ALBERT

Description: The development of an integrated approach to the modeling of forest dynamics encompassing submodels of forest growth and succession, soil processes and radiation interactions, is reported. Remote sensing technology is a key element of this study in that it provides data for developing, initializing, updating, and validating the models. The objectives are reviewed, the data collected and models in use are discussed, and a framework for studying interactions between the forest growth, soil process and energy interaction components, is described. Remote sensing technology used in the study includes optical and microwave field, aircraft and satellite borne instruments. The types of data collected during intensive field and aircraft campaigns included bidirectional reflectance, thermal emittance and multifrequency, multipolarization synthetic aperture radar backscatter. Synthetic imagery of derived products such as forest biomass and NDVI (Normalized Difference Vegetative Index), and collections of ground data are being assembled in a georeferenced data base. These data are used to drive or test multidiscipline simulations of forested ecosystems. Enhancements to the modeling environment permit considerable flexibility in configuring simulations and selecting results for reporting and graphical display.

Description: The quantitative interpretation of satellite observations requires the use of mathematical tools to extract the desired information on terrestrial environments from the radiation data collected in space. A whole range of approaches can be pursued, from the development of models capable of explaining the nature of the physical signal being measured and of characterizing the state of the system under observation, to the empirical correlations between the variables of interest and the space measurements. The premises and implications of these approaches are outlined, paying special attention to the mathematical and numerical requirements. The role and specific applications of empirical bidirectional reflectance models is also discussed, even though these models do not contribute to the understanding of the theory of radiation transfer or to the assessment of the variables of interest. The advantages and drawbacks of these various approaches and the research priorities for the next few years are discussed in the context of the planned availability of new sensors.

Description: Management of crop residues, the portion of a crop left in the field after harvest, is an important conservation practice for minimizing soil erosion and for improving water quality. Quantification of crop residue cover is required to evaluate the effectiveness of conservation tillage practices. Methods are needed to quantify residue cover that are rapid, accurate, and objective. The fluorescence of crop residue was found to be a broadband phenomenon with emission maxima at 420 to 495 nm for excitations of 350 to 420 nm. Soils had low intensity broadband emissions over the 400 to 690 nm region for excitations of 300 to 600 nm. The range of relative fluorescence intensities for the crop residues was much greater than the fluorescence observed of the soils. As the crop residues decompose their blue fluorescence values approach the fluorescence of the soil. Fluorescence techniques are concluded to be less ambiguous and better suited for discriminating crop residues and soils than reflectance methods. If properly implemented, fluorescence techniques can be used to quantify, not only crop residue cover, but also photosynthetic efficiency in the field.

Description: The importance of the measurement of wind fields is discussed. Wind regime data can be used to infer the amount and type of wind induced (aerolian) transport of sand and dust, or to establish global circulation models, for example on other planets. Since local measurements are costly and often impossible, it is desired to infer such data from remotely sensed information. A potential mechanism for remotely inferring the wind regime by using synthetic aperture radar data to describe the roughness of the surface is described. A project to estimate the practicality of using such a mechanism is described. An experiment that extends the mechanism to vegetated sites, where the goal is to measure potential for erosion, is reported.

Description: Surface reflectance is required to quantitatively investigate molecular absorption and particle scattering properties of materials on the Earth's surface. Atmospheric aerosol optical depth, surface pressure and water vapor are required to constrain a radiative transfer code for the inversion of measured spectral radiance to apparent surface reflectance. A suite of algorithms using nonlinear least squares fitting techniques are described that directly estimate these atmospheric parameters from spectral radiance measured by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The derived atmospheric parameters are used to constrain a radiative transfer code for the inversion of the imaging spectrometer radiance to apparent reflectance. The derived apparent reflectance is validated with respect to in situ measurement on the same target.

Description: Investigations designed to study land surface hydrologic-atmospheric interactions, showing the potential of L band passive microwave radiometry for measuring surface soil moisture over large areas, are discussed. Satisfying the data needs of these investigations requires the ability to map large areas rapidly. With aircraft systems this means a need for more beam positions over a wider swath on each flightline. For satellite systems the essential problem is resolution. Both of these needs are currently being addressed through the development and verification of Electronically Scanned Thinned Array Radiometer (ESTAR) technology. The ESTAR L band radiometer was evaluated for soil moisture mapping applications in two studies. The first was conducted over the semiarid rangeland Walnut Gulch watershed located in south eastern Arizona (U.S.). The second was performed in the subhumid Little Washita watershed in south west Oklahoma (U.S.). Both tests showed that the ESTAR is capable of providing soil moisture with the same level of accuracy as existing systems.

Description: A weather resistant automatic scanning Sun photometer system is assessed and demonstrated as practical for measurements of aerosol concentrations and properties at remote sites. Interfaced with a transmitter using the Geostationary Data Collection System (GDCS), the data are processed in near real time. The processing allows a time dependence of the aerosols and water vapor and an ongoing assessment of the health and calibration of the instruments. The system's automatic data acquisition, transmission, and processing offer immediate application to atmospheric monitoring and modeling on a regional to global scale and validation of satellite retrievals. It is estimated that under normal circumstances the retrieved aerosol optical thickness has a network wide accuracy of +/- 0.02 from 340 nm to 1020 nm, water vapor +/- 0.2 cm and size distribution from 0.1 to 3 micrometers.

Description: As part of a global program to validate the ocean surface sensors on board ERS-1, a joint experiment on the Grand Banks of Newfoundland was carried out in Nov. 1991. The principal objective was to provide a field validation of ERS-1 Synthetic Aperture Radar (SAR) measurement of ocean surface structure. The NASA-P3 aircraft measurements made during this experiment provide independent measurements of the ocean surface along the validation swath. The Radar Ocean Wave Spectrometer (ROWS) is a radar sensor designed to measure direction of the long wave components using spectral analysis of the tilt induced radar backscatter modulation. This technique greatly differs from SAR and thus, provides a unique set of measurements for use in evaluating SAR performance. Also, an altimeter channel in the ROWS gives simultaneous information on the surface wave height and radar mean square slope parameter. The sets of geophysical parameters (wind speed, significant wave height, directional spectrum) are used to study the SAR's ability to accurately measure ocean gravity waves. The known distortion imposed on the true directional spectrum by the SAR imaging mechanism is discussed in light of the direct comparisons between ERS-1 SAR, airborne Canadian Center for Remote Sensing (CCRS) SAR, and ROWS spectra and the use of the nonlinear ocean SAR transform.

Description: Terrain slopes, which can be measured with Synthetic Aperture Radar (SAR) interferometry either from a height map or from the interferometric phase gradient, were used to calculate the local incidence angle and the correct pixel area. Both are required for correct thematic interpretation of SAR data. The interferometric correlation depends on the pixel area projected on a plane perpendicular to the look vector and requires correction for slope effects. Methods for normalization of the backscatter and interferometric correlation for ERS-1 SAR are presented.

Description: The relationship between the gradient of the interferometric phase and the terrain slope, which, it is thought, would allow a derivation of the terrain slopes without phase unwrapping, is presented. A linear relationship between the interferometric phase gradient and the terrain slopes was found. A quantitative error analysis showed that only very small errors are introduced by these approximations for orbital Synthetic Aperture Radar (SAR) geometries. An example of a slope map for repeat pass interferometry from ERS-1 SAR data is given. A number of direct and indirect applications of the terrain slope are indicated: erosion and avalanche hazard studies, radiometric calibration of SAR data, and normalization of the interferometric correlation coefficient.

Description: Research on the use of active microwaves in remote sensing, presented during plenary and poster sessions, is summarized. The main highlights are: calibration techniques are well understood; innovative modeling approaches have been developed which increase active microwave applications (segmentation prior to model inversion, use of ERS-1 scatterometer, simulations); polarization angle and frequency diversity improves characterization of ice sheets, vegetation, and determination of soil moisture (X band sensor study); SAR (Synthetic Aperture Radar) interferometry potential is emerging; use of multiple sensors/extended spectral signatures is important (increase emphasis).

Description: Crop residues, the portion of the crop left in the field after harvest, can be an important management factor in controlling soil erosion. Methods to quantify residue cover are needed that are rapid, accurate, and objective. Scenes with known amounts of crop residue were illuminated with long wave ultraviolet (UV) radiation and fluorescence images were recorded with an intensified video camera fitted with a 453 to 488 nm band pass filter. A light colored soil and a dark colored soil were used as background for the weathered soybean stems. Residue cover was determined by counting the proportion of the pixels in the image with fluorescence values greater than a threshold. Soil pixels had the lowest gray levels in the images. The values of the soybean residue pixels spanned nearly the full range of the 8-bit video data. Classification accuracies typically were within 3(absolute units) of measured cover values. Video imaging can provide an intuitive understanding of the fraction of the soil covered by residue.

Description: Global study of land surface properties uses AVHRR channels 1 and 2, but channel 3 may be of interest, although its use requires preprocessing. It consists of both a reflective part and an emissive part, the former can be derived from T3, T4 and T5. Since the water vapor affects channel 3, its content is retrieved from the channel 4 and 5 using the split window technique. A formula of reflective part retrieval at 3.75 micrometers is tested in the case of sunglint observations where the emissivities of channels 4 and 5 can be set to the unity. The formula is adapted and validated to land surface using the FIFE-87 data set. Preliminary applications of the reflectance at 3.75 micrometers to the studies of surface properties retrieval, aerosol retrieval over land, and desertic aerosol retrieval, are addressed.

Description: The polarization of the sunlight scattered by atmospheric aerosols or cloud droplets and reflected from ground surfaces or plant canopies may convey much information when used for remote sensing purposes. The typical polarization features of aerosols, cloud droplets, and plant canopies, as observed by ground based and airborne sensors, are investigated, looking especially for those invariant properties amenable to description by simple models when possible. The question of polarization measurements from space is addressed. The interest of such measurements for remote sensing purposes is investigated, and their feasibility is tested by using results obtained during field campaigns of the airborne POLDER instrument, a radiometer designed to measure the directionality and polarization of the sunlight scattered by the ground atmosphere system.

Description: Papers focused on land surface, atmospheric, and ocean properties are reported. Specific comments pertaining to polarization, models and inversion, and measurements, are given. Recommendations are: continued research into the application potential of the BRDF (Bidirectional Reflectance Distribution Function) and polarization properties of ground surface and atmospheric targets; three dimensional models, which account for the statistical behavior of remotely sensed data, should be extended and inverted in order to support analysis of data potentially covering rolling terrain such that pixels represent heterogeneous mixtures of surface cover types and project ground footprints with sizes between 10 to 6 km, the ground pixel sizes of planned future sensors; available reflectance models should be further validated by means of multi dimensional (directional, spectral, temporal) field data and existing models should be intercompared in more depth to evaluate their performance and limitations; existing methods for model inversion should be validated in more depth in order to quantify the practical limitations and the expected accuracy of the parameters retrieved and new approaches should be developed based upon apriori knowledge of plant canopy development and spectral BRDF properties; there is a need to establish a protocol of validation and intercomparison of the indices and compositing techniques which have been proposed during these last years.

Description: Traditionally, the remote sensing community has relied totally on spectral knowledge to extract vegetation characteristics. However, there are other knowledge bases (KB's) that can be used to significantly improve the accuracy and robustness of inference techniques. Using AI (artificial intelligence) techniques a KB system (VEG) was developed that integrates input spectral measurements with diverse KB's. These KB's consist of data sets of directional reflectance measurements, knowledge from literature, and knowledge from experts which are combined into an intelligent and efficient system for making vegetation inferences. VEG accepts spectral data of an unknown target as input, determines the best techniques for inferring the desired vegetation characteristic(s), applies the techniques to the target data, and provides a rigorous estimate of the accuracy of the inference. VEG was developed to: infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; infer percent ground cover from any combination of nadir and/or off-nadir view angles; infer unknown view angle(s) from known view angle(s) (known as view angle extension); and discriminate between user defined vegetation classes using spectral and directional reflectance relationships developed from an automated learning algorithm. The errors for these techniques were generally very good ranging between 2 to 15% (proportional root mean square). The system is designed to aid scientists in developing, testing, and applying new inference techniques using directional reflectance data.

Description: Most earth surfaces, particularly those supporting natural vegetation ecosystems, constitute structurally and spectrally complex surfaces that are distinctly non-Lambertian reflectors. Obtaining meaningful measurements of the directional radiances of landscapes and obtaining estimates of the complete bidirectional reflectance distribution functions of ground targets with complex and variable landscape and radiometric features are challenging tasks. Reasons for the increased interest in directional radiance measurements are presented, and the issues that must be addressed when trying to acquire directional radiances for vegetated land surfaces from different types of remote sensing platforms are discussed. Priority research emphases are suggested, concerning field measurements of directional surface radiances and reflectances for future research. Primarily, emphasis must be given to the acquisition of more complete and directly associated radiometric and biometric parameter data sets that will empower the exploitation of the 'angular dimension' in remote sensing of vegetation through enabling the further development and rigorous validation of state of the art plant canopy models.

Description: Synthetic aperture radar (SAR) images of the Greenland ice sheet collected by an airborne system clearly reveal the four melting facies of this sheet defined 30 years ago from snow stratigraphy studies by glaciologists. In particular, the radar echoes from the percolation facies have radiometric and polarimetric characteristics that are unique among terrestrial surfaces, but that resemble the exotic radar echoes recorded from the icy Galilean satellites. There, the radar signals interact with subsurface, massive ice features created in the cold, dry snow by seasonal melting and refreezing events. The subsurface features act as efficient reflectors of the incident radiation most likely via internal reflections. In the soaked-snow facies, the radar reflectivity is much lower because radar signals are attenuated by the wetter snow before they can interact with subsurface structures. Inversion algorithms to derive geophysical information from the SAR data are developed in both cases to estimate snow wetness in the soaked-snow facies and the mass of ice water retained in the percolation facies.

Description: An operational stratospheric correction scheme used after the Mount Pinatubo (Phillipines) eruption (Jun. 1991) is presented. The stratospheric aerosol distribution is assumed to be only variable with latitude. Each 9 days the latitudinal distribution of the optical thickness is computed by inverting radiances observed in the NOAA AVHRR channel 1 (0.63 micrometers) and channel 2 (0.83 micrometers) over the Pacific Ocean. This radiance data set is used to check the validity of model used for inversion by checking consistency of the optical thickness deduced from each channel as well as optical thickness deduced from different scattering angles. Using the optical thickness profile previously computed and radiative transfer code assuming Lambertian boundary condition, each pixel of channel 1 and 2 are corrected prior to computation of NDVI (Normalized Difference Vegetation Index). Comparison between corrected, non corrected, and years prior to Pinatubo eruption (1989 to 1990) NDVI composite, shows the necessity and the accuracy of the operational correction scheme.

Description: Aspects of aerosol studies and remote sensing are reviewed. Aerosol scatters solar radiation before it reaches the surface and scatters and absorbs it again after it is reflected from the surface and before it reaches the satellite sensor. The effect is spectrally and spatially dependent. Therefore atmospheric aerosol (dust, smoke and air pollution particles) has a significant effect on remote sensing. Correction for the aerosol effect was never achieved on an operational basis though several case studies were demonstrated. Correction can be done in a direct way by deriving the aerosol loading from the image itself and correcting for it using the appropriate radiative transfer model or by an indirect way, by defining remote sensing functions that are less dependent on the aerosol loading. To some degree this was already achieved in global remote sensing of vegetation where a composite of several days of NDVI (Normalized Difference Vegetation Index) measurements, choosing the maximal value, was used instead of a single cloud screened value. The Atmospheric Resistant Vegetation Index (ARVI) introduced recently for the NASA Earth Observing System EOS-MODIS is the most appropriate example of indirect correction, where the index is defined in such a way that the atmospheric effect in the blue spectral channel cancels to a large degree the atmospheric in the red channel in computations of a vegetation index. Atmospheric corrections can also use aerosol climatology and ground based instrumentation.

Description: A session dedicated to high spectral resolution in the solar spectrum, covering topics of calibration, atmospheric correction, geology/pedology, inland water, and vegetation, is reported. The session showed a high degree of diversity in the topics and the approaches used. It was highlighted that high spectral resolution data could provide atmospherically corrected ground level calibrated reflectance values. Important advances were shown in the use of radiative transfer models applied either on water bodies or vegetation. Several studies highlighted the high degree of redundancy contained in high spectral resolution data.

Description: Spectral absorption-coefficients (cross-sections) kappa(sub nu) (/cm/atm) have been measured in the 7.62, 8.97, and 12.3 micrometer bands of HCFC-22 (CHClF2) and the 10.6 micrometer bands of SF6 employing a high-resolution Fourier-transform spectrometer. Temperature and total pressure have been varied to simulate conditions corresponding to tropospheric and stratospheric layers in the atmosphere. The kappa(sub nu) are compared with values measured by us previously using a tunable diode laser spectrometer and with the appropriate entries in HITRAN and GEISA, two of the databases known to the atmospheric scientist. The measured absolute intensities of the bands are compared with previously published values.

Description: Microwave radar and radiometer measurements of grasslands indicate a substantial reduction in sensor sensitivity to soil moisture in the presence of a thatch layer. When this layer is wet it masks changes in the underlying soil, making the canopy appear warm in the case of passive sensors (radiometer) and decreasing backscatter in the active case (scatterometer). A model for a grass canopy with thatch will be presented in this paper to explain this behavior and to compare with observations. The canopy model consists of three layers: grass, thatch, and the underlying soil. The grass blades are modeled by elongated elliptical discs and the thatch is modeled as a collection of disk shaped water droplets (i.e., the dry matter is neglected). The ground is homogeneous and flat. The distorted Born approximation is used to compute the radar cross section of this three layer canopy and the emissivity is computed from the radar cross section using the Peake formulation for the passive problem. Results are computed at L-band (1.4 GHz) and C-band (4.75 GHz) using canopy parameters (i.e., plant geometry, soil moisture, plant moisture, etc.) representative of Konza Prairie grasslands. The results are compared to C-band scatterometer measurements and L-band radiometer measurements at these grasslands.

Description: There have been many significant improvements in the public access to the Space Shuttle Earth Observations Photography Database. New information is provided for the user community on the recently released videodisc of this database. Topics covered included the following: earlier attempts; our first laser videodisc in 1992; the new laser videodisc in 1994; and electronic database access.

Description: The Challenge Awards are designed to provide a unique perspective to students gifted in the arts and humanities from which to understand scientific endeavor by giving students an opportunity to participate in an ongoing research project. In the graduate program, seven students who had participated in previous Challenge Awards programs were selected to help develop the tools for Earth observations for the astronauts on the Space Radar Laboratory (SRL) missions. The goal of the Challenge Awards program was to prepare a training manual for the astronauts on the SRL missions. This paper describes the observations to be made by the astronauts on the SRL missions. The emphasis is on the dynamic seasonal features of the Earth's surface and atmosphere which justify the need for more than one flight of the SRL. Complete notebooks of the sites, global seasonal patterns, examples of radar and the Measurement of Air Pollution from Satellites data, and shuttle photographs have been given to each of the SRL crews.

Description: MacSigma0 is an interactive tool for the Macintosh which allows you to display and make computations from radar data collected by the following sensors: the JPL AIRSAR, ERS-1, JERS-1, and Magellan. The JPL AIRSAR system is a multi-polarimetric airborne synthetic aperture radar developed and operated by the Jet Propulsion Laboratory. It includes the single-frequency L-band sensor mounted on the NASA CV990 aircraft and its replacement, the multi-frequency P-, L-, and C-band sensors mounted on the NASA DC-8. MacSigma0 works with data in the standard JPL AIRSAR output product format, the compressed Stokes matrix format. ERS-1 and JERS-1 are single-frequency, single-polarization spaceborne synthetic aperture radars launched by the European Space Agency and NASDA respectively. To be usable by MacSigma0, The data must have been processed at the Alaska SAR Facility and must be in the "low-resolution" format. Magellan is a spacecraft mission to map the surface of Venus with imaging radar. The project is managed by the Jet Propulsion Laboratory. The spacecraft carries a single-frequency, single-polarization synthetic aperture radar. MacSigma0 works with framelets of the standard MIDR CD-ROM data products. MacSigma0 provides four basic functions: synthesis of images (if necessary), statistical analysis of selected areas, analysis of corner reflectors as a calibration measure (if appropriate and possible), and informative mouse tracking. For instance, the JPL AIRSAR data can be used to synthesize a variety of images such as a total power image. The total power image displays the sum of the polarized and unpolarized components of the backscatter for each pixel. Other images which can be synthesized are HH, HV, VV, RL, RR, HHVV*, HHHV*, HVVV*, HHVV* phase and correlation coefficient images. For the complex and phase images, phase is displayed using color and magnitude is displayed using intensity. MacSigma0 can also be used to compute statistics from within a selected area. The statistics computed depend on the image type. For JPL AIRSAR data, the HH, HV, VV, HHVV* phase, and correlation coefficient means and standard deviation measures are calculated. The mean, relative standard deviation, minimum, and maximum values are calculated for all other data types. A histogram of the selected area is also calculated and displayed. The selected area can be rectangular, linear, or polygonal in shape. The user is allowed to select multiple rectangular areas, but not multiple linear or polygonal areas. The statistics and histogram are displayed to the user and can either be printed or saved as a text file. MacSigma0 can also be used to analyze corner reflectors as a measure of the calibration for JPL AIRSAR, ERS-1, and JERS-1 data types. It computes a theoretical radar cross section and the actual radar cross section for a selected trihedral corner reflector. The theoretical cross section, measured cross section, their ratio in dBs, and other information are displayed to the user and can be saved into a text file. For ERS-1, JERS-1, and Magellan data, MacSigma0 simultaneously displays pixel location in data coordinates and in latitude, longitude coordinates. It also displays sigma0, the incidence angle (for Magellan data), the original pixel value (for Magellan data), and the noise power value (for ERS-1 and JERS-1 data). Grey scale computed images can be saved in a byte format (a headerless format which saves the image as a string of byte values) or a PICT format (a standard format readable by other image processing programs for the Macintosh). Images can also be printed. MacSigma0 is written in C-language for use on Macintosh series computers. The minimum configuration requirements for MacSigma0 are System 6.0, Finder 6.1, 1Mb of RAM, and at least a 4-bit color or grey-scale graphics display. MacSigma0 is also System 7 compatible. To compile the source code, Apple's Macintosh Programmers Workbench (MPW) 3.2 and the MPW C language compiler version 3.2 are required. The source code will not compile with a later version of the compiler; however, the compiled application which will run under the minimum hardware configuration is provided on the distribution medium. In addition, the distribution media includes an executable which runs significantly faster but requires a 68881 compatible math coprocessor and a 68020 compatible CPU. Since JPL AIRSAR data files can be very large, it is often desirable to reduce the size of a data file before transferring it to the Macintosh for use in MacSigma0. A small FORTRAN program which can be used for this purpose is included on the distribution media. MacSigma0 will print statistics on any output device which supports QuickDraw, and it will print images on any device which supports QuickDraw or PostScript. The standard distribution medium for MacSigma0 is a set of five 1.4Mb Macintosh format diskettes. This program was developed in 1992 and is a copyrighted work with all copyright vested in NASA. Version 4.2 of MacSigma0 was released in 1993.

Description: VICAR (Video Image Communication and Retrieval) is a general purpose image processing software system that has been under continuous development since the late 1960's. Originally intended for data from the NASA Jet Propulsion Laboratory's unmanned planetary spacecraft, VICAR is now used for a variety of other applications including biomedical image processing, cartography, earth resources, and geological exploration. The development of this newest version of VICAR emphasized a standardized, easily-understood user interface, a shield between the user and the host operating system, and a comprehensive array of image processing capabilities. Structurally, VICAR can be divided into roughly two parts; a suite of applications programs and an executive which serves as the interfaces between the applications, the operating system, and the user. There are several hundred applications programs ranging in function from interactive image editing, data compression/decompression, and map projection, to blemish, noise, and artifact removal, mosaic generation, and pattern recognition and location. An information management system designed specifically for handling image related data can merge image data with other types of data files. The user accesses these programs through the VICAR executive, which consists of a supervisor and a run-time library. From the viewpoint of the user and the applications programs, the executive is an environment that is independent of the operating system. VICAR does not replace the host computer's operating system; instead, it overlays the host resources. The core of the executive is the VICAR Supervisor, which is based on NASA Goddard Space Flight Center's Transportable Applications Executive (TAE). Various modifications and extensions have been made to optimize TAE for image processing applications, resulting in a user friendly environment. The rest of the executive consists of the VICAR Run-Time Library, which provides a set of subroutines (image I/O, label I/O, parameter I/O, etc.) to facilitate image processing and provide the fastest I/O possible while maintaining a wide variety of capabilities. The run-time library also includes the Virtual Raster Display Interface (VRDI) which allows display oriented applications programs to be written for a variety of display devices using a set of common routines. (A display device can be any frame-buffer type device which is attached to the host computer and has memory planes for the display and manipulation of images. A display device may have any number of separate 8-bit image memory planes (IMPs), a graphics overlay plane, pseudo-color capabilities, hardware zoom and pan, and other features). The VRDI supports the following display devices: VICOM (Gould/Deanza) IP8500, RAMTEK RM-9465, ADAGE (Ikonas) IK3000 and the International Imaging Systems IVAS. VRDI's purpose is to provide a uniform operating environment not only for an application programmer, but for the user as well. The programmer is able to write programs without being concerned with the specifics of the device for which the application is intended. The VICAR Interactive Display Subsystem (VIDS) is a collection of utilities for easy interactive display and manipulation of images on a display device. VIDS has characteristics of both the executive and an application program, and offers a wide menu of image manipulation options. VIDS uses the VRDI to communicate with display devices. The first step in using VIDS to analyze and enhance an image (one simple example of VICAR's numerous capabilities) is to examine the histogram of the image. The histogram is a plot of frequency of occurrence for each pixel value (0 - 255) loaded in the image plane. If, for example, the histogram shows that there are no pixel values below 64 or above 192, the histogram can be "stretched" so that the value of 64 is mapped to zero and 192 is mapped to 255. Now the user can use the full dynamic range of the display device to display the data and better see its contents. Another example of a VIDS procedure is the JMOVIE command, which allows the user to run animations interactively on the display device. JMOVIE uses the concept of "frames", which are the individual frames which comprise the animation to be viewed. The user loads images into the frames after the size and number of frames has been selected. VICAR's source languages are primarily FORTRAN and C, with some VAX Assembler and array processor code. The VICAR run-time library is designed to work equally easily from either FORTRAN or C. The program was implemented on a DEC VAX series computer operating under VMS 4.7. The virtual memory required is 1.5MB. Approximately 180,000 blocks of storage are needed for the saveset. VICAR (version 2.3A/3G/13H) is a copyrighted work with all copyright vested in NASA and is available by license for a period of ten (10) years to approved licensees. This program was developed in 1989.

Description: The Interactive Image Display Program (IMDISP) is an interactive image display utility for the IBM Personal Computer (PC, XT and AT) and compatibles. Until recently, efforts to utilize small computer systems for display and analysis of scientific data have been hampered by the lack of sufficient data storage capacity to accomodate large image arrays. Most planetary images, for example, require nearly a megabyte of storage. The recent development of the "CDROM" (Compact Disk Read-Only Memory) storage technology makes possible the storage of up to 680 megabytes of data on a single 4.72-inch disk. IMDISP was developed for use with the CDROM storage system which is currently being evaluated by the Planetary Data System. The latest disks to be produced by the Planetary Data System are a set of three disks containing all of the images of Uranus acquired by the Voyager spacecraft. The images are in both compressed and uncompressed format. IMDISP can read the uncompressed images directly, but special software is provided to decompress the compressed images, which can not be processed directly. IMDISP can also display images stored on floppy or hard disks. A digital image is a picture converted to numerical form so that it can be stored and used in a computer. The image is divided into a matrix of small regions called picture elements, or pixels. The rows and columns of pixels are called "lines" and "samples", respectively. Each pixel has a numerical value, or DN (data number) value, quantifying the darkness or brightness of the image at that spot. In total, each pixel has an address (line number, sample number) and a DN value, which is all that the computer needs for processing. DISPLAY commands allow the IMDISP user to display all or part of an image at various positions on the display screen. The user may also zoom in and out from a point on the image defined by the cursor, and may pan around the image. To enable more or all of the original image to be displayed on the screen at once, the image can be "subsampled." For example, if the image were subsampled by a factor of 2, every other pixel from every other line would be displayed, starting from the upper left corner of the image. Any positive integer may be used for subsampling. The user may produce a histogram of an image file, which is a graph showing the number of pixels per DN value, or per range of DN values, for the entire image. IMDISP can also plot the DN value versus pixels along a line between two points on the image. The user can "stretch" or increase the contrast of an image by specifying low and high DN values; all pixels with values lower than the specified "low" will then become black, and all pixels higher than the specified "high" value will become white. Pixels between the low and high values will be evenly shaded between black and white. IMDISP is written in a modular form to make it easy to change it to work with different display devices or on other computers. The code can also be adapted for use in other application programs. There are device dependent image display modules, general image display subroutines, image I/O routines, and image label and command line parsing routines. The IMDISP system is written in C-language (94%) and Assembler (6%). It was implemented on an IBM PC with the MS DOS 3.21 operating system. IMDISP has a memory requirement of about 142k bytes. IMDISP was developed in 1989 and is a copyrighted work with all copyright vested in NASA. Additional planetary images can be obtained from the National Space Science Data Center at (301) 286-6695.

Description: PC-SEAPAK is a user-interactive satellite data analysis software package specifically developed for oceanographic research. The program is used to process and interpret data obtained from the Nimbus-7/Coastal Zone Color Scanner (CZCS), and the NOAA Advanced Very High Resolution Radiometer (AVHRR). PC-SEAPAK is a set of independent microcomputer-based image analysis programs that provide the user with a flexible, user-friendly, standardized interface, and facilitates relatively low-cost analysis of oceanographic satellite data. Version 4.0 includes 114 programs. PC-SEAPAK programs are organized into categories which include CZCS and AVHRR level-1 ingest, level-2 analyses, statistical analyses, data extraction, remapping to standard projections, graphics manipulation, image board memory manipulation, hardcopy output support and general utilities. Most programs allow user interaction through menu and command modes and also by the use of a mouse. Most programs also provide for ASCII file generation for further analysis in spreadsheets, graphics packages, etc. The CZCS scanning radiometer aboard the NIMBUS-7 satellite was designed to measure the concentration of photosynthetic pigments and their degradation products in the ocean. AVHRR data is used to compute sea surface temperatures and is supported for the NOAA 6, 7, 8, 9, 10, 11, and 12 satellites. The CZCS operated from November 1978 to June 1986. CZCS data may be obtained free of charge from the CZCS archive at NASA/Goddard Space Flight Center. AVHRR data may be purchased through NOAA's Satellite Data Service Division. Ordering information is included in the PC-SEAPAK documentation. Although PC-SEAPAK was developed on a COMPAQ Deskpro 386/20, it can be run on most 386-compatible computers with an AT bus, EGA controller, Intel 80387 coprocessor, and MS-DOS 3.3 or higher. A Matrox MVP-AT image board with appropriate monitor and cables is also required. Note that the authors have received some reports of incompatibilities between the MVP-AT image board and ZENITH computers. Also, the MVP-AT image board is not necessarily compatible with 486-based systems; users of 486-based systems should consult with Matrox about compatibility concerns. Other PC-SEAPAK requirements include a Microsoft mouse (serial version), 2Mb RAM, and 100Mb hard disk space. For data ingest and backup, 9-track tape, 8mm tape and optical disks are supported and recommended. PC-SEAPAK has been under development since 1988. Version 4.0 was updated in 1992, and is distributed without source code. It is available only as a set of 36 1.2Mb 5.25 inch IBM MS-DOS format diskettes. PC-SEAPAK is a copyrighted product with all copyright vested in the National Aeronautics and Space Administration. Phar Lap's DOS_Extender run-time version is integrated into several of the programs; therefore, the PC-SEAPAK programs may not be duplicated. Three of the distribution diskettes contain DOS_Extender files. One of the distribution diskettes contains Media Cybernetics' HALO88 font files, also licensed by NASA for dissemination but not duplication. IBM is a registered trademark of International Business Machines. MS-DOS is a registered trademark of Microsoft Corporation. HALO88 is a registered trademark of Media Cybernetics, but the product was discontinued in 1991.

Description: The Land Analysis System (LAS) is an image analysis system designed to manipulate and analyze digital data in raster format and provide the user with a wide spectrum of functions and statistical tools for analysis. LAS offers these features under VMS with optional image display capabilities for IVAS and other display devices as well as the X-Windows environment. LAS provides a flexible framework for algorithm development as well as for the processing and analysis of image data. Users may choose between mouse-driven commands or the traditional command line input mode. LAS functions include supervised and unsupervised image classification, film product generation, geometric registration, image repair, radiometric correction and image statistical analysis. Data files accepted by LAS include formats such as Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Advanced Very High Resolution Radiometer (AVHRR). The enhanced geometric registration package now includes both image to image and map to map transformations. The over 200 LAS functions fall into image processing scenario categories which include: arithmetic and logical functions, data transformations, fourier transforms, geometric registration, hard copy output, image restoration, intensity transformation, multispectral and statistical analysis, file transfer, tape profiling and file management among others. Internal improvements to the LAS code have eliminated the VAX VMS dependencies and improved overall system performance. The maximum LAS image size has been increased to 20,000 lines by 20,000 samples with a maximum of 256 bands per image. The catalog management system used in earlier versions of LAS has been replaced by a more streamlined and maintenance-free method of file management. This system is not dependent on VAX/VMS and relies on file naming conventions alone to allow the use of identical LAS file names on different operating systems. While the LAS code has been improved, the original capabilities of the system have been preserved. These include maintaining associated image history, session logging, and batch, asynchronous and interactive mode of operation. The LAS application programs are integrated under version 4.1 of an interface called the Transportable Applications Executive (TAE). TAE 4.1 has four modes of user interaction: menu, direct command, tutor (or help), and dynamic tutor. In addition TAE 4.1 allows the operation of LAS functions using mouse-driven commands under the TAE-Facelift environment provided with TAE 4.1. These modes of operation allow users, from the beginner to the expert, to exercise specific application options. LAS is written in C-language and FORTRAN 77 for use with DEC VAX computers running VMS with approximately 16Mb of physical memory. This program runs under TAE 4.1. Since TAE 4.1 is not a current version of TAE, TAE 4.1 is included within the LAS distribution. Approximately 130,000 blocks (65Mb) of disk storage space are necessary to store the source code and files generated by the installation procedure for LAS and 44,000 blocks (22Mb) of disk storage space are necessary for TAE 4.1 installation. The only other dependencies for LAS are the subroutine libraries for the specific display device(s) that will be used with LAS/DMS (e.g. X-Windows and/or IVAS). The standard distribution medium for LAS is a set of two 9~track 6250 BPI magnetic tapes in DEC VAX BACKUP format. It is also available on a set of two TK50 tape cartridges in DEC VAX BACKUP format. This program was developed in 1986 and last updated in 1992.

Description: Spaceborne Synthetic Aperture Radar (SAR) images are useful for planetary mapping and Earth sciences investigations. However, swath widths rarely exceed 100 Kilometers, and images must be patched together to create a mosaic in order to analyze larger areas. The primary function of this program is to generate large digital mosaics of SAR imagery without manually marked tiepoints. MOSK can produce multiframe mosaics by combining images in the along-track, adjacent cross-track swaths, or ascending and descending passes. Geocoded map registered images, such as the ones produced by MAPJTC (NPO-17718), are required as input. The output is a geocoded mosaic on a standard map grid which permits easy registration with other geocoded data sets. Mosaicking of geocoded SAR imagery involves three steps. First, a match point is selected at the center of the overlapping area, then an image patch around the match point is extracted from both images and cross-correlation is done on this area. Then, images with their refined match points are merged together to form a mosaic. To handle the large data volume of overlapping intermediate stages, large mosaics are divided into equal size quadrants with each quadrant cut from an intermediate mosaic. The full mosaic can then be assembled from the individual quadrants. Finally, radiometric disparities at the image seams are smoothed by a "feathering" technique. The automatic mosaic system generates output with minimal operator interaction. However, manual tiepointing is required in cases of a large registration error or two images with smooth surfaces such as ocean images. MOSK is implemented on a DEC VAX 11/785 running VMS 4.5. Most subroutines are in FORTRAN, but three are in MAXL and one is in APAL. The program requires 1 Mb of memory and a Floating Point Systems AP-5210 array processor. The system memory usage is approximately 1000 pages and the requirement of page file size is 2000 blocks. MOSK was developed in 1988.

Description: MAPJTC was designed to rectify and transform the standard image output of the digital Synthetic Aperture Radar (SAR) correlator into a geocoded map registered image without operator interaction or manual tiepointing. This is accomplished by modeling the distortions and predicting the pixel displacements based on platform and radar parameters. The map projection implemented in MAPJTC is the Universal Transverse Mercator. Since the re-sampling operation is independent of the transformation data generation, other cartographic projections can be implemented with few software modifications. MAPJTC makes a precise determination of the geodetic location of an arbitrary pixel within the image frame based on the simultaneous solution of a set of earth model equations, SAR Doppler equations, and SAR range equations that identify the slant range from the sensor to the target at a specific image pixel. Based on a table of geodetic coordinates of the image pixels, the image is then mapped onto the desired cartographic projection by applying the appropriate transformation equations. Typically, mapping involves a two-dimensional re-sampling and is very computationally intensive. MAPJTC reduces the procedure to two one-dimensional passes, which saves computer time. Geocoding transforms the rectified image into a grid defined by a specific map projection. (The image is rotated and rectified to match the map projection.) Again, the two dimensional re-sampling process can be separated into two one-dimensional re-sampling processes. Optionally, MAPJTC can correct terrain-induced distortions in SAR imagery when a digital elevation map is available. MAPJTC was developed on a DEC VAX 11/785 under VMS 4.5. The program is written in FORTRAN (84%), APAL (2%), and MAXL (14%). It requires 6Mb of memory and a Floating Point Systems AP-5210 Array Processor equipped with 1Mb of memory. MAPJTC can run interactively or as a batch job. MAPJTC was developed in 1987.

Description: The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

Description: The Spectral Analysis Manager (SPAM) was developed to allow easy qualitative analysis of multi-dimensional imaging spectrometer data. Imaging spectrometers provide sufficient spectral sampling to define unique spectral signatures on a per pixel basis. Thus direct material identification becomes possible for geologic studies. SPAM provides a variety of capabilities for carrying out interactive analysis of the massive and complex datasets associated with multispectral remote sensing observations. In addition to normal image processing functions, SPAM provides multiple levels of on-line help, a flexible command interpretation, graceful error recovery, and a program structure which can be implemented in a variety of environments. SPAM was designed to be visually oriented and user friendly with the liberal employment of graphics for rapid and efficient exploratory analysis of imaging spectrometry data. SPAM provides functions to enable arithmetic manipulations of the data, such as normalization, linear mixing, band ratio discrimination, and low-pass filtering. SPAM can be used to examine the spectra of an individual pixel or the average spectra over a number of pixels. SPAM also supports image segmentation, fast spectral signature matching, spectral library usage, mixture analysis, and feature extraction. High speed spectral signature matching is performed by using a binary spectral encoding algorithm to separate and identify mineral components present in the scene. The same binary encoding allows automatic spectral clustering. Spectral data may be entered from a digitizing tablet, stored in a user library, compared to the master library containing mineral standards, and then displayed as a timesequence spectral movie. The output plots, histograms, and stretched histograms produced by SPAM can be sent to a lineprinter, stored as separate RGB disk files, or sent to a Quick Color Recorder. SPAM is written in C for interactive execution and is available for two different machine environments. There is a DEC VAX/VMS version with a central memory requirement of approximately 242K of 8 bit bytes and a machine independent UNIX 4.2 version. The display device currently supported is the Raster Technologies display processor. Other 512 x 512 resolution color display devices, such as De Anza, may be added with minor code modifications. This program was developed in 1986.

Description: The Science and Technology Laboratory Applications Software (ELAS) was originally designed to analyze and process digital imagery data, specifically remotely-sensed scanner data. This capability includes the processing of Landsat multispectral data; aircraft-acquired scanner data; digitized topographic data; and numerous other ancillary data, such as soil types and rainfall information, that can be stored in digitized form. ELAS has the subsequent capability to geographically reference this data to dozens of standard, as well as user created projections. As an integrated image processing system, ELAS offers the user of remotely-sensed data a wide range of capabilities in the areas of land cover analysis and general purpose image analysis. ELAS is designed for flexible use and operation and includes its own FORTRAN operating subsystem and an expandable set of FORTRAN application modules. Because all of ELAS resides in one "logical" FORTRAN program, data inputs and outputs, directives, and module switching are convenient for the user. There are over 230 modules presently available to aid the user in performing a wide range of land cover analyses and manipulation. The file management modules enable the user to allocate, define, access, and specify usage for all types of files (ELAS files, subfiles, external files etc.). Various other modules convert specific types of satellite, aircraft, and vector-polygon data into files that can be used by other ELAS modules. The user also has many module options which aid in displaying image data, such as magnification/reduction of the display; true color display; and several memory functions. Additional modules allow for the building and manipulation of polygonal areas of the image data. Finally, there are modules which allow the user to select and classify the image data. An important feature of the ELAS subsystem is that its structure allows new applications modules to be easily integrated in the future. ELAS has as a standard the flexibility to process data elements exceeding 8 bits in length, including floating point (noninteger) elements and 16 or 32 bit integers. Thus it is able to analyze and process "non-standard" nonimage data. The VAX (ERL-10017) and Concurrent (ERL-10013) versions of ELAS 9.0 are written in FORTRAN and ASSEMBLER for DEC VAX series computers running VMS and Concurrent computers running MTM. The Sun (SSC-00019), Masscomp (SSC-00020), and Silicon Graphics (SSC-00021) versions of ELAS 9.0 are written in FORTRAN 77 and C-LANGUAGE for Sun4 series computers running SunOS, Masscomp computers running UNIX, and Silicon Graphics IRIS computers running IRIX. The Concurrent version requires at least 15 bit addressing and a direct memory access channel. The VAX and Concurrent versions of ELAS both require floating-point hardware, at least 1Mb of RAM, and approximately 70Mb of disk space. Both versions also require a COMTAL display device in order to display images. For the Sun, Masscomp, and Silicon Graphics versions of ELAS, the disk storage required is approximately 115Mb, and a minimum of 8Mb of RAM is required for execution. The Sun version of ELAS requires either the X-Window System Version 11 Revision 4 or Sun OpenWindows Version 2. The Masscomp version requires a GA1000 display device and the associated "gp" library. The Silicon Graphics version requires Silicon Graphics' GL library. ELAS display functions will not work with a monochrome monitor. The standard distribution medium for the VAX version (ERL~10017) is a set of two 9-track 1600 BPI magnetic tapes in DEC VAX BACKUP format. This version is also available on a TK50 tape cartridge in DEC VAX BACKUP format. The standard distribution medium for the Concurrent version (ERL-10013) is a set of two 9-track 1600 BPI magnetic tapes in Concurrent BACKUP format. The standard distribution medium for the Sun version (SSC-00019) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Masscomp version, (SSC-00020) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Silicon Graphics version (SSC-00021) is a .25 inch streaming magnetic IRIS tape cartridge in UNIX tar format. Version 9.0 was released in 1991. Sun4, SunOS, and Open Windows are trademarks of Sun Microsystems, Inc. MIT X Window System is licensed by Massachusetts Institute of Technology.

Description: The Science and Technology Laboratory Applications Software (ELAS) was originally designed to analyze and process digital imagery data, specifically remotely-sensed scanner data. This capability includes the processing of Landsat multispectral data; aircraft-acquired scanner data; digitized topographic data; and numerous other ancillary data, such as soil types and rainfall information, that can be stored in digitized form. ELAS has the subsequent capability to geographically reference this data to dozens of standard, as well as user created projections. As an integrated image processing system, ELAS offers the user of remotely-sensed data a wide range of capabilities in the areas of land cover analysis and general purpose image analysis. ELAS is designed for flexible use and operation and includes its own FORTRAN operating subsystem and an expandable set of FORTRAN application modules. Because all of ELAS resides in one "logical" FORTRAN program, data inputs and outputs, directives, and module switching are convenient for the user. There are over 230 modules presently available to aid the user in performing a wide range of land cover analyses and manipulation. The file management modules enable the user to allocate, define, access, and specify usage for all types of files (ELAS files, subfiles, external files etc.). Various other modules convert specific types of satellite, aircraft, and vector-polygon data into files that can be used by other ELAS modules. The user also has many module options which aid in displaying image data, such as magnification/reduction of the display; true color display; and several memory functions. Additional modules allow for the building and manipulation of polygonal areas of the image data. Finally, there are modules which allow the user to select and classify the image data. An important feature of the ELAS subsystem is that its structure allows new applications modules to be easily integrated in the future. ELAS has as a standard the flexibility to process data elements exceeding 8 bits in length, including floating point (noninteger) elements and 16 or 32 bit integers. Thus it is able to analyze and process "non-standard" nonimage data. The VAX (ERL-10017) and Concurrent (ERL-10013) versions of ELAS 9.0 are written in FORTRAN and ASSEMBLER for DEC VAX series computers running VMS and Concurrent computers running MTM. The Sun (SSC-00019), Masscomp (SSC-00020), and Silicon Graphics (SSC-00021) versions of ELAS 9.0 are written in FORTRAN 77 and C-LANGUAGE for Sun4 series computers running SunOS, Masscomp computers running UNIX, and Silicon Graphics IRIS computers running IRIX. The Concurrent version requires at least 15 bit addressing and a direct memory access channel. The VAX and Concurrent versions of ELAS both require floating-point hardware, at least 1Mb of RAM, and approximately 70Mb of disk space. Both versions also require a COMTAL display device in order to display images. For the Sun, Masscomp, and Silicon Graphics versions of ELAS, the disk storage required is approximately 115Mb, and a minimum of 8Mb of RAM is required for execution. The Sun version of ELAS requires either the X-Window System Version 11 Revision 4 or Sun OpenWindows Version 2. The Masscomp version requires a GA1000 display device and the associated "gp" library. The Silicon Graphics version requires Silicon Graphics' GL library. ELAS display functions will not work with a monochrome monitor. The standard distribution medium for the VAX version (ERL~10017) is a set of two 9-track 1600 BPI magnetic tapes in DEC VAX BACKUP format. This version is also available on a TK50 tape cartridge in DEC VAX BACKUP format. The standard distribution medium for the Concurrent version (ERL-10013) is a set of two 9-track 1600 BPI magnetic tapes in Concurrent BACKUP format. The standard distribution medium for the Sun version (SSC-00019) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Masscomp version, (SSC-00020) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Silicon Graphics version (SSC-00021) is a .25 inch streaming magnetic IRIS tape cartridge in UNIX tar format. Version 9.0 was released in 1991. Sun4, SunOS, and Open Windows are trademarks of Sun Microsystems, Inc. MIT X Window System is licensed by Massachusetts Institute of Technology.

Description: IMAGEP is a FORTRAN computer algorithm containing various image processing, analysis, and enhancement functions. It is a keyboard-driven program organized into nine subroutines. Within the subroutines are other routines, also, selected via keyboard. Some of the functions performed by IMAGEP include digitization, storage and retrieval of images; image enhancement by contrast expansion, addition and subtraction, magnification, inversion, and bit shifting; display and movement of cursor; display of grey level histogram of image; and display of the variation of grey level intensity as a function of image position. This algorithm has possible scientific, industrial, and biomedical applications in material flaw studies, steel and ore analysis, and pathology, respectively. IMAGEP is written in VAX FORTRAN for DEC VAX series computers running VMS. The program requires the use of a Grinnell 274 image processor which can be obtained from Mark McCloud Associates, Campbell, CA. An object library of the required GMR series software is included on the distribution media. IMAGEP requires 1Mb of RAM for execution. The standard distribution medium for this program is a 1600 BPI 9~track magnetic tape in VAX FILES-11 format. It is also available on a TK50 tape cartridge in VAX FILES-11 format. This program was developed in 1991. DEC, VAX, VMS, and TK50 are trademarks of Digital Equipment Corporation.

Description: A brief mission overview of STS-49 is given, and some of the pictorially outstanding and scientifically interesting photographs obtained during the mission are presented. The Earth observations are described and include the following: the Southwestern Pacific Ocean -- wind and water; the Southwestern Pacific Ocean -- coasts and volcanoes; the US; Cuba and the Bahamas; South America; Africa; the Red Sea and Western Indian Ocean; and the Indian Subcontinent.

Description: The Science and Technology Laboratory Applications Software (ELAS) was originally designed to analyze and process digital imagery data, specifically remotely-sensed scanner data. This capability includes the processing of Landsat multispectral data; aircraft-acquired scanner data; digitized topographic data; and numerous other ancillary data, such as soil types and rainfall information, that can be stored in digitized form. ELAS has the subsequent capability to geographically reference this data to dozens of standard, as well as user created projections. As an integrated image processing system, ELAS offers the user of remotely-sensed data a wide range of capabilities in the areas of land cover analysis and general purpose image analysis. ELAS is designed for flexible use and operation and includes its own FORTRAN operating subsystem and an expandable set of FORTRAN application modules. Because all of ELAS resides in one "logical" FORTRAN program, data inputs and outputs, directives, and module switching are convenient for the user. There are over 230 modules presently available to aid the user in performing a wide range of land cover analyses and manipulation. The file management modules enable the user to allocate, define, access, and specify usage for all types of files (ELAS files, subfiles, external files etc.). Various other modules convert specific types of satellite, aircraft, and vector-polygon data into files that can be used by other ELAS modules. The user also has many module options which aid in displaying image data, such as magnification/reduction of the display; true color display; and several memory functions. Additional modules allow for the building and manipulation of polygonal areas of the image data. Finally, there are modules which allow the user to select and classify the image data. An important feature of the ELAS subsystem is that its structure allows new applications modules to be easily integrated in the future. ELAS has as a standard the flexibility to process data elements exceeding 8 bits in length, including floating point (noninteger) elements and 16 or 32 bit integers. Thus it is able to analyze and process "non-standard" nonimage data. The VAX (ERL-10017) and Concurrent (ERL-10013) versions of ELAS 9.0 are written in FORTRAN and ASSEMBLER for DEC VAX series computers running VMS and Concurrent computers running MTM. The Sun (SSC-00019), Masscomp (SSC-00020), and Silicon Graphics (SSC-00021) versions of ELAS 9.0 are written in FORTRAN 77 and C-LANGUAGE for Sun4 series computers running SunOS, Masscomp computers running UNIX, and Silicon Graphics IRIS computers running IRIX. The Concurrent version requires at least 15 bit addressing and a direct memory access channel. The VAX and Concurrent versions of ELAS both require floating-point hardware, at least 1Mb of RAM, and approximately 70Mb of disk space. Both versions also require a COMTAL display device in order to display images. For the Sun, Masscomp, and Silicon Graphics versions of ELAS, the disk storage required is approximately 115Mb, and a minimum of 8Mb of RAM is required for execution. The Sun version of ELAS requires either the X-Window System Version 11 Revision 4 or Sun OpenWindows Version 2. The Masscomp version requires a GA1000 display device and the associated "gp" library. The Silicon Graphics version requires Silicon Graphics' GL library. ELAS display functions will not work with a monochrome monitor. The standard distribution medium for the VAX version (ERL~10017) is a set of two 9-track 1600 BPI magnetic tapes in DEC VAX BACKUP format. This version is also available on a TK50 tape cartridge in DEC VAX BACKUP format. The standard distribution medium for the Concurrent version (ERL-10013) is a set of two 9-track 1600 BPI magnetic tapes in Concurrent BACKUP format. The standard distribution medium for the Sun version (SSC-00019) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Masscomp version, (SSC-00020) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Silicon Graphics version (SSC-00021) is a .25 inch streaming magnetic IRIS tape cartridge in UNIX tar format. Version 9.0 was released in 1991. Sun4, SunOS, and Open Windows are trademarks of Sun Microsystems, Inc. MIT X Window System is licensed by Massachusetts Institute of Technology.

Description: The Science and Technology Laboratory Applications Software (ELAS) was originally designed to analyze and process digital imagery data, specifically remotely-sensed scanner data. This capability includes the processing of Landsat multispectral data; aircraft-acquired scanner data; digitized topographic data; and numerous other ancillary data, such as soil types and rainfall information, that can be stored in digitized form. ELAS has the subsequent capability to geographically reference this data to dozens of standard, as well as user created projections. As an integrated image processing system, ELAS offers the user of remotely-sensed data a wide range of capabilities in the areas of land cover analysis and general purpose image analysis. ELAS is designed for flexible use and operation and includes its own FORTRAN operating subsystem and an expandable set of FORTRAN application modules. Because all of ELAS resides in one "logical" FORTRAN program, data inputs and outputs, directives, and module switching are convenient for the user. There are over 230 modules presently available to aid the user in performing a wide range of land cover analyses and manipulation. The file management modules enable the user to allocate, define, access, and specify usage for all types of files (ELAS files, subfiles, external files etc.). Various other modules convert specific types of satellite, aircraft, and vector-polygon data into files that can be used by other ELAS modules. The user also has many module options which aid in displaying image data, such as magnification/reduction of the display; true color display; and several memory functions. Additional modules allow for the building and manipulation of polygonal areas of the image data. Finally, there are modules which allow the user to select and classify the image data. An important feature of the ELAS subsystem is that its structure allows new applications modules to be easily integrated in the future. ELAS has as a standard the flexibility to process data elements exceeding 8 bits in length, including floating point (noninteger) elements and 16 or 32 bit integers. Thus it is able to analyze and process "non-standard" nonimage data. The VAX (ERL-10017) and Concurrent (ERL-10013) versions of ELAS 9.0 are written in FORTRAN and ASSEMBLER for DEC VAX series computers running VMS and Concurrent computers running MTM. The Sun (SSC-00019), Masscomp (SSC-00020), and Silicon Graphics (SSC-00021) versions of ELAS 9.0 are written in FORTRAN 77 and C-LANGUAGE for Sun4 series computers running SunOS, Masscomp computers running UNIX, and Silicon Graphics IRIS computers running IRIX. The Concurrent version requires at least 15 bit addressing and a direct memory access channel. The VAX and Concurrent versions of ELAS both require floating-point hardware, at least 1Mb of RAM, and approximately 70Mb of disk space. Both versions also require a COMTAL display device in order to display images. For the Sun, Masscomp, and Silicon Graphics versions of ELAS, the disk storage required is approximately 115Mb, and a minimum of 8Mb of RAM is required for execution. The Sun version of ELAS requires either the X-Window System Version 11 Revision 4 or Sun OpenWindows Version 2. The Masscomp version requires a GA1000 display device and the associated "gp" library. The Silicon Graphics version requires Silicon Graphics' GL library. ELAS display functions will not work with a monochrome monitor. The standard distribution medium for the VAX version (ERL~10017) is a set of two 9-track 1600 BPI magnetic tapes in DEC VAX BACKUP format. This version is also available on a TK50 tape cartridge in DEC VAX BACKUP format. The standard distribution medium for the Concurrent version (ERL-10013) is a set of two 9-track 1600 BPI magnetic tapes in Concurrent BACKUP format. The standard distribution medium for the Sun version (SSC-00019) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Masscomp version, (SSC-00020) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Silicon Graphics version (SSC-00021) is a .25 inch streaming magnetic IRIS tape cartridge in UNIX tar format. Version 9.0 was released in 1991. Sun4, SunOS, and Open Windows are trademarks of Sun Microsystems, Inc. MIT X Window System is licensed by Massachusetts Institute of Technology.

Description: MacMultiview is an interactive tool for the Macintosh II family which allows one to display and make computations utilizing polarimetric radar data collected by the Jet Propulsion Laboratory's imaging SAR (synthetic aperture radar) polarimeter system. The system includes the single-frequency L-band sensor mounted on the NASA CV990 aircraft and its replacement, the multi-frequency P-, L-, and C-band sensors mounted on the NASA DC-8. MacMultiview provides two basic functions: computation of synthesized polarimetric images and computation of polarization signatures. The radar data can be used to compute a variety of images. The total power image displays the sum of the polarized and unpolarized components of the backscatter for each pixel. The magnitude/phase difference image displays the HH (horizontal transmit and horizontal receive polarization) to VV (vertical transmit and vertical receive polarization) phase difference using color. Magnitude is displayed using intensity. The user may also select any transmit and receive polarization combination from which an image is synthesized. This image displays the backscatter which would have been observed had the sensor been configured using the selected transmit and receive polarizations. MacMultiview can also be used to compute polarization signatures, three dimensional plots of backscatter versus transmit and receive polarizations. The standard co-polarization signatures (transmit and receive polarizations are the same) and cross-polarization signatures (transmit and receive polarizations are orthogonal) can be plotted for any rectangular subset of pixels within a radar data set. In addition, the ratio of co- and cross-polarization signatures computed from different subsets within the same data set can also be computed. Computed images can be saved in a variety of formats: byte format (headerless format which saves the image as a string of byte values), MacMultiview (a byte image preceded by an ASCII header), and PICT2 format (standard format readable by MacMultiview and other image processing programs for the Macintosh). Images can also be printed on PostScript output devices. Polarization signatures can be saved in either a PICT format or as a text file containing PostScript commands and printed on any QuickDraw output device. The associated Stokes matrices can be stored in a text file. MacMultiview is written in C-language for Macintosh II series computers. MacMultiview will only run on Macintosh II series computers with 8-bit video displays (gray shades or color). The program also requires a minimum configuration of System 6.0, Finder 6.1, and 1Mb of RAM. MacMultiview is NOT compatible with System 7.0. It requires 32-Bit QuickDraw. Note: MacMultiview may not be fully compatible with preliminary versions of 32-Bit QuickDraw. Macintosh Programmer's Workshop and Macintosh Programmer's Workshop C (version 3.0) are required for recompiling and relinking. The standard distribution medium for this package is a set of three 800K 3.5 inch diskettes in Macintosh format. This program was developed in 1989 and updated in 1991. MacMultiview is a copyrighted work with all copyright vested in NASA. QuickDraw, Finder, Macintosh, and System 7 are trademarks of Apple Computer, Inc.

Description: Background information and exercises are provided to: (1) establish or expand understanding of the concepts, methods, and terminology of computer processing of image producing data; (2) develop insight into the advantages of computer based image processing compared with the photointerpretation approach for processing, classifying, interpreting, and applying remote sensing data; (3) foster a broad perspective on the principal of the main techniques for image enhancement, pattern recognition, and thematic classification; (4) appreciate the pros and cons of batch and interactive modes of image analysis; (5) examine and evaluate some specific computer generated products for subscenes in Pennsylvania and New Jersey; and (6) interrelate these particular examples of output with more theoretical explanations of computer processing strategies and procedures.

Description: The accurate partitioning of available energy into sensible and latent heat flux is crucial to the understanding of surface atmosphere interactions. This issue is more complicated in arid and semi arid regions where the relative contribution to surface fluxes from the soil and vegetation may vary significantly throughout the day and throughout the season. A three component model to estimate sensible heat flux over heterogeneous surfaces is presented. The surface was represented with two adjacent compartments. The first compartment is made up of two components, shrubs and shaded soil, the second of open 'illuminated' soil. Data collected at two different sites in Nevada (U.S.) during the Summers of 1991 and 1992 were used to evaluate model performance. The results show that the present model is sufficiently general to yield satisfactory results for both sites.

Description: Images characteristics of geographic regions other than the northeastern part of the United States are presented for interpretation. Pre- and post-eruption imagery of Mt. St. Helens volcano serves to demonstrate the advantages of thermal infrared sensing, and the potential for developing a timely, decision oriented thematic map to be used in solving drought-related problems in Upper Volta is examined to show the applicability of satellite remote sensing in all geographic areas.

Description: The 1980 eruptions of Mount St. Helens in southeast Washington resulted in a pronounced effect on the surface and ground water resources of the state. In response to the volcanic activity, the U.S. Geological Survey intensified statewide surface and ground water sampling programs to determine the nature and magnitude of the volcanic-induced variations. Streams to the east of Mount St. Helens received the major ash fallout. Chemical effects were best noted in smaller streams sampled 60 to 70 miles northeast of Mount St. Helens. The chemical variations observed were pronounced but short lived. Sulfate and chloride increases in anionic composition were prevalent immediately following the eruption; however, the original bicarbonate predominance was again attained within several days. Suspended iron and aluminum concentrations were similarly elevated during the period of greatest ash deposition (highest turbidity); however, the dissolved concentrations remained relatively constant. Depressions of pH were minor and short lived. Streams draining to the south, tributaries to the Columbia river, showed little observable changes in water chemistry. Streams draining to the west (Toutle river and its tributaries) were compositionally affected by the various volcanic activities. Chloride and sulfate anion percentage exceeded the bicarbonate percentage up to one month following the eruption period. Streams and lakes sampled in the immediate vicinity of Mount St. Helens, in addition to trace metals, contained organic compounds derived from decomposing wood buried in the debris deposits. This organic material may constitute a significant source of organic compounds to surface and ground water for some time to come.

Description: The benefits-to-cost ratio of satellite remote sensing, both as a substitute for conventional methods of monitoring and assessing resources, and as a supplement to these methods is examined using a model which analyzes the cost of aerial photography versus satellite scanner for producing and interpreting an image of the Earth's surface sized to LANDSAT dimensions. Examples of cost savings are tabulated for ground surveys, aerial photos, and LANDSAT. Possible additional benefits from LANDSAT D are assessed. The way in which satellites fit into more comprehensive models for resources management is discussed. It is shown that remote sensing is but one essential component in a complex system that aggregates technical. Socioeconomics, political, cultural, and other factors in the human decision process.

Description: Computer processing facilitates extraction of information from every pixel by executing a variety of functional operations, called processed algorithms, in general or specialized routines. The best results are obtained when data from more than one multispectral band are used together. Multivariate tatistical analysis, computer tape characteristics, processing modes, and a choice of systems (batch or interactive) are discussed. The major operations in computer processing elaborated include: preprocessing, enhancement, effects of rationing, and classification. Techniques for multisource data correlation are considered with emphasis on geobased systems.

Description: Learning objectives include: (1) developing an understanding of the implications of the term "near surface observations"; (2) associating the appearance of large ground features as seen in satellite imagery with their appearance as seen from the ground; (3) grasping criteria and procedures for selecting training sites on the ground for use in supervised classification; (4) running through an example of training site selection; (5) becoming familiar with several methods of accuracy assessment; (6) becoming aware of the approach and value of making supporting measurements of the spectral and physical properties of materials on the ground and from aircraft; (7) taking note of the different types of instruments used in making specific ground measurements; and (8) appreciating the rationale underlying laboratory and field studies on or near the Earth's surface for the purpose of developing new sensor systems.

Description: Learning objectives include: (1) developing a facility for applying conventional techniques of photointerpretation to small scale (satellite) imager; (2) promoting the ability to locate, identify, and interpret small natural and man made surface features in a LANDSAT image; (3) using supporting imagery, such as aerial and space photography, to conduct specific applications analyses; (4) learning to apply change detection techniques to recognize and explain transient and temporal events in individual or seasonal imagery; (5) producing photointerpretation maps that define major surface units, themes, or classes; (6) classifying or analyzing a scene for specific discipline applications in geology, agriculture, forestry, hyrology, coastal wetlands, and environmental pollution; and (7) evaluating both advantages and shortcomings in relying on the photointerpretive approach (rather than computer based analytical approach) for extracting information from LANDSAT data.

Description: Activities are provided for: (1) developing insight into the way in which the LANDSAT MSS produces multispectral data; (2) promoting understanding of what a "pixel" means in a LANDSAT image and the implications of the term "mixed pixel"; (3) explaining the concept of spectral signatures; (4) deriving a simple signature for a class or feature by analysis: of the four band images; (5) understanding the production of false color composites; (6) appreciating the use of color additive techniques; (7) preparing Diazo images; and (8) making quick visual identifications of major land cover types by their characteristic gray tones or colors in LANDSAT images.

Description: Learning objectives of the activities provided include: (1) reading the annotation of a LANDSAT image; (2) becoming acquainted with the characteristics of 1:1,000,000 scale transparencies and prints of MSS images; (3) noting the general information visible in LANDSAT photo products; (4) observing changes of appearance of any ground feature or class in the black and white images made from the four MSS bands and the characteristic color of each class in color composites; (5) determining the degree to which a LANDSAT image meets map accuracy standards and can be fitted to map projections; (6) assessing the effects of LANDSAT enlargements and scale changes and of the limitations of satellite resolution relative to aerial photos; (7) observing the influence of time of acquisition (season) on a scene; (8) getting a feel for image quality as dependent on processing and photoreproduction; (9) appreciating the characteristics of the RBV and thermal band imagery obtained from LANDSAT-3; and (10) becoming familiar with certain attributes of adjacent LANDSAT images which permit them to be joined in mosaics and to be viewed in stereo.

Description: The primary LANDSAT mission and the system requirements are summarized and pertinent parameters of the spacecraft, its orbit, and payload are tabulated. The history acquisition to entry into the archives for storage and product generation and dissemination is recounted. The LANDSAT D data handling plan is discussed showing requirements for both the MSS CCT and the thematic mapper CCT.

Description: The term remote sensing is defined as well as ideas such as class, pattern, feature, pattern recognition, feature extraction, and theme. The electromagnetic spectrum is examined especially those wavelength regions available to remote sensing. Relevant energy and wave propagation laws are discussed and the characteristics of emitted and reflected radiation and their detection are investigated. The identification of classes by their spectral signatures, the multispectral approach, and the principal types of sensors and platforms used in remote sensing are also considered.

Description: The history of remote sensing is reviewed and the scope and versatility of the several remote sensing systems already in orbit are discussed, especially those with sensors operating in other EM spectral modes. The multisensor approach is examined by interrelating LANDSAT observations with data from other satellite systems. The basic principles and practices underlying the use of thermal infrared and radar sensors are explored and the types of observations and interpretations emanating from the Nimbus, Heat Capacity Mapping Mission, and SEASAT programs are examined. Approved or proposed Earth resources oriented missions for the 1980's previewed include LANDSAT D, Stereosat, Gravsat, the French satellite SPOT-1, and multimission modular spacecraft launched from space shuttle. The pushbroom imager, the linear array pushbroom radiometer, the multispectral linear array, and the operational LANDSAT observing system, to be designed the LANDSAT-E series are also envisioned for this decade.

Description: The use of computer aided classification of LANDSAT data in developing water quality plans for New Jersey watersheds is used to exemplify how a state natural resource management program benefits from satellite imagery. The transition of a research and development system into an operational remote sensing system to help decision makers is demonstrated. Nontechnial issues that can assist (or hinder) an agency in adopting a new technology are examined. The progress of LANDSAT use by state government from the earliest stage of curiosity through to incorporation in actual state planning methods is charted. Potential applications of LANDSAT data to real information needs and solutions to management problems are examined. The problems and mistakes that occurred in using LANDSAT data in the past are discussed as well as the ways by which these problems were overcome.

Description: Information and activities are provided to: (1) enhance the ability to distinguish between a Geographic Information System (GIS) and a data management system; (2) develop understanding of spatial data handling by conventional methods versus the automated approach; (3) promote awareness of GIS design and capabilities; (4) foster understanding of the concepts and problems of data base development and management; (5) facilitate recognition of how a computerized GIS can model conditions in the present "real world" to project conditions in the future; and (6) appreciate the utility of integrating LANDSAT and other remotely sensed data into the GIS.

Description: Since September 1991, the ERS-1 SAR (Synthetic Aperture Radar) has collected approximately 170 frames of ocean imagery on 28 passes over the western Gulf Stream in support of ESA experiment US8-2c. SAR signatures of the north wall are seen on nearly all passes, with modulation depth varying from 3% to 35% for 100 m samples. Many small and mesoscale circulation features associated with the Stream are evident. The detailed form of the signature varies considerably, however. Narrow bright or dark linear features appear to follow streamlines, and on one occasion a strong dark line was associated with an in situ measurement of a sharp current shear. Similarly, larger spatial scale changes in backscatter over the Stream were associated with in situ measurements of atmospheric stability transitions. Physical explanations for the narrow features are not so obvious. However, the accumulation of surfactants along converging current boundaries or local short wave straining and breaking appear plausible. These preliminary results strongly suggest that a wide swath (approximately 500 km) SAR with at least 100 m resolution would be a useful adjunct to existing satellite AVHRR (Advanced Very High Resolution Radiometer) imagery.

Description: ERS-1 SAR (Synthetic Aperture Radar) data were used to specify Winter physical processes on the surface of the Greenland Sea, and SSM/I (Special Sensor Microwave/Imager) data were used to characterize the regional behavior of the ice cover. Examination of the SSM/I data indicated that the convective water was likely to be confined to small (less than 100 km) domains near the ice edge. Using ERS-1 SAR data crossing the ice edge, it was possible to identify ice edge features that are very similar to modeled plumes; they have a diameter of about 100 m, a spacing of about 300 m, and cover an area about 20 by 90 km. This plume observation is the first such identification of convection. The plumes are topped by ice, and the return-water areas are open, indicating a freshened top layer of the sea and emphasizing the importance of this layer to convection.

Description: There is renewed interest in using optical remote sensing techniques for measuring and monitoring airborne toxins. Many instruments have been used to measure traces of atmospheric molecular species. Some optical remote sensing technology is in use for measuring or monitoring toxic or pollutant gases. The examples in this article provide a number of lessons that may be of use in the new field of optical remote sensing of toxic gases. Topics covered include the following: atmospheric properties, Fourier transform spectrometry, gas-filter correlation, differential absorption laser systems, aircraft missions, laser long-path instruments, differential optical absorption spectrometry, and ozone measurement.

Description: Global and regional temperature variations in the lower troposphere and lower stratosphere are examined for the period 1979-92 from Microwave Sounder Unit (MSU) data obtained by the Television Infrared Observation Satellite (TIROS)-N series of National Oceanic and Atmospheric Administration (NOAA) operational satellites. In the lower troposphere, globally-averaged temperature variations appear to be dominated by tropical El Nino (warm) and La Nina (cool) events and volcanic eruptions. The Pinatubo volcanic eruption in June 1991 appears to have initiated a cooling trend which persisted through the most recent data analyzed (July, 1992), and largely overwhelmed the warming from the 1991-92 El Nino. The cooling has been stronger in the Northern Hemisphere than in the Southern Hemisphere. The temperature trend over the 13.5 year satellite record is small (+0.03 C) compared to the year-to-year variability (0.2-0.4 C), making detection of any global warming signal fruitless to date. However, the future global warming trend, currently predicted to be around 0.3 C/decade, will be much easier to discern should it develop. The lower stratospheric temperature record is dominated by warm episodes from the Pinatubo eruption and the March 1982 eruption of El Chichon volcano.

Description: Several types of algorithms are generally used to process digital imagery such as Landsat data. The most commonly used algorithms perform the task of registration, compression, and classification. Because there are different techniques available for performing registration, compression, and classification, imagery data users need a rationale for selecting a particular approach to meet their particular needs. This collection of registration, compression, and classification algorithms was developed so that different approaches could be evaluated and the best approach for a particular application determined. Routines are included for six registration algorithms, six compression algorithms, and two classification algorithms. The package also includes routines for evaluating the effects of processing on the image data. This collection of routines should be useful to anyone using or developing image processing software. Registration of image data involves the geometrical alteration of the imagery. Registration routines available in the evaluation package include image magnification, mapping functions, partitioning, map overlay, and data interpolation. The compression of image data involves reducing the volume of data needed for a given image. Compression routines available in the package include adaptive differential pulse code modulation, two-dimensional transforms, clustering, vector reduction, and picture segmentation. Classification of image data involves analyzing the uncompressed or compressed image data to produce inventories and maps of areas of similar spectral properties within a scene. The classification routines available include a sequential linear technique and a maximum likelihood technique. The choice of the appropriate evaluation criteria is quite important in evaluating the image processing functions. The user is therefore given a choice of evaluation criteria with which to investigate the available image processing functions. All of the available evaluation criteria basically compare the observed results with the expected results. For the image reconstruction processes of registration and compression, the expected results are usually the original data or some selected characteristics of the original data. For classification processes the expected result is the ground truth of the scene. Thus, the comparison process consists of determining what changes occur in processing, where the changes occur, how much change occurs, and the amplitude of the change. The package includes evaluation routines for performing such comparisons as average uncertainty, average information transfer, chi-square statistics, multidimensional histograms, and computation of contingency matrices. This collection of routines is written in FORTRAN IV for batch execution and has been implemented on an IBM 360 computer with a central memory requirement of approximately 662K of 8 bit bytes. This collection of image processing and evaluation routines was developed in 1979.

Description: The Science and Technology Laboratory Applications Software (ELAS) was originally designed to analyze and process digital imagery data, specifically remotely-sensed scanner data. This capability includes the processing of Landsat multispectral data; aircraft-acquired scanner data; digitized topographic data; and numerous other ancillary data, such as soil types and rainfall information, that can be stored in digitized form. ELAS has the subsequent capability to geographically reference this data to dozens of standard, as well as user created projections. As an integrated image processing system, ELAS offers the user of remotely-sensed data a wide range of capabilities in the areas of land cover analysis and general purpose image analysis. ELAS is designed for flexible use and operation and includes its own FORTRAN operating subsystem and an expandable set of FORTRAN application modules. Because all of ELAS resides in one "logical" FORTRAN program, data inputs and outputs, directives, and module switching are convenient for the user. There are over 230 modules presently available to aid the user in performing a wide range of land cover analyses and manipulation. The file management modules enable the user to allocate, define, access, and specify usage for all types of files (ELAS files, subfiles, external files etc.). Various other modules convert specific types of satellite, aircraft, and vector-polygon data into files that can be used by other ELAS modules. The user also has many module options which aid in displaying image data, such as magnification/reduction of the display; true color display; and several memory functions. Additional modules allow for the building and manipulation of polygonal areas of the image data. Finally, there are modules which allow the user to select and classify the image data. An important feature of the ELAS subsystem is that its structure allows new applications modules to be easily integrated in the future. ELAS has as a standard the flexibility to process data elements exceeding 8 bits in length, including floating point (noninteger) elements and 16 or 32 bit integers. Thus it is able to analyze and process "non-standard" nonimage data. The VAX (ERL-10017) and Concurrent (ERL-10013) versions of ELAS 9.0 are written in FORTRAN and ASSEMBLER for DEC VAX series computers running VMS and Concurrent computers running MTM. The Sun (SSC-00019), Masscomp (SSC-00020), and Silicon Graphics (SSC-00021) versions of ELAS 9.0 are written in FORTRAN 77 and C-LANGUAGE for Sun4 series computers running SunOS, Masscomp computers running UNIX, and Silicon Graphics IRIS computers running IRIX. The Concurrent version requires at least 15 bit addressing and a direct memory access channel. The VAX and Concurrent versions of ELAS both require floating-point hardware, at least 1Mb of RAM, and approximately 70Mb of disk space. Both versions also require a COMTAL display device in order to display images. For the Sun, Masscomp, and Silicon Graphics versions of ELAS, the disk storage required is approximately 115Mb, and a minimum of 8Mb of RAM is required for execution. The Sun version of ELAS requires either the X-Window System Version 11 Revision 4 or Sun OpenWindows Version 2. The Masscomp version requires a GA1000 display device and the associated "gp" library. The Silicon Graphics version requires Silicon Graphics' GL library. ELAS display functions will not work with a monochrome monitor. The standard distribution medium for the VAX version (ERL~10017) is a set of two 9-track 1600 BPI magnetic tapes in DEC VAX BACKUP format. This version is also available on a TK50 tape cartridge in DEC VAX BACKUP format. The standard distribution medium for the Concurrent version (ERL-10013) is a set of two 9-track 1600 BPI magnetic tapes in Concurrent BACKUP format. The standard distribution medium for the Sun version (SSC-00019) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Masscomp version, (SSC-00020) is a .25 inch streaming magnetic tape cartridge in UNIX tar format. The standard distribution medium for the Silicon Graphics version (SSC-00021) is a .25 inch streaming magnetic IRIS tape cartridge in UNIX tar format. Version 9.0 was released in 1991. Sun4, SunOS, and Open Windows are trademarks of Sun Microsystems, Inc. MIT X Window System is licensed by Massachusetts Institute of Technology.

Description: Calibration of polarimetric radar systems is a field of research in which great progress has been made over the last few years. POLCAL (Polarimetric Radar Calibration) is a software tool intended to assist in the calibration of Synthetic Aperture Radar (SAR) systems. In particular, POLCAL calibrates Stokes matrix format data produced as the standard product by the NASA/Jet Propulsion Laboratory (JPL) airborne imaging synthetic aperture radar (AIRSAR). POLCAL was designed to be used in conjunction with data collected by the NASA/JPL AIRSAR system. AIRSAR is a multifrequency (6 cm, 24 cm, and 68 cm wavelength), fully polarimetric SAR system which produces 12 x 12 km imagery at 10 m resolution. AIRSTAR was designed as a testbed for NASA's Spaceborne Imaging Radar program. While the images produced after 1991 are thought to be calibrated (phase calibrated, cross-talk removed, channel imbalance removed, and absolutely calibrated), POLCAL can and should still be used to check the accuracy of the calibration and to correct it if necessary. Version 4.0 of POLCAL is an upgrade of POLCAL version 2.0 released to AIRSAR investigators in June, 1990. New options in version 4.0 include automatic absolute calibration of 89/90 data, distributed target analysis, calibration of nearby scenes with calibration parameters from a scene with corner reflectors, altitude or roll angle corrections, and calibration of errors introduced by known topography. Many sources of error can lead to false conclusions about the nature of scatterers on the surface. Errors in the phase relationship between polarization channels result in incorrect synthesis of polarization states. Cross-talk, caused by imperfections in the radar antenna itself, can also lead to error. POLCAL reduces cross-talk and corrects phase calibration without the use of ground calibration equipment. Removing the antenna patterns during SAR processing also forms a very important part of the calibration of SAR data. Errors in the processing altitude or in the aircraft roll angle are possible causes of error in computing the antenna patterns inside the processor. POLCAL uses an altitude error correction algorithm to correctly remove the antenna pattern from the SAR images. POLCAL also uses a topographic calibration algorithm to reduce calibration errors resulting from ground topography. By utilizing the backscatter measurements from either the corner reflectors or a well-known distributed target, POLCAL can correct the residual amplitude offsets in the various polarization channels and correct for the absolute gain of the radar system. POLCAL also gives the user the option of calibrating a scene using the calibration data from a nearby site. This allows precise calibration of all the scenes acquired on a flight line where corner reflectors were present. Construction and positioning of corner reflectors is covered extensively in the program documentation. In an effort to keep the POLCAL code as transportable as possible, the authors eliminated all interactions with a graphics display system. For this reason, it is assumed that users will have their own software for doing the following: (1) synthesize an image using HH or VV polarization, (2) display the synthesized image on any display device, and (3) read the pixel locations of the corner reflectors from the image. The only inputs used by the software (in addition to the input Stokes matrix data file) is a small data file with the corner reflector information. POLCAL is written in FORTRAN 77 for use on Sun series computers running SunOS and DEC VAX computers running VMS. It requires 4Mb of RAM under SunOS and 3.7Mb of RAM under VMS for execution. The standard distribution medium for POLCAL is a .25 inch streaming magnetic tape cartridge in UNIX tar format. It is also available on a 9-track 1600 BPI magnetic tape in DEC VAX FILES-11 format or on a TK50 tape cartridge in DEC VAX FILES-11 format. Other distribution media may be available upon request. Documentation is included in the price of the program. POLCAL 4.0 was released in 1992 and is a copyrighted work with all copyright vested in NASA.

Description: The spectral and spatial requirements for remote sensing in the next decade are presented. The requirements presented were obtained through extensive literature research and discussions with leading members of the various remote sensing research communities. In the 0.35-2.5 micron region of the spectrum, numerous bands will be needed at bandwidths as narrow as 10-20 nanometers. There is also growing interest in the thermal infrared (8-14 microns). Spatial resolution (instantaneous field of view) of 5 to 10 meters will be of great benefit to many fields of remote sensing.

Description: The presence of positive serial correlation (autocorrelation) in remotely sensed data results in an underestimate of the variance-covariance matrix when calculated using contiguous pixels. This underestimate produces an inflation in F statistics. For a set of Thematic Mapper Simulator data (TMS), used to test the ability to discriminate a known geobotanical anomaly from its background, the inflation in F statistics related to serial correlation is between 7 and 70 times. This means that significance tests of means of the spectral bands initially appear to suggest that the anomalous site is very different in spectral reflectance and emittance from its background sites. However, this difference often disappears and is always dramatically reduced when compared to frequency distributions of test statistics produced by the comparison of simulated training sets possessing equal means, but which are composed of autocorrelated observations. Previously announced in STAR as N82-25602

Description: A complete automatic unsupervised classification approach has been developed to estimate the proportion of corn, soybeans, and other crops in a Landsat 5-by-6-nanometer segment. The technique involves extracting crop growth variables that are predictable from agromet models, it provides a signature extension not possible before. The technique has been applied in 3 years (1978-1980) for 56 segments and shows neither a year-to-year effect nor any geographic effect. The results to date are considered far better than those obtainable from any other currently available technique. Nontheless, the technique can be improved to reduce the bias.

Description: Since NASA's program of research concerning remote sensing was initiated in the 1960s, one of its major objectives has been to advance the state-of-the-art in machine processing of satellite acquired multispectral data. Possibilities have been studied regarding a use of these data to identify type, to monitor condition, and to estimate the ontogenetic stage of cultural vegetation. The present investigation provides a review of the state-of-the-art of the technology used to make remote sensing crop production estimates in foreign regions. Attention is given to Landsat data acquisition, aspects of registration and preprocessing, questions of data transformation, data modeling, proportion estimation, labeling, development stage models, crop condition models, and an outlook regarding future developments.

Description: Automated information extraction procedures for analysis of multitemporal Landsat data in non-U.S. crop inventory and monitoring are reviewed. Experiments to develop and evaluate crop area estimation technologies for spring small grains, summer crops, corn, and soybeans are discussed. Previously announced in STAR as N82-32793

Description: Agriculture, which occupies a vital position in the economy of the State of California, depends crucially on the available water. The California Department of Water Resources (DWR) is, therefore, greatly concerned with the total water requirements for agricultural applications. In view of the limitations of an area-limited, single-date survey system, the DWR has been cooperating with NASA and the University of California in a study of the applicability of Landsat imagery and digital data as an aid in making decisions concerning the management of water resources. Attention is given to a statewide inventory of irrigated land, computer-assisted estimation and mapping of irrigated land, and a crop type analysis using Landsat digital data.

Description: The California Integrated Remote Sensing System's San Bernardino County Project was devised to study the utilization of a data base at a number of jurisdictional levels. The present paper discusses the implementation of change-detection and masking techniques in the updating of Landsat-derived land-cover maps. A baseline landcover classification was first created from a 1976 image, then the adjusted 1976 image was compared with a 1979 scene by the techniques of (1) multidate image classification, (2) difference image-distribution tails thresholding, (3) difference image classification, and (4) multi-dimensional chi-square analysis of a difference image. The union of the results of methods 1, 3 and 4 was used to create a mask of possible change areas between 1976 and 1979, which served to limit analysis of the update image and reduce comparison errors in unchanged areas. The techniques of spatial smoothing of change-detection products, and of combining results of difference change-detection algorithms are also shown to improve Landsat change-detection accuracies.

Description: A technique is examined for improving the comparability of Landsat multisppectral scanner (MSS) data acquired on different dates. The technique involves conversion of digital brightness counts to relative radiance values measured in energy units (milliwatts per square centimeter-steradian). The statistical data of signature from 23 land cover (or biomass) classifications derived from all three Landsats were compared before and after the radiance normalization. Significant convergence occurred among the data sets for mean spectral values and the variances associated with each of seven major land cover types for MSS bands 4, 5, and 7. Overall, the variance attributed to the sensor component was reduced from 5.39 to 2.69 percent, with the largest decrease occurring in band 4 (14.4 percent to 3.7 percent).

Description: Remote terrestrial sensing (RTS) data is constantly being collected from a variety of space-based and earth-based sensors. The collected data, and especially 'value-added' analyses of the data, are finding growing application for commercial, government, and scientific purposes. The scale of this data collection and analysis is truly enormous; e.g., by 1995, the amount of data available in just one sector, NASA space science, will reach 5 petabytes. Moreover, the amount of data, and the value of analyzing the data, are expected to increase dramatically as new satellites and sensors become available (e.g., NASA's Earth Observing System satellites). Lockheed and other companies are beginning to provide data and analysis commercially. A critical issue for the exploitation of collected data is the dissemination of data and value-added analyses to a diverse and widely distributed customer base. Customers must be able to use their computational environment (eventually the National Information Infrastructure) to obtain timely and complete information, without having to know the details of where the relevant data resides and how it is accessed. Customers must be able to routinely use standard, widely available (and, therefore, low cost) analyses, while also being able to readily create on demand highly customized analyses to make crucial decisions. The diversity of user needs creates a difficult software problem: how can users easily state their needs, while the computational environment assumes the responsibility of finding (or creating) relevant information, and then delivering the results in a form that users understand? A software agent is a self-contained, active software module that contains an explicit representation of its operational knowledge. This explicit representation allows agents to examine their own capabilities in order to modify their goals to meet changing needs and to take advantage of dynamic opportunities. In addition, the explicit representation allows agents to advertize their capabilities and results to other agents, thereby allowing the collection of agents to reuse each others work.

Description: Weather forecasting has been called the second oldest profession. To do so accurately and with some consistency requires an ability to understand the processes which create the clouds, drive the winds, and produce the ever changing atmospheric conditions. Measurement of basic parameters such as temperature, water vapor content, pressure, windspeed and wind direction throughout the three dimensional atmosphere form the foundation upon which a modern forecast is created. Doppler radar, and space borne remote sensing have provided forecasters the new tools with which to ply their trade.

Description: The problem of estimating the parameters which determine a mixture density is reviewed as well as maximum likelihood estimation for it. A particular iterative procedure for numerically approximating maximum likelihood estimates for mixture density problems is considered. This EM algorithm, is a specialization to the mixture density context of a general algorithm of the same name used to approximate maximum likelihood estimates for incomplete data problems. The formulation and theoretical and practical properties of the EM algorithm for mixture densities are discussed focussing in particular on mixtures of densities from exponential families.

Description: An important question in cluster analysis and pattern recognition is the determination of the number of clusters into which a given population should be divided. Frequently, particularly when certain specific clustering methods are being used, the number of clusters is taken to be equal to the number of modes, or local maxima, in the probability density function underlying the given data set. The use of kernal density estimates in mode estimation is discussed. The test statistic to be used is defined and a bootstrap technique for assessing significance is given. An illustrative application is followed by an examination of the asymptotic behavior of the test statistic.

Description: Experience gained in applying nonparametric maximum likelihood techniques of density estimation to judge the comparative quality of various estimators is reported. Two invariate data sets of one hundered samples (one Cauchy, one natural normal) are considered as well as studies in the multivariate case.

Description: The problem of estimating a density f on R sup d from a sample Xz(1),...,X(n) of independent identically distributed random vectors is critically examined, and some recent results in the field are reviewed. The following statements are qualified: (1) For any sequence of density estimates f(n), any arbitrary slow rate of convergence to 0 is possible for E(integral/f(n)-fl); (2) In theoretical comparisons of density estimates, integral/f(n)-f/ should be used and not integral/f(n)-f/sup p, p 1; and (3) For most reasonable nonparametric density estimates, either there is convergence of integral/f(n)-f/ (and then the convergence is in the strongest possible sense for all f), or there is no convergence (even in the weakest possible sense for a single f). There is no intermediate situation.

Description: A method of determining three-dimensional motion and structure from two image frames is presented. The method requires eight point correspondences between the two frames, from which motion and structure parameters are determined by solving a set of eight linear equations and a singular value decomposition of a 3x3 matrix. It is shown that the solution thus obtained is unique.

Description: Methods for the segmentation and recognition of individual targets sensed with forward looking infrared detectors are discussed. Particular attention is given to an adaptive multi-scenario target screener.

Description: The structural analysis of remotely sensed imagery is defined and basic techniques for implementing the process are described. Structural analysis uses knowledge of the properties of an entity, its parts and their relationships, and the relationships in which it participates at a higher level to locate and recognize objects in a visual scene. The representation of structural knowledge, the development of algorithms for using the knowledge to help analyze an image, and techniques for storage and retrieval of relational models are addressed.

Description: Computer-based techniques for automatic photointerpretation based upon information derived from texture and morphology analysis of images are discussed. By automatic photointerpretation, is meant the determination of semantic descriptions of the content of the images by computer. To perform semantic analysis of morphology, a heirarchical structure of knowledge representation was developed. The simplest elements in a morphology are strokes, which are used to form alphabets. The alphabets are the elements for generating words, which are used to describe the function or property of an object or a region. The words are the elements for constructing sentences, which are used for semantic description of the content of the image. Photointerpretation based upon morphology is then augmented by textural information. Textural analysis is performed using a pixel-vector approach.

Description: Methods used to measure the geometrical properties of regions in a segmented image are discussed including the use of centroids, moments, and principle axes. In addition, statistical picture properties, particularly those which describe visual texture, are discussed. Gray level statistics, local property statistics, and autocorrelation and power spectrum are addressed.

Description: Research into the role of cooperative, or relaxation, processes in image segmentation is surveyed. Cooperative processes can be employed at several levels of the segmentation process as a preprocessing enhancement step, during supervised or unsupervised pixel classification and, finally, for the interpretation of image segments based on segment properties and relations.

Description: The methodologies and capabilities of image segmentation techniques are reviewed. Single linkage schemes, hybrid linkage schemes, centroid linkage schemes, histogram mode seeking, spatial clustering, and split and merge schemes are addressed.

Description: Given N distinct points (X sub i, Y sub i) and N real numbers Z sub i, BSPLASH constructs a function G (x, y) that satisfies G (x sub i, y sub i) = Z sub i for i = 1,..., N. This C(2) interpolant consists of a bicubic spline approximation and Shepard's bivariate interpolant.

Description: The physical and geometric interpretation of a surface fitting technique, multiquadric equations (MQ), is discussed. The relation of this method and its reciprocal form to biharmonic and harmonic techniques respectively, is pointed out. In both forms the solutions may be viewed as being numerical approximations of an integral equation in which an unknown density function is the physical source for disturbing potential (reciprocal-MQ) or elastic displacement (MQ).

Description: An algorithm is described for constructing a smooth computable function, f, defined over the surface of a sphere and interpolating a set of n data values, u sub i, associated with n locations, P sub i, on the surface of the sphere. The interpolation function, f, will be continuous and have continuous first partial derivatives. The locations, p sub i, are not required to lie on any type of regular grid.

Description: A variety of numerical methods for fitting a function to data given at a set of points scattered throughout a domain in the plane are surveyed. Four classes of methods are discussed: (1) global interpolation; (2) local interpolation; (3) global approximation; and (4) local approximation. Also, two-stage methods and contouring are discussed. The surfaces constructed include polynomials, spline functions, and rational functions, among others.

Description: Some mathematical/statistical problems within the AgRISTARS program amendable to investigations involving the use of surface fitting techniques are overviewed. The Bayes and maximum likelihood rules, bias determination, regression estimators, parameter estimation, and classifier design are addressed.

Description: Image processing and enhancement techniques for improving the geologic utility of digital satellite radar images are reviewed. Preprocessing techniques such as mean and variance correction on a range or azimuth line by line basis to provide uniformly illuminated swaths, median value filtering for four-look imagery to eliminate speckle, and geometric rectification using a priori elevation data. Examples are presented of application of preprocessing methods to Seasat and Landsat data, and Seasat SAR imagery was coregistered with Landsat imagery to form composite scenes. A polynomial was developed to distort the radar picture to fit the Landsat image of a 90 x 90 km sq grid, using Landsat color ratios with Seasat intensities. Subsequent linear discrimination analysis was employed to discriminate rock types from known areas. Seasat additions to the Landsat data improved rock identification by 7%.

Description: An examination of the possibilities of using Landsat data to simulate NOAA-6 Advanced Very High Resolution Radiometer (AVHRR) data on two channels, as well as using actual NOAA-6 imagery, for large-scale hydrological studies is presented. A running average was obtained of 18 consecutive pixels of 1 km resolution taken by the Landsat scanners were scaled up to 8-bit data and investigated for different gray levels. AVHRR data comprising five channels of 10-bit, band-interleaved information covering 10 deg latitude were analyzed and a suitable pixel grid was chosen for comparison with the Landsat data in a supervised classification format, an unsupervised mode, and with ground truth. Landcover delineation was explored by removing snow, water, and cloud features from the cluster analysis, and resulted in less than 10% difference. Low resolution large-scale data was determined useful for characterizing some landcover features if weekly and/or monthly updates are maintained.

Description: (Previously announced in STAR as N81-19529)

Description: Problems associated with the use of Landsat multispectral scanner (MSS) imagery for the detection of urban growth and land use patterns are discussed. The presence of vegetation, either original or added between scanning periods, has been found to dramatically effect the range of signatures in a given area. Different land use developmental stages have been successfully identified by means of 1:50,000 scale panchromatic aerial photography, a resolution only considered possible by spaceborne instrumentation with the advent of the Landsat D satellite. Textural information generated through the grey-tone spatial-dependency matrix for the Landsat band 5 data is compared for different years and a change detection algorithm is described. It is found that the addition of vegetation during development after the removal of natural vegetation resulted in error of omission in the single band data, which must therefore only be used in concert with other data sources.

Description: Procedures necessary for the development of a generalized three-dimensional perspective software capability in support of graphic, topographic, and color mapping of Landsat data are reviewed. The NASA Earth Resources Laboratory developed the procedures in order to facilitate the processing and analysis of disparate, geographically oriented base maps from aircraft and satellite sensors. Perspective displays are obtained through a translation of the space-viewed object to a vantage point coordinate system, followed by a rotation through two angles for alignment along the vantage line of sight, and finally a perspective transformation to yield two-dimensional displays with no hidden lines. Matrix equations for the transformations are reviewed, including scaling, and block diagrams are provided of the data and perspective software systems. The classification data plane may be mapped onto a topographic elevation data plane.

Description: A modified Kubelka-Munk model has been utilized to derive useful equations for the analysis of apparent canopy reflectance. Based on the solution to the model simple working equations were formulated by employing reflectance characteristic parameters. The relationships derived show the asymptotic nature of reflectance data that is typically observed in remote sensing studies of plant biomass. They also establish the range of expected apparent canopy reflectance values for specific plant canopy types. The usefulness of the simplified equations was demonstrated by the exceptionally close fit of the theoretical curves to two separately acquired data sets for alfalfa and shortgrass prairie canopies.

Description: The following working objectives were adopted: (1) define the current state of knowledge concerning the role of multispectral imaging science in hydrology; (2) identify critical areas where gaps in our knowledge limit opportunities for significant improvements in our understanding of the hydrologic processes; (3) evaluate the potential of multispectral imaging sciences as tools to close these gaps in knowledge; and (4) develop guidelines for a series of remote-sensing-based experiments that would help close these gaps in knowledge and, thereby, provide man with the improved scientific base necessary for better utilization of the world's water resource. The resulting documentation is intended to provide guidance for multispectral imaging programs in the hydrologic sciences with special emphasis on the visible and infrared (IR) wavelengths.

Description: Specific activity in information extraction science (taken to include data handling) is needed to: help identify the bounds of practical missions; identify potential data handling and analysis scenarios; identify the required enabling technology; and identify the requirements for a design data base to be used by the disciplines in determining potential parameters for future missions. It was defined that specific analysis topics were a function of the discipline involved, and therefore no attempt was made to define any specific analysis developments required. Rather, it was recognized that a number of generic data handling requirements exist whose solutions cannot be typically supported by the disciplines. The areas of concern were therefore defined as: data handling aspects of system design considerations; enabling technology for data handling, with specific attention to rectification and registration; and enabling technology for analysis. Within each of these areas, the following topics were addressed: state of the art (current status and contributing factors); critical issues; and recommendations for research and/or development.

Description: The use of multispectral imaging systems in land use, geomorphological, and cartographic applications is examined. Spatial, spectral, and geometric resolution requirements for photo interpretation and multispectral pattern recognition are discussed. The potential contributions of these systems in specific experiments is also included.

Description: The role that TM and MSS data play in the analysis of spatial patterns for land use/land cover, geomorphology studies, and the development of cartographic products is discussed. Tables listing geographic science data gaps, mission data requirements, and possible future remote sensing missions are included.