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  • 1
    Publication Date: 2013-08-31
    Description: An initial analysis of LANDSAT 4 thematic mapper (TM) data for the delineation and classification of agricultural, forested wetland, and urban land covers was conducted. A study area in Poinsett County, Arkansas was used to evaluate a classification of agricultural lands derived from multitemporal LANDSAT multispectral scanner (MSS) data in comparison with a classification of TM data for the same area. Data over Reelfoot Lake in northwestern Tennessee were utilized to evaluate the TM for delineating forested wetland species. A classification of the study area was assessed for accuracy in discriminating five forested wetland categories. Finally, the TM data were used to identify urban features within a small city. A computer generated classification of Union City, Tennessee was analyzed for accuracy in delineating urban land covers. An evaluation of digitally enhanced TM data using principal components analysis to facilitate photointerpretation of urban features was also performed.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: NASA-TM-85499 , NAS 1.15:85499 , NSTL/ERL-215 , E84-10073
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  • 2
    Publication Date: 2014-09-17
    Description: The capabilities of TM data for discriminating land covers within three particular cultural and ecological realms was assessed. The agricultural investigation in Poinsett County, Arkansas illustrates that TM data can successfully be used to discriminate a variety of crop cover types within the study area. The single-date TM classification produced results that were significantly better than those developed from multitemporal MSS data. For the Reelfoot Lake area of Tennessee TM data, processed using unsupervised signature development techniques, produced a detailed classification of forested wetlands with excellent accuracy. Even in a small city of approximately 15,000 people (Union City, Tennessee). TM data can successfully be used to spectrally distinguish specific urban classes. Furthermore, the principal components analysis evaluation of the data shows that through photointerpretation, it is possible to distinguish individual buildings and roof responses with the TM.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: NASA. Goddard Space Flight Center LANDSAT-4 Sci. Characterization Early Results, Vol. 4; p 131-152
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  • 3
    Publication Date: 2011-08-24
    Description: A method for water temperature estimation on the basis of thermal data is presented and tested against NASA's Thermal IR Multispectral Scanner. Using realistic bounds on emissivities, temperature bounds are calculated and refined to estimate a tighter bound on the emissivity of the source. The method is useful only when a realistic set of bounds can be obtained for the emissivities of the data.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: In: Automatic object recognition II; Proceedings of the Meeting, Orlando, FL, Apr. 22-24, 1992 (A93-33243 12-63); p. 406-416.
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  • 4
    Publication Date: 2013-08-31
    Description: The effective flux incident upon the detectors of a thermal sensor, after it has been corrected for atmospheric effects, is a function of a non-linear combination of the emissivity of the target for that channel and the temperature of the target. The sensor system cannot separate the contribution from the emissivity and the temperature that constitute the flux value. A method that estimates the bounds on these temperatures and emissivities from thermal data is described. This method is then tested with remotely sensed data obtained from NASA's Thermal Infrared Multispectral Scanner (TIMS) - a 6 channel thermal sensor. Since this is an under-determined set of equations i.e. there are 7 unknowns (6 emissivities and 1 temperature) and 6 equations (corresponding to the 6 channel fluxes), there exist theoretically an infinite combination of values of emissivities and temperature that can satisfy these equations. Using some realistic bounds on the emissivities, bounds on the temperature are calculated. These bounds on the temperature are refined to estimate a tighter bound on the emissivity of the source. An error analysis is also carried out to quantitatively determine the extent of uncertainty introduced in the estimate of these parameters. This method is useful only when a realistic set of bounds can be obtained for the emissivities of the data. In the case of water the lower and upper bounds were set at 0.97 and 1.00 respectively. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected with the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. Ground truth temperatures using thermometers and radiometers were also obtained over an area of the reservoir. The results of two independent runs of the radiometer data averaged 7.03 plus or minus .70 for the first run and 7.31 plus or minus .88 for the second run. The results of the algorithm yield a temperature of 7.68 for the low altitude data to 8.73 for the high altitude data.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: JPL, Summaries of the Third Annual JPL Airborne Geoscience Workshop. Volume 2: TIMS Workshop; p 22-24
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  • 5
    Publication Date: 2013-08-31
    Description: Fractal geometry is increasingly becoming a useful tool for modeling natural phenomenon. As an alternative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. Since they are characterized by self-similarity, an ideal fractal surface is scale-independent; i.e. at different scales a fractal surface looks the same. This is not exactly true for natural surfaces. When viewed at different spatial resolutions parts of natural surfaces look alike in a statistical manner and only for a limited range of scales. Images acquired by NASA's Thermal Infrared Multispectral Scanner are used to compute the fractal dimension as a function of spatial resolution. Three methods are used to determine the fractal dimension - Schelberg's line-divider method, the variogram method, and the triangular prism method. A description of these methods and the results of applying these methods to a remotely-sensed image is also presented. Five flights were flown in succession at altitudes of 2 km (low), 6 km (mid), 12 km (high), and then back again at 6 km and 2 km. The area selected was the Ross Barnett reservoir near Jackson, Mississippi. The mission was flown during the predawn hours of 1 Feb. 1992. Radiosonde data was collected for that duration to profile the characteristics of the atmosphere. This corresponds to 3 different pixel sizes - 5m, 15m, and 30m. After, simulating different spatial sampling intervals within the same image for each of the 3 image sets, the results are cross-correlated to compare the extent of detail and complexity that is obtained when data is taken at lower spatial intervals.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: JPL, Summaries of the Third Annual JPL Airborne Geoscience Workshop. Volume 2: TIMS Workshop; p 25-27
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  • 6
    Publication Date: 2011-08-24
    Description: Images acquired by NASA's Calibrated Airborne Multispectral Scanner are used to compute the fractal dimension as a function of spatial resolution. Three methods are used to determine the fractal dimension: Shelberg's (1982, 1983) line-divider method, the variogram method, and the triangular prism method. A description of these methods and the result of applying these methods to a remotely-sensed image is also presented. The scanner data was acquired over western Puerto Rico in January, 1990 over land and water. The aim is to study impacts of man-induced changes on land that affect sedimentation into the near-shore environment. The data were obtained over the same area at three different pixel sizes: 10 m, 20 m, and 30 m.
    Keywords: COMPUTER PROGRAMMING AND SOFTWARE
    Type: In: Visual information processing; Proceedings of the Meeting, Orlando, FL, Apr. 20-22, 1992 (A93-32438 12-61); p. 43-54.
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  • 7
    Publication Date: 2014-09-13
    Description: An initial analysis of LANDSAT 4 Thematic Mapper (TM) data for the discrimination of agricultural, forested wetland, and urban land covers is conducted using a scene of data collected over Arkansas and Tennessee. A classification of agricultural lands derived from multitemporal LANDSAT Multispectral Scanner (MSS) data is compared with a classification of TM data for the same area. Results from this comparative analysis show that the multitemporal MSS classification produced an overall accuracy of 80.91% while the TM classification yields an overall classification accuracy of 97.06% correct.
    Keywords: DOCUMENTATION AND INFORMATION SCIENCE
    Type: NASA. Goddard Space Flight Center LANDSAT-4 Sci. Invest. Summ., Including Dec. 1983 Workshop Results, Vol. 2; p 111-112
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  • 8
    Publication Date: 2019-07-13
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: International Symposium on Remote Sensing of Environment; May 9-13, 1983; Ann Arbor, MI
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  • 9
    Publication Date: 2019-07-13
    Description: There are no author-identified significant results in this report.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E80-10338 , NASA-CR-163418 , SAPR-12
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  • 10
    Publication Date: 2019-07-13
    Description: The author has identified the following significant results. The Lowndes County data base is essentially complete with 18 primary variables and 16 proximity variables encoded into the geo-information system. The single purpose, decision tree classifier is now operational. Signatures for the thematic extraction of strip mines from LANDSAT Digital data were obtained by employing both supervised and nonsupervised procedures. Dry, blowing sand areas of beach were also identified from the LANDSAT data. The primary procedure was the analysis of analog data on the I2S signal slicer.
    Keywords: EARTH RESOURCES AND REMOTE SENSING
    Type: E79-10196 , NASA-CR-158510 , SAPR-11
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