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Applications of ERTS-1 data and imagery in the fields of land use and mapping are summarized. Three areas are investigated and discussed: (1) mapping investigations; (2) land use inventory/image interpretation techniques; and (3) land use investigations/automatic pattern recognition techniques.
The author has identified the following significant results. Several of the tasks have produced significant results which are summarized: (1) Absolute water depth can be calculated from a ratio of signals from bands MSS 4 and MSS 5. (2) A 13 category terrain feature classification map of Yellowstone National Park has been produced using supervised pattern recognition techniques. (3) ERTS-1 data has been shown to provide a detection and monitoring capability for a number of water quality problems associated with off-shore ocean dumping sites and inland lakes. (4) A corrected ratio of bands MSS-5 and MSS-7 signals has been formed. (5) A concise format has been devised for storing the ratio signatures of geologic rock and mineral materials determined from laboratory reflectance spectra. (6) Results of work in information extraction demonstrate: signal variability exists among ERTS-1 detectors in any one spectral band that will impact users doing quantitative analysis on successive ERTS-1 images; a newly developed computer-aided procedure for correlating ERTS-1 pixels to ground features; the strong influence of atmospheric effects in ERTS-1 data; and area estimation accuracies are better using the ERIM proportion estimation algorithm than for conventional recognition techniques.
The digital calculations that drive the classification portion of the Hybrid Pattern Recognition System (HYMPS) are considered. A revision of these calculations is suggested that involves three items: matrix inversion, det calculations and singularity, and covariance factorization. It is shown that it is more economical to first factor the covariance matrix, and by so doing, delete the matrix inversion routine. In addition, the necessary det calculations can be more easily realized by use of simple theoretical facts about the factorization.
Present automated systems of interpretation which apply pattern recognition techniques on MSS data do not fully consider the geometry of the acquisition system. In an effort to improve the usefulness of the MSS data when digitally treated, geometric aspects are analyzed and discussed. Attempts to correct for scanner instabilities in position and orientation by affine and polynomial transformations, as well as by modified collinearity equations are described. Methods of accounting for panoramic and relief effects are also discussed. It is anticipated that reliable area as well as position determinations can be accomplished during the process of automatic interpretation. A concept for a unified approach to the treatment of remote sensing data, both metric and nonmetric is presented.
The Small Interactive Image Processing System (SMIP) is designed to facilitate the acquisition, digital processing and recording of image data as well as pattern recognition in an interactive mode. Objectives of the system are ease of communication with the computer by personnel who are not expert programmers, fast response to requests for information on pictures, complete error recovery as well as simplification of future programming efforts for extension of the system. The SMIP system is intended for operation under OS/MVT on an IBM 360/75 or 91 computer equipped with the IBM-2250 Model 1 display unit. This terminal is used as an interface between user and main computer. It has an alphanumeric keyboard, a programmed function keyboard and a light pen which are used for specification of input to the system. Output from the system is displayed on the screen as messages and pictures.
Review of the data handling and analysis methods used in the near-operational test of remote sensing systems provided by the 1971 corn blight watch experiment. The general data analysis techniques and, particularly, the statistical multispectral pattern recognition methods for automatic computer analysis of aircraft scanner data are described. Some of the results obtained are examined, and the implications of the experiment for future data communication requirements of earth resource survey systems are discussed.
Applications of the optical computer include an approach for increasing the sharpness of images obtained from the most powerful electron microscopes and fingerprint/credit card identification. The information-handling capability of the various optical computing processes is very great. Modern synthetic-aperture radars scan upward of 100,000 resolvable elements per second. Fields which have assumed major importance on the basis of optical computing principles are optical image deblurring, coherent side-looking synthetic-aperture radar, and correlative pattern recognition. Some examples of the most dramatic image deblurring results are shown.
Topics related to photoreceptors are considered, giving attention to visual pattern recognition and directional orientation in insects, the sensory basis of orientation in amphibians, and the aerial and underwater visual acuity in the California sea lion as a function of luminance. Other subjects explored are in the fields of phonoreceptors, chemoreception, vestibular receptors, and electrical and magnetic sensitivity. Questions of the development and evolution of orientation are also investigated, taking into account field studies of mass emigration and orientation in the spiny lobster and investigations concerning the jumping behavior in the Gobiid fish. Individual items are announced in this issue.
A procedure for modeling a linear system by an optimal finite-dimensional approximation is developed on the basis of Sard's (1967) generalized spline. Error bounds are given, and the application of the procedure is illustrated by two presented examples. The procedure may be employed, not only in the modeling of conventional lumped-parameter and distributed-parameter continuous dynamical systems, but also in mathematical operations such as those involved in pattern recognition and picture enhancement problems.
Description of remote sensing studies carried out for the purpose of developing and/or demonstrating techniques which can be employed for land use inventory, marsh vegetation classification, and water characteristics surveys. Attention is given to results obtained with (1) photo interpretation techniques and procedures for the development of land use information from high-altitude aircraft and satellite imagery, (2) computer based pattern recognition techniques utilizing multispectral scanner data for marsh vegetation classification, and (3) infrared and microwave techniques for the monitoring and surveying of coastal water temperature and salinity characteristics.
The applications of remote sensing techniques to spectral surveys of irrigation, crops, and soils are reported. Topics discussed include: (1) canopy temperature as an indication of plant water stress, (2) temperature of soils and of crop canopies differing in water conditions, (3) ERTS project, (4) spectrum matching and pattern recognition, (5) photographic procedures and interpretation, (6) interaction of light with plants, and (7) plant physiological and histological factors.
The author has identified the following significant results. Orbital SL-2 imagery (earth terrain camera S-190B), received September 5, 1973, was subjected to quantitative network analysis and compared to 7.5 minute topographic mapping (scale: 1/24,000) and U.S.D.A. conventional black and white aerial photography (scale: 1/22,200). Results can only be considered suggestive because detail on the SL-2 imagery was badly obscured by heavy cloud cover. The upper Bee Creek basin was chosen for analysis because it appeared in a relatively cloud-free portion of the orbital imagery. Drainage maps were drawn from the three sources digitized into a computer-compatible format, and analyzed by the WATER system computer program. Even at its small scale (1/172,000) and with bad haze the orbital photo showed much drainage detail. The contour-like character of the Glen Rose Formation's resistant limestone units allowed channel definition. The errors in pattern recognition can be attributed to local areas of dense vegetation and to other areas of very high albedo caused by surficial exposure of caliche. The latter effect caused particular difficulty in the determination of drainage divides.
The development of holography and the state of the art in recording and displaying information, microscopy, motion, pictures, and television applications are discussed. In addition to optical holography, information is presented on microwave, acoustic, ultrasonic, and seismic holography. Other subjects include data processing, data storage, pattern recognition, and computer-generated holography. Diagrams of holographic installations are provided. Photographs of typical holographic applications are used to support the theoretical aspects.
The author has identified the following significant results. Multispectral scanner data obtained by ERTS-1 over six test sites in the Central United States were analyzed and interpreted. ERTS-1 data for some of the test sites were geometrically corrected and temporally overlayed. Computer-implemented pattern recognition techniques were used in the analysis of all multispectral data. These techniques were used to evaluate ERTS-1 data as a tool for soil survey. Geology maps and land use inventories were prepared by digital analysis of multispectral data. Identification and mapping of crop species and rangelands were achieved throught the analysis of 1972 and 1973 ERTS-1 data. Multiple dates of ERTS-1 data were examined to determine the variation with time of the areal extent of surface water resources on the Southern Great Plain.
The growth of the field of system identification is discussed along with changes in methodology which have taken place in recent years. The similarity between pattern recognition and system identification is pointed out, involving the modelling in the latter and the feature selection problem in the former. It is stated that once a model is formulated, including the disturbances and measurement errors, the parameter finding can be formulated as a statistical estimation problem. The various techniques and their application are discussed.
Theoretical backgrounds and digital techniques for a class of image processing problems are presented. Image formation in the context of linear system theory, image evaluation, noise characteristics, mathematical operations on image and their implementation are discussed. Various techniques for image restoration and image enhancement are presented. Methods for object extraction and the problem of pictorial pattern recognition and classification are discussed.
A comprehensive study has been undertaken to determine the extent to which ERTS-1 data could be used to detect, identify (classify), locate and measure features of applications interest in the disciplines of Agriculture and Forestry. The study areas included: six counties in five states in which were located examples of the most important crops and practices of American agriculture; and a portion of the Sam Houston National Forest, a typical Gulf coastal plain pine forest. The investigation utilized conventional image interpretation and computer-aided (spectral pattern recognition) analysis using both image products and computer compatible tapes. The emphasis was generally upon the computer-aided techniques. It was concluded that ERTS-1 data can be used to detect, identify, locate and measure a wide array of features of interest in agriculture and forestry.
A comprehensive study has been undertaken to determine the extent to which conventional image interpretation and computer-aided (spectral pattern recognition) analysis techniques using ERTS-1 data could be used to detect, identify (classify), locate, and measure current land use over large geographic areas. It can be concluded that most of the level 1 and 2 categories in the USGS Circular no. 671 can be detected in the Houston-Gulf Coast area using a combination of both techniques for analysis. These capabilities could be exercised over larger geographic areas, however, certain factors such as different vegetative cover, topography, etc. may have to be considered in other geographic regions. The best results in identification (classification), location, and measurement of level 1 and 2 type categories appear to be obtainable through automatic data processing of multispectral scanner computer compatible tapes.