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The terrain-surface features of the Appalachian Valley and Ridge province were analyzed using Seasat synthetic aperture radar imagery. Particular attention was given to determining the efficiency and capability of this microwave imaging system for geologic mapping.
A methodology is proposed for international geological correlation studies based on LANDSAT-MSS imagery, Bullard's model of continental fit and compatible structural trends between Northeast Brazil and the West African counterpart. Six extensive lineaments in the Brazilian study area are mapped and discussed according to their regional behavior and in relation to the adjacent continental margin. Among the first conclusions, correlations were found between the Sobral Pedro II Lineament and the megafaults that surround the West African craton; and the Pernambuco Lineament with the Ngaurandere Linemanet in Cameroon. Ongoing research to complete the methodological stages includes the mapping of the West African structural framework, reconstruction of the pre-drift puzzle, and an analysis of the counterpart correlations.
LANDSAT imagery was used to determine the amount of deforestation in a study area comprising 55 million hectares of the Amazon region. Results show that more than 4 million hectares were deforested. Maps and pictures of the deforested area in relation to the total area of the Amazon are included.
A digital processing algorithm and its associated system design for producing images from SEASAT synthetic aperture radar (SAR) data is described. The proposed system uses the fast Fourier transform approach to perform the two dimensional correlation process. The range migration problem can be alleviated by approximating the locus of echoes from a point target by several linear segments. Data corresponding to each segment are correlated separately and the results are coherently summed to produce full resolution images. This processing approach exhibits high computation efficiency and simple processing control functions. It is particularly attractive for software implementation based on general purpose computers. Results of this implementation and examples of digitally correlated SEASAT SAR imagery are discussed.
The feasibility of remote, high-resolution infrared imagery of the Shuttle Orbiter lower surface during entry to obtain accurate measurements of aerodynamic heat transfer was demonstrated. Using available technology, such images can be taken from an existing aircraft/telescope system (the C141 AIRO) with minimum modification or addition of systems. Images with a spatial resolution of 1 m or better and a temperature resolution of 2.5% between temperatures of 800 and 1900 K can be obtained. Data reconstruction techniques can provide a geometrically and radiometrically corrected array on addressable magnetic tape ready for display by NASA.
A technique for producing topographic information is described which is based on same side/same time viewing using a dissimilar combination of radar imagery and photographic images. Common geographic areas viewed from similar space reference locations produce scene elevation displacements in opposite direction and proper use of this characteristic can yield the perspective information necessary for determination of base to height ratios. These base to height ratios can in turn be used to produce a topographic map. A test area covering the Harrisburg, Pennsylvania region was observed by synthetic aperture radar on the Seasat satellite and by return beam vidicon on by the LANDSAT - 3 satellite. The techniques developed for the scaling re-orientation and common registration of the two images are presented along with the topographic determination data. Topographic determination based exclusively on the images content is compared to the map information which is used as a performance calibration base.
A model for radar image data is derived for use in developing enhancement techniques. This model describes the image data as the result of a multiplicative-convolved noise process. This information is then used to design a minimum mean square error (MMSE) filter. The resulting filter is implemented adaptively to change with local statistics. A radar image processing technique which provides the MMSE estimate inside homogeneous areas and tends to preserve edge structure is thus developed. This technique has been implemented and tested using digitally correlated SEASAT-A synthetic aperture radar (SAR) imagery.
The paper is concerned with the interpretation of hydrologic features using L-band (HH) imagery collected by aircraft and Seasat systems. Areas of research needed to more precisely define the accuracy and repeatability of measurements related to the conditions of surfaces and boundaries of fresh water bodies are identified. These include: the definition of shoreline, the nature of variations in surface roughness across a water body and along streams and lake shores, and the separation of ambiguous conditions which appear similar to lakes.
A study has been carried out to develop a photo-optical technique by which Landsat imagery can be used to monitor trophic states of lakes. The proposed technique uses a single number to characterize the trophic state, and a feature within the satellite scene is used as an internal standard for comparison of the lakes in time. By use of the technique it is possible to assess in retrospect the trophic state of each individual lake.
The formulation is rigorous and includes all misalignment angles of the VISSR, the sun sensor and the instantaneous spin axis with the satellite's body axis. It also includes the effects due to the motion of the satellite's suborbital point. All the mapping equations for distortion removal were reduced to simplest forms, and all the algorithms were optimized as much as possible. An approach was then formulated for implementing these algorithms for in-line operational use. It is concluded that in-line distortion removal is possible in real-time processing of infra-red but not visible VISSR imagery data.
The problem of obtaining the probabilities of class labels for the clusters using spectral and spatial information from a given set of labeled patterns and their neighbors is considered. A relationship is developed between class and clusters conditional densities in terms of probabilities of class labels for the clusters. Expressions are presented for updating the a posteriori probabilities of the classes of a pixel using information from its local neighborhood. Fixed-point iteration schemes are developed for obtaining the optimal probabilities of class labels for the clusters. These schemes utilize spatial information and also the probabilities of label imperfections. Experimental results from the processing of remotely sensed multispectral scanner imagery data are presented.
One of the advantages of automated cartography is that map data stored in the digital computer can be plotted or displayed at any scale or projection by recomputing the coordinates of the data. This is especially easy in the case of vector (graphics) data but in the case of digital image (raster) data, remapping is a more difficult operation. Examples of the remapping of digital imagery would include rectification of a LANDSAT MSS to an orthographic or Mercator projection, warping of one image to register with another, or rotation, scale, or aspect changes of a digital image. Use of general purpose computers and array processors for this task will be covered. Data processing error will be discussed for each modelling/warping approach.
Multivariant hydrologic parameters over the Shark River Slough were investigated. Ground truth was established utilizing U-2 infrared photography and comprehensive field data to define a control network which represented all hydrobiological systems in the slough. These data were then applied to LANDSAT imagery utilizing an interactive multispectral processor which generated hydrographic maps through classification of the slough and defined the multispectral surface radiance characteristics of the wetlands areas in the park. The spectral response of each hydrobiological zone was determined and plotted to formulate multispectral relationships between the emittent energy from the slough in order to determine the best possible multispectral wavelength combinations to enhance classification results. The extent of each hydrobiological zone in slough was determined and flow vectors for water movement throughout the slough established.
The detectability of urban land cover types is explored using digitally processed Seasat SAR imagery of the Denver, Colorado area. Test sites within the metropolitan area were selected to include a cross section of Anderson, et. al. Level II land cover classes and cover types representative of the urban area growth stages. Using the Image 100 interactive processing system each test site was level sliced in an attempt to define specific reflectance boundaries for each cover type and to determine the spectral and spatial characteristics of homogeneous response regions. The rural-urban fringe boundary was readily definable, but a precise Level I and Level II land cover classification was not possible. High density housing could be separated from low density housing and from parks, but reflectance values were often look angle dependent. Confusion between some water and vegetation responses also posed problems.
An F-scale analysis of Hurricane Frederic (September 12 and 13, 1979) was performed in order to determine the structural damage patterns attributed to the storm. Enhanced SMS imagery revealed patterns of mesoscale features as well as features related to the shielding effects of trees and the grouping effect of structures. The scatter in estimating the damage scale was + or - 1 F-scale. It is shown that discrepancies in recorded wind speed and the estimated wind-speed from the F-scale are the result of different damage mechanisms of hurricane and tornado winds. Radar echoes revealed that the structure of Hurricane Frederic changed from an axisymmetric center to an instantaneous center of rotation. Finally, it is suggested that major hurricane wind and water damage be investigated in greater detail by aerial photography, damage vector mapping, and ground surveys.
The cost and effectiveness of developing land cover information derived from Landsat imagery for hydrologic studies are compared with the cost and effectiveness of conventional sources. The analysis shows that the conventional and Landsat methods are nearly equally effective in providing adequate land cover data for hydrologic studies. The total cost effectiveness analysis demonstrates that the conventional method is cost effective for a study area of less than 26 sq km and that the Landsat method is to be preferred for areas of more than 26 sq km.
This paper describes a digital processing algorithm and its associated system design for producing images from SEASAT Synthetic Aperture Radar (SAR) data. The proposed system uses the fast Fourier transform approach to perform the two-dimensional correlation process. The range migration problem, which is often a major obstacle to efficient processing, can be alleviated by approximating the locus of echoes from a point target by several linear segments. SAR data corresponding to each segment is correlated separately, and the results are coherently summed to produce full-resolution images. This processing approach exhibits high computation efficiency and simple processing control functions. It is particularly attractive for software implementation based on general purpose computer. Results of this implementation and examples of digitally correlated SEASAT SAR imagery are discussed
One of the sensors of the Seasat satellite was a synthetic aperture radar (SAR), which was operated over both oceanic and land areas. The Seasat SAR was an active imaging microwave system which transmitted and received horizontally polarized radiation at L-band frequency (1.275 GHz, 23-cm wavelength). Extensive coverage was obtained over North America, Europe, the Eastern Pacific Ocean, the Western and Northern Atlantic Ocean, and the Beaufort Sea. Surface coverage was also acquired over limited portions of Central America, the Gulf of Mexico, and the Caribbean Sea. The majority of the data has been optically processed in a so-called survey mode. Each optically processed Seasat pass has a swath width of 100 km at a scale of 1:500,000. A subset of the SAR data has been digitally processed in a so-called high-resolution mode. Digital processing has been performed upon selected scenes with dimensions of 100 x 100 km. Digitally processed imagery has a nominal ground resolution of 25 m.