function (PSF) which determines the resolution of the system. A method of estimating the PSF is described that utilizes data obtained during scanning of ground elements having identifiable geometric and radiometric structure. These data are then processed in such a manner as to recover either the PSF itself or to estimate the parameters of an assumed functional representation of the PSF.
An evaluation is presented of the supervised vegetation classification images of heavily forested terrain in the eastern US produced from simulated Landsat-D Thematic Mapper data as part of the Joint NASA/Geosat Test Case study of the Lost River, West Virginia, gas field. This investigation utilized data supplied by the NS-001 aircraft multispectral scanner (15 m IFOV) of NASA. The instruments recognized a total of 9 vegetation classes and one soil class. A hybrid parallelepiped-Bayesian maximum likelihood classifier was employed to produce the supervised vegetation classifications. The data were obtained at the height of the fall foliage display for this portion of West Virginia. Results show that both classifications are highly accurate, based on a comparison of assignment of vegetation classes on each of the images with actual ground conditions. It is noted that the anomalous distribution of certain woody species found in the resulting supervised classifications may be related to the microseepage of methane from the gas reservoir.
LANDSAT thematic mapper P-data of Washington, D.C., Harrisburg, PA, and Salton Sea, CA were analyzed to determine magnitudes and causes of error in the geometric conformity of the data to known earth-surface geometry. Several tests of data geometry were performed. Intra-band and inter-band correlation and registration were investigated, exclusive of map-based ground truth. Specifically, the magnitudes and statistical trends of pixel offsets between a single band's mirror scans (due to processing procedures) were computed, and the inter-band integrity of registration was analyzed.
Simultaneous data acquisition by the LANDSAT 4 thematic mapper and the multispectral scanner permits the comparison of the two types of image data with respect to engineering performance and data applications. Progress in the evaluation of information content of matching scenes in agricultural areas is briefly reported.
The initial objectives of analyses of the MSS data are two-fold: (1) to evaluate the geodetic accuracy of CCT-P data of the test sites; and (2) to improve the geodetic accuracy by additional processing if the original data either do not meet pre-launch specifications or mapping requirements. The location of 45 ground control points (GCP) digitized from 35 U.S. Geological Survey 1:24,000 scale quadrangles (UTM coordinates) were identified in terms of pixel and scan line values. These 46 points are used to establish UTM position error vector distributions in the scene. As an initial check on the geometric reliability of the MSS data, 28 well-distributed GCPs were input to a program which compares the scaled image distances between all possible point pairs with the corresponding map distances and computes the distance differences; that is, the relative positional errors. The relative errors obtained from initial computations averaged about +/- 200 m. These errors could result from a number of sources, including misidentification of GCP locations, UTM coordinate errors introduced by the map digitizing process or errors resulting from data acquisition and geometric processing.
Tables and graphs show the results of the spectral, radiometric, and geometric characterization of LANDSAT 4 sensors associated with imagery and of the imagery associated with sensors and processing. Specifications for the various parameters are compared with the photoflight and flight values.
Rectifications of multispectral scanner and thematic mapper data sets for full and subscene areas, analyses of planimetric errors, assessments of the number and distribution of ground control points required to minimize errors, and factors contributing to error residual are examined. Other investigations include the generation of three dimensional terrain models and the effects of spatial resolution on digital classification accuracies.
A detailed spectral analysis is conducted of thematic mapper and MSS data for an area near Des Moines, Iowa. Data are utilized from 7 blocks distributed throughout the area which included agricultural, forest, suburan, urban, and water scene types. The blocks are processed using a clustering algorithm to produce up to 18 cluster groupings for each block. Each cluster class is then identified with a ground-cover class using aerial photography and maps of the area. The clusters from each of the 7 blocks are inspected with regard to separability, mean, and variances. The separability measure used in the transformed divergence function or processor measures the statistical distance between classes based on class means and covariance matrices. The measure has a maximum value of 2,000 and the minimum of 0. Spectrally, very close classes will typically have values as low as 50 to 500.
Some of the LANDSAT 4 Thematic Mapper detectors (band 2 detector 4 and band 5 detector 3) have inadequate performances. The operational system correction processing will disregard the data sensed by the failed detectors and replace them by data coming from the neighbor detectors of the same spectra band. The analysis performed by ESA Earthnet and attempts to suggest an operational failed detector replacement algorithm are described.
Lithologic mapping techniques using the near infrared bands of the Thematic Mapper onboard the LANDSAT 4 satellite are investigated. These methods are coupled with digital masking to test the capability of mapping geologic materials. Data are examined under medium to low Sun angle illumination conditions to determine the detection limits of materials with absorption features. Several detection anomalies are observed and explained.
Experiments to determine overall radiometric resolution are discussed. Scene structures, such as roads and field edges, are used with numerical estimation procedures to predict resolution in LANDSAT 4 Thematic Mapper imagery. A nominal resolution of 39 meters is determined rather than the predicted 30 meter prelaunch estimates.
The enroute noise of an Advanced Turboprop powered aircraft was estimated. The measured noise levels were roughly equivalent in annoyance to the noise 15.24 m from an automobile traveling at 80 km/h. It is felt that these levels would not illicit noise complaints from urban areas during the day but might be a slight annoyance in rural areas or in urban areas at night. Although it is not felt that the enroute noise is a major problem, it is indicated that a reduction in the enroute noise could improve the acceptability of advance turboprop airplanes.