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The problems involved in satellite remote sensing of coastal zones are examined. The differences between remote sensing of terrestrial regions and remote sensing of open ocean areas are reviewed. The associate ranges of time and spatial scales and spectral and radiometric resolution are considered. It is concluded that, in general remote sensing of the coastal region is more appropriately performed with aircraft.
The middle infrared portion of the spectrum available for geologic remote sensing extends from approximately 3 to 25 micrometers. The source of energy is thermal radiation from surface materials and ambient terrestrial temperatures. The spectral range of usefulness is limited by both the amount of energy available and by transmission of energy through the atmosphere. The best atmospheric window lies between about 8 and 14 micrometers. Remote sensing of the Earth in the infrared is just on the threshold of becoming a valuable geologic tool. Topics which need study include: (1) the used and limitations of the 8 to 14 micrometer region for distinguishing between silicates and nonsilicates; (2) theoretical and experimental understanding of laboratory spectra of rocks and minerals and their relationship to remotely sensed emission spectra; and (3) the possible use of the 3 to 5 and 17 to 25 micrometer portions of the spectrum for remote sensing.
This paper first examines the extension of two-frequency, or Delta-k near-nadir remote sensing techniques to off-nadir radar altimetry. A different approach to sea state sensing is investigated which appears to offer much higher accuracy. The second section examines the Delta-k method of sensing rough surface area correlation or ocean wavenumber spectrum. The technique shows promise of directly sensing this parameter, in contrast with synthetic-aperture radar methods which are based on complex wave interaction mechanisms and mathematical transformations requiring the acquisition of voluminous data.
A discussion is presented concerning U.S. governmental funding policy for the Land Remote Sensing programs, in which the Landsat spacecraft and the research and development activities associated with them are essential elements. Even if present program management practices were to be changed in the next 1-2 years, the investment of significant amounts of private capital in land remote sensing may be 3-5 years away, due to the immaturity of the prospective markets for the services rendered and the present state of technological development. It is judged that even if NASA is successful in bringing significant private investment into remote sensing activities by the mid-1980s, government must continue to support basic research and expensive technology development in long term and high risk, but potentially high payoff, areas which the still-developing remote sensing industry cannot afford.
Both passive and active remote sensing of atmospheric precipitation are studied with the vector radiative transfer equations by making use of the Mie scattering phase functions and incorporating the raindrop-size distributions. For passive remote sensing, the Gaussian quadrature method is employed to solve for the brightness temperatures. For active remote sensing, an iterative approach carrying out to the second order in albedo is used to calculate for the bistatic coefficients, the backscattering cross sections/unit volume, and the interchannel cross talks. The calculated results are plotted as a function of rainfall rates and compared to various available experimental data. The theoretical model is easily applied to the remote sensing of aerosol particles, smoke, fog, and haze at infrared and visible frequencies.
The present conference on geoscience and remote sensing considers the multispectral remote sensing of saline seeps, the augmentation of LANDSAT MSS data with topographic data, thematic mapping, the sampling problem in radiation budget studies, aerial conductivity measurements over geothermal areas, a comparison of multifrequency band radars for crop classification, the improved estimation of vegetation-covered soil by combined active/passive microwave remote sensing, and atmospheric water vapor profiling by ground-based radiometry. Also discussed are SAR imaging from an inclined geosynchronous orbit, the classification of agricultural crops in radar images, the Ocean Color Experiment on the second orbital flight test of the Space Shuttle, the dielectric properties of wet materials, remote sensing systems for the mm-wave region, and the simulation of spaceborne stereo radar imagery.
The severe North Atlantic storm which damaged the ocean liner Queen Elizabeth 2 (QE2) was studied to assess the impact of remotely sensed marine surface wind data obtained by SEASAT-A, on sea state specifications and forecasts. Alternate representations of the surface wind field in the QE2 storm were produced from the SEASAT enhanced data base, and from operational analyses based upon conventional data. The wind fields were used to drive a high resolution spectral ocean surface wave prediction model. Results show that sea state analyses would have been vastly improved during the period of storm formation and explosive development had remote sensing wind data been available in real time. A modest improvement in operational 12 to 24 hour wave forecasts would have followed automatically from the improved initial state specification made possible by the remote sensing data in both numerical and sea state prediction models. Significantly improved 24 to 48 hour wave forecasts require in addition to remote sensing data, refinement in the numerical and physical aspects of weather prediction models.
A comparison between active and passive sensing of soil moisture over vegetated areas is studied via scattering models. In active sensing three contributing terms to radar backscattering can be identified: (1) the ground surface scatter term; (2) the volume scatter term representing scattering from the vegetation layer; and (3) the surface volume scatter term accounting for scattering from both surface and volume. In emission three sources of contribution can also be identified: (1) surface emission; (2) upward volume emission from the vegetation layer; and (3) downward volume emission scattered upward by the ground surface. As ground moisture increases, terms (1) and (3) increase due to increase in permittivity in the active case. However, in passive sensing, term (1) decreases but term (3) increases for the same reason. This self conpensating effect produces a loss in sensitivity to change in ground moisture. Furthermore, emission from vegetation may be larger than that from the ground. Hence, the presence of vegetation layer causes a much greater loss of sensitivity to passive than active sensing of soil moisture.
Research using satellite remotely sensed data, even within any single scientific discipline, often lacked a unifying principle or strategy with which to plan or integrate studies conducted over an area so large that exhaustive examination is infeasible, e.g., the U.S.A. However, such a series of studies would seem to be at the heart of what makes satellite remote sensing unique, that is the ability to select for study from among remotely sensed data sets distributed widely over the U.S., over time, where the resources do not exist to examine all of them. Using this philosophical underpinning and the concept of a unifying principle, an operational procedure for developing a sampling strategy and formal testable hypotheses was constructed. The procedure is applicable across disciplines, when the investigator restates the research question in symbolic form, i.e., quantifies it. The procedure is set within the statistical framework of general linear models. The dependent variable is any arbitrary function of remotely sensed data and the independent variables are values or levels of factors which represent regional climatic conditions and/or properties of the Earth's surface. These factors are operationally defined as maps from the U.S. National Atlas (U.S.G.S., 1970). Eighty-five maps from the National Atlas, representing climatic and surface attributes, were automated by point counting at an effective resolution of one observation every 17.6 km (11 miles) yielding 22,505 observations per map. The maps were registered to one another in a two step procedure producing a coarse, then fine scale registration. After registration, the maps were iteratively checked for errors using manual and automated procedures. The error free maps were annotated with identification and legend information and then stored as card images, one map to a file. A sampling design will be accomplished through a regionalization analysis of the National Atlas data base (presently being conducted). From this analysis a map of homogeneous regions of the U.S.A. will be created and samples (LANDSAT scenes) assigned by region.
Active and passive microwave remote sensing of earth terrains is studied. Electromagnetic wave scattering and emission from stratified media and rough surfaces are considered with particular application to the remote sensing of soil moisture. Radiative transfer theory for both the random and discrete scatterer models is examined. Vector radiative transfer equations for nonspherical particles are developed for both active and passive remote sensing. Single and multiple scattering solutions are illustrated with applications to remote sensing problems. Analytical wave theory using the Dyson and Bethe-Salpeter equations is employed to treat scattering by random media. The backscattering enhancement effects, strong permittivity fluctuation theory, and modified radiative transfer equations are addressed. The electromagnetic wave scattering from a dense distribution of discrete scatterers is studied. The effective propagation constants and backscattering coefficients are calculated and illustrated for dense media.
A comparison between active and passive sensing of soil moisture over vegetated areas is studied via scattering models. In active sensing three contributing terms to radar backscattering can be identified: (1) the ground surface scatter term; (2) the volume scatter term representing scattering from the vegetation layer; and (3) the surface volume scatter term accounting for scattering from both surface and volume. In emission three sources of contribution can also be identified: (1) surface emission; (2) upward volume emission from the vegetation layer; and (3) downward volume emission scattered upward by the ground surface. As ground moisture increases, terms (1) and (3) increase due to increase in permittivity in the active case. However, in passive sensing, term (1) decreases but term (3) increases for the same reason. This self compensating effect produces a loss in sensitivity to change in ground moisture. Furthermore, emission from vegetation may be larger than that from the ground. Hence, the presence of vegetation layer causes a much greater loss of sensitivity to passive than active sensing of soil moisture.
Most of the remote sensing activities in Brazil have been conducted by the Institute for Space Research (INPE). This report describes briefly INPE's activities in remote sensing in the last years. INPE has been engaged in research (e.g., radiance studies), development (e.g., CCD-scanners, image processing devices) and applications (e.g., crop survey, land use, mineral resources, etc.) of remote sensing. INPE is also responsible for the operation (data reception and processing) of the LANDSATs and meteorological satellites. Data acquisition activities include the development of CCD-Camera to be deployed on board the space shuttle and the construction of a remote sensing satellite.
The evolution of remote sensing techniques in the developing countries of southeast Asia is reviewed. The use of the images for monitoring soil, water, and vegetation resources, in order to develop a national policy for conservation of the resources, is described. The remote sensing data are helpful in observing deforestation in southeast Asia; however, excessive cloud coverage does not allow accurate evaluation of the rice crop. The effects of the capabilities of the developing countries to process the data and remote sensing program of industrial countries on the future application of satellite imagery in developing countries are studied. The need for improved data banking and dissemination of the imagery is analyzed. Agreements on proprietary rights due to the improved ground resolution of orbital sensors are required. The designing of remote sensing equipment to meet the requirements of its users is discussed.
Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.
A dynamic force sensing method is proposed for a robot manipulator. A 6-axis wrist force sensor which is commonly used for robot force sensing does not take the direct measurement of the force and moment applied to an end effector externally from the environment of the manipulator, but takes the resultant of the gravity, the inertial force and moment on the end effector, and the external force and moment. The separation of gravitational and inertial force and moment from the measurement of the force sensor is crucial to achieving dynamically accurate force sensing and fast manipulator motion under force feedback control. A mathematical model is derived for the force sensing process and the separation of the force and moment as a nonlinear optimal state estimation problem formulated. Then an approximate solution is given using extended Kalman filtering techniques.
The properties and advantages of remote sensing lasers are discussed. The theory of nonresonant techniques, which is based on the lidar equation and elastic backscatter, and their applications to aerosol and meteorological parameters are examined. The characteristics and applications of the differential absorption lidar technique, the fluorescence technique, and Raman scattering are described. The use of a laser heterodyne radiometer and fiber optics for remote sensing is studied. Future developments in the field of remote sensing, in particular the improvement of laser sources, the fabrication of compact remote sensing instruments, and space-borne applications for lidar, are considered.
Improved techniques for the remote sensing of the land surface energy balance (SEB) and soil moisture would greatly improve prediction of climate and weather as well as be of benefit to agriculture, hydrology and many associated fields. Most of the satellite remote sensing methods which were researched to date rely upon satellite-measured infrared surface temperatures or their time changes as a remote sensing signal. Optimistically, only four or five levels of information (wet to dry) in surface heating/evaporation are discernable by surface temperature methods and a good understanding of atmospheric conditions is necessary to bring them to this accuracy level. Skin temperature methods were researched as well as begun work on several new methods for the remote sensing of the SEB, some elements of which are applicable to current and retrospective data sources and some which will rely on instrumentation from the Earth Observing System (EOS) program in the 1990s.
A technique of compensating for pneumatic distortion in pressure sensing devices was developed and verified. This compensation allows conventional pressure sensing technology to obtain improved unsteady pressure measurements. Pressure distortion caused by frictional attenuation and pneumatic resonance within the sensing system makes obtaining unsteady pressure measurements by conventional sensors difficult. Most distortion occurs within the pneumatic tubing which transmits pressure impulses from the aircraft's surface to the measurement transducer. To avoid pneumatic distortion, experiment designers mount the pressure sensor at the surface of the aircraft, (called in-situ mounting). In-situ transducers cannot always fit in the available space and sometimes pneumatic tubing must be run from the aircraft's surface to the pressure transducer. A technique to measure unsteady pressure data using conventional pressure sensing technology was developed. A pneumatic distortion model is reduced to a low-order, state-variable model retaining most of the dynamic characteristics of the full model. The reduced-order model is coupled with results from minimum variance estimation theory to develop an algorithm to compensate for the effects of pneumatic distortion. Both postflight and real-time algorithms are developed and evaluated using simulated and flight data.