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The requirements necessary to establish a comprehensive data base for the Chesapeake Bay are discussed. Three essential questions were addressed: (1) which entities should be measured; (2) how close together should measurements be made in space and time; and (3) what should be done with the data. Possible answers to the questions were evaluated in relation to existing technology, cost effectiveness, and potential uses of the data base.
Use of remote sensing technology provided through the NASA/Wallops Chesapeake Bay Ecological Program was investigated by means of extensive interviews with users. Since the inception of the Program four years ago, the technology has been used in 136 different managerial projects. Sixty-five regional managerial agencies took part in projects that the authors categorized as socioeconomic, political/managerial, monetary, legal, and other. Remote sensing technology was considered successful in 88.6 percent of the completed projects and unsuccessful in 2.8 percent.
Both the proportions of the various land use categories present on each watershed and the specific management practices in use in each category affect the quality of runoff waters, and the water quality of the Bay. Several permanent and portable stations on various Maryland Rivers collect volume-integrated water samples. All samples are analyzed for a series of nutrient, particulate, bacterial, herbicide, and heavy metal parameters. Each basin is mapped with respect to land use by the analysis of low-elevation aerial photos. Analyses are verified and adjusted by ground truth surveys. Data are processed and stored in the Smithsonian Institution data bank. Land use categories being investigated include forests/old fields, pastureland, row crops, residential areas, upland swamps, and tidal marshes.
Maintenance of the Baltimore and the Newport News/Norfolk harbors as well as of the Chesapeake and Delaware Canal is accomplished by different dredging operations which depend on the amount and type of material to be moved, water depth, and location of disposal sites. Methods for determining the physical or chemical-biological interactive effects of these activities on the environment and on the shellfish and finfish industries on the Bay are discussed. The types of dredges used are classed according to their mode of operation.
The advantages and limitations of using remote sensing to acquire fast reliable data on the nutrient problem in the Chesapeake Bay ecosystem are discussed. Pollution effects to phytoplankton blooms during late summer and early fall months are also considered.
The proceedings are presented of a conference, jointly sponsored by the National Aeronautics and Space Administration, the U.S. Environmental Protection Agency, and the University of Maryland. The purpose of the Conference was to assemble representatives of federal and state government agencies engaged in research on the condition and evolution of the Chesapeake Bay to compose a status report, to present current activities and future plans, and to recommend a long-range future course of policies and programs.
Skylab/EREP S190A and S190B film products were optically enhanced and visually interpreted to extract data suitable for; (1) mapping coastal land use; (2) inventorying wetlands vegetation; (3) monitoring tidal conditions; (4) observing suspended sediment patterns; (5) charting surface currents; (6) locating coastal fronts and water mass boundaries; (7) monitoring industrial and municipal waste dumps in the ocean; (8) determining the size and flow direction of river, bay and man-made discharge plumes; and (9) observing ship traffic. Film products were visually analyzed to identify and map ten land-use and vegetation categories at a scale of 1:125,000. Digital tapes from the multispectral scanner were used to prepare thematic maps of land use. Classification accuracies obtained by comparison of derived thematic maps of land-use with USGS-CARETS land-use maps in southern Delaware ranged from 44 percent to 100 percent.
The author has identified the following significant results. The probability of correct classification of various populations in data was defined as the primary performance index. The multispectral data being of multiclass nature as well, required a Bayes error estimation procedure that was dependent on a set of class statistics alone. The classification error was expressed in terms of an N dimensional integral, where N was the dimensionality of the feature space. The multispectral scanner spatial model was represented by a linear shift, invariant multiple, port system where the N spectral bands comprised the input processes. The scanner characteristic function, the relationship governing the transformation of the input spatial, and hence, spectral correlation matrices through the systems, was developed.
The benefits and costs that would result from an intra-regional air service operation in the San Francisco Bay area were determined by utilizing an iterative statistical decision model to evaluate combinations of commuter airport sites and surface transportation facilities in conjunction with service by a given commuter aircraft type in light of area regional growth alternatives and peak and off-peak regional travel patterns. The model evaluates such transportation option with respect to criteria of airline profitability, public acceptance, and public and private non-user costs. In so doing, it incorporates information on modal split, peak and off-peak use of the air commuter fleet, terminal and airport costs, development costs and uses of land in proximity to the airport sites, regional population shifts, and induced zonal shifts in travel demand. The model is multimodal in its analytic capability, and performs exhaustive sensitivity analysis.
The regional setting for the three San Franscisco Bay area airports is described. The general role of the airports in the national air transportation system, the demand for air transportation, and the relationship of airport location to the demand for air transportation are examined. The problem of airport access is also considered. Various access modes, their destination, frequency, and cost are presented.
Current transportation technology and expected technological trends are reviewed. These technologies are assessed within the framework of the airport access system in the San Francisco Bay area. Four types of technological options are considered: (1) automotive systems, (2) commuter air systems, (3) automated guideways, and (4) water systems.
The Inertial Upper Stage (IUS) is a two-stage or three-stage booster used to transport spacecraft from the space shuttle orbit to synchronous orbit or on an interplanetary trajectory. The mechanisms which were designed specifically to perform the two-stage IUS required functions while contained within the cargo bay of the space shuttle during the boost phase and while in a low Earth orbit are discussed. The requirements, configuration, and operation of the mechanisms are described, with particular emphasis on the tilt actuator and the mechanism for decoupling the actuators during boost to eliminate redundant load paths.
The author has identified the following significant results. Data from an ocean color scanner flown on a U-2 aircraft at 65,000 ft and from LANDSAT MSS were enhanced to identify biologically active areas of San Francisco Bay, and to determine the salinity, turbidity, chlorophylls, and suspended solids. The best fit regression models for mapping water quality parameters were based on bands 3, 5, 7, and 10. Comparision of the results indicate that chlorophyll concentrations can best be estimated by the OCS or MSS data. Salinity can best be estimated by OCS data; turbidity can best be estimated by LANDSAT data. Neither OCS nor MSS data provide reliable basis for estimating suspended solids. Aerial photography of the highest quality taken with either conventional color or infrared-sensitive color films was unable to locate the biologically active areas.
Water quality parameters in the San Francisco Bay-delta area using remotely sensed data combined with in situ data are investigated. The parameters included suspended solids, chlorophyll, turbidity, and electrical conductivity; the ocean color scanner (OCS) data were acquired from a NASA U-2 aircraft, and water quality samples were obtained from boats. It was concluded that areas with high biological activity were clearly discernible on enhanced imagery from OCS data, and it was impossible to locate such areas on aerial photography taken with conventional or infrared sensitive color films.
The purpose of the paper is to evaluate the performance of rigid-lid formulations in predicting velocity and temperature fields in domains where the applicability of rigid-lid formulations is not immediately obvious. A test was conducted to determine whether local depth scaled vertical exchange coefficients yield better simulations compared to constant vertical coefficient formulations. Extensive infrared imagery was used to evaluate the model's ability to predict temperature yields in Biscayne Bay, Fla. Two cases, one with constant vertical eddy transport coefficient, and the other with vertical transport coefficient scaled with local depth are discussed.
Detection of water quality in Guanabara Bay using multispectral scanning digital data taken from LANDSAT satellites was examined. To test these processes, an empirical (statistical) approach was choosen to observe the degree of relationship between LANDSAT data and the in situ data taken simultaneously. The linear and nonlinear regression analyses were taken from among those developed by INPE in 1978. Results indicate that the major regression was in the number six MSS band, atmospheric effects, which indicated a correction coefficient of 0.99 and an average error of 6.59 micrograms liter. This error was similar to that obtained in the laboratory. The chlorophyll content was between 0 and 100 micrograms/liter, as taken from the MSS of LANDSAT.
A system for automated multidate Landsat CCT MSS measurement of suspended sediment concentration (S) has been implemented and verified on nine sets (108 points) of data from the Bay of Fundy, Canada. The system employs 'chromaticity analysis' to provide automatic pixel-by-pixel adjustment of atmospheric variations, permitting reference calibration data from one or several dates to be spatially and temporally extrapolated to other regions and to other dates. For verification, each data set was used in turn as test data against the remainder as a calibration set: the average absolute error was 44 percent of S over the range 1-1000 mg/l. The system can be used to measure chlorophyll (in the absence of atmospheric variations), Secchi disk depth, and turbidity.
The results of the Chesapeake Bay plume study are reported. The role of remote sensing in monitoring and assessing the effects of pollution of marine resources is delineated.