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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.

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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1973

A semi-automated system for plotting and computer cataloging of remote sensing imagery

Description of a computer-assisted system for plotting and descriptor-cataloging of aerial imagery - an ingredient of the aerial image data handling system of the NASA Earth Resources Aircraft Project (ERAP). The system under consideration uses two graphic tablets linked interactively with a digital computer as input devices for deriving frame coordinates by correlating image points to map points. The various software programs and operating modes facilitate a semiautomatic plotting of an image by selecting two or more points within the image for matching with map details. The computer performs the scaling and orientation transformations for the calculation of the center and corner coordinates of the frame. Twenty five other descriptors for each frame are fed into a computerized data base requiring a minimum operator's time for verification and correction.

Gnauck, G. E.↗
NASA NTRS1975

Stream network analysis and geomorphic flood plain mapping from orbital and suborbital remote sensing imagery application to flood hazard studies in central Texas

The author has identified the following significant results. Development of a quantitative hydrogeomorphic approach to flood hazard evaluation was hindered by (1) problems of resolution and definition of the morphometric parameters which have hydrologic significance, and (2) mechanical difficulties in creating the necessary volume of data for meaningful analysis. Measures of network resolution such as drainage density and basin Shreve magnitude indicated that large scale topographic maps offered greater resolution than small scale suborbital imagery and orbital imagery. The disparity in network resolution capabilities between orbital and suborbital imagery formats depends on factors such as rock type, vegetation, and land use. The problem of morphometric data analysis was approached by developing a computer-assisted method for network analysis. The system allows rapid identification of network properties which can then be related to measures of flood response.

Baker, V. R.↗
NASA NTRS1977

Photomorphic analysis techniques: An interim spatial analysis using satellite remote sensor imagery and historical data

The use of machine scanning and/or computer-based techniques to provide greater objectivity in the photomorphic approach was investigated. Photomorphic analysis and its application in regional planning are discussed. Topics included: delineation of photomorphic regions; inadequacies of existing classification systems; tonal and textural characteristics and signature analysis techniques; pattern recognition and Fourier transform analysis; and optical experiments. A bibliography is included.

Keuper, H. R.↗
NASA NTRS1980

Applications of remote-sensing imagery

Compilation of reports discusses usefulness of aircraft and satellite data in land-development projects. Landsat and Earth Resources Technology Satellites data are available to general public. Much information on biological, geological, and hydrological features as well as land use can be determined by eye without sophisticated analyzers.

Hughes, T. H.↗
NASA NTRS1984

Registration of a synthetic aperture radar image to Thematic Mapper imagery for remote sensing applications

Multiple Thematic Mapper multitemporal acquisitions from Landsat and one synthetic-aperture radar acquisition from Seasat have been precisely registered using Johnson Space Center registration processors. The registered images have been output in the Universal Transverse Mercator projection. The procedure to accomplish such disparate data processing tasks and the registration accuracy evaluation are discussed.

Yao, S. S.↗
NASA NTRS1985

Strategies for analyzing mixed pixels in remotely sensed imagery

Two uncalibrated synthetic aperture radar (SAR) scenes from Death Valley, California, and two uncalibrated scenes from Owens Valley, California, were used to test a technique to identify and separate the primary factors associated with multipolarized radar image sets. Unique to the technique is the concept that varied types of radar polarization signatures are a result of the interaction of a few physical factors (e.g., roughness, volume scattering, and dielectric constant). Thus, the varied signatures observed in an image reflect the interaction between these factors. The objectives are to first separate the interaction of factors directly influencing the measurement and to attempt to identify these factors. Interpretation of the SAR image sets proceeds by testing models that hypothesize the cause and effect relations between those factors directly affecting the radar measurement and those features of interest to the interpreter. The results of our analysis indicated two consistent endmember types over all four image scenes. These types are defined by a high flat polarized signature near a level of 255 DN and a low level flat signature near 0 DN for all polarizations. Four other endmember types were also isolated. The spatial distribution of these endmember types indicates possible correspondence to surface volume scattering and changes in surface dielectric. However, the shapes of these endmember types were different from scene to scene.

Smith, M.↗
NASA NTRS1987

Detection of Rift Valley fever viral activity in Kenya by satellite remote sensing imagery

Data from the advanced very high resolution radiometer on board the National Oceanic and Atmospheric Administration's polar-orbiting meteorological satellites have been used to infer ecological parameters associated with Rift Valley fever (RVF) viral activity in Kenya. An indicator of potential viral activity was produced from satellite data for two different ecological regions in Kenya, where RVF is enzootic. The correlation between the satellite-derived green vegetation index and the ecological parameters associated with RVF virus suggested that satellite data may become a forecasting tool for RVF in Kenya and, perhaps, in other areas of sub-Saharan Africa.

Linthicum, Kenneth J.↗
NASA NTRS1989

Sources of error in thematic classification of remotely sensed imagery

From a statistician's point of view, the input datasets are rarely examined to determine their underlying frequency distribution; it is just assumed that the data are normal enough, and that the deviations from normality are unimportant. It is not clear how deviations from a hypothetical multivariate normal might affect the power of the classification process, and there is ample evidence in the literature that, at a minimum, the spectral channels are correlated. From a practioner's point of view, in a supervised classification the number of training fields for developing a statistical description of a given class is usually arbitrary. It is unclear how small changes in the details of the training field selection process affect the quality of the derived thematic information. The start of an examination of this latter problem is discussed.

Star, Jeffrey L.↗
NASA NTRS1992

Design of neural networks for classification of remotely sensed imagery

Classification accuracies of a backpropagation neural network are discussed and compared with a maximum likelihood classifier (MLC) with multivariate normal class models. We have found that, because of its nonparametric nature, the neural network outperforms the MLC in this area. In addition, we discuss techniques for constructing optimal neural nets on parallel hardware like the MasPar MP-1 currently at GSFC. Other important discussions are centered around training and classification times of the two methods, and sensitivity to the training data. Finally, we discuss future work in the area of classification and neural nets.

Chettri, Samir R.↗
NASA NTRS1991

Compiling and editing agricultural strata boundaries with remotely sensed imagery and map attribute data using graphics workstations

The USDA presently uses labor-intensive photographic interpretation procedures to delineate large geographical areas into manageable size sampling units for the estimation of domestic crop and livestock production. Computer software to automate the boundary delineation procedure, called the computer-assisted stratification and sampling (CASS) system, was developed using a Hewlett Packard color-graphics workstation. The CASS procedures display Thematic Mapper (TM) satellite digital imagery on a graphics display workstation as the backdrop for the onscreen delineation of sampling units. USGS Digital Line Graph (DLG) data for roads and waterways are displayed over the TM imagery to aid in identifying potential sample unit boundaries. Initial analysis conducted with three Missouri counties indicated that CASS was six times faster than the manual techniques in delineating sampling units.

Cheng, Thomas D.↗
NASA NTRS1995

A conflict of water and fire: Remote sensing imagery of the Uinkaret Volcanic Field, Grand Canyon, Arizona

The sedimentary geology of the western Grand Canyon consists of gently northeast dipping sandstones, shales, and carbonates. However, due to facies changes within the units, the geomorphology varies from that seen by visitors at the National Park Headquarters. There, the cliff and slope expression of the rocks is replaced in the west by a series of mesas, ridges, and horizontal platforms. The largest of these occurs on the Esplanade Sandstone within the Supai Formation. The Esplanade is formed by slope retreat of the overlying units and resistance to erosion by the underlying limestones. It is onto this platform that the lavas of the Uinkaret Plateau were emplaced. The Uinkaret lava field lies 120 km south of St. George, Utah and is tectonically defined by two major normal faults -- the Hurricane to the west and the Toroweap to the east. The purpose of this investigation was to collect visible, near and thermal infrared data at different periods of the day and year. It is expected that these data will provide the ability to retrieve water temperatures; monitor sediment loads; map and examine any changes in the near shore vegetation communities and understand some of the intricacies of the geology. This paper will serve, to some degree, as a progress report on the Grand Canyon study, since only a fraction of the data has been received and processed thus far. Data from the Thermal Infrared Multispectral Scanner (TIMS) and the Landsat Thematic Mapper simulator (NS001) were acquired simultaneously on April 4, 1994. A second data acquisition occurred on August 27, 1994. Initial analysis of the TIMS data indicates a remarkably noise-free data set with minimal atmospheric attenuation. environments is evident.

Ramsey, Michael S.↗
NASA NTRS2001

Multi-Sensor Registration of Earth Remotely Sensed Imagery

Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

LeMoigne, Jacqueline↗