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At least 127 records · Page 7

Key Issues in the Analysis of Remote Sensing Data: A report on the workshop

The procedures of a workshop assessing the state of the art of machine analysis of remotely sensed data are summarized. Areas discussed were: data bases, image registration, image preprocessing operations, map oriented considerations, advanced digital systems, artificial intelligence methods, image classification, and improved classifier training. Recommendations of areas for further research are presented.

Swain, P. H.↗

Application of scanning microdensitometer data in selected plant science case studies

This paper treats a representative sample of projects aimed at vegetation mapping and assessment via analysis of both digital photographic and Landsat data projects and illustrates the potential for using scanning microdensitometric data extracted from color infrared photographs in the following applications: freshwater wetlands mapping, tree type mapping, and yield vs. reflectance modeling in corn fertilization experiments. These case studies are presented to illustrate the general applicability of scanning microdensitometer data in the contexts of image classification and enhancement as well as quantitative modeling of ground parameters.

Lillesand, T. M.↗

Analysis of the Tanana River Basin using LANDSAT data

Digital image classification techniques were used to classify land cover/resource information in the Tanana River Basin of Alaska. Portions of four scenes of LANDSAT digital data were analyzed using computer systems at Ames Research Center in an unsupervised approach to derive cluster statistics. The spectral classes were identified using the IDIMS display and color infrared photography. Classification errors were corrected using stratification procedures. The classification scheme resulted in the following eleven categories; sedimented/shallow water, clear/deep water, coniferous forest, mixed forest, deciduous forest, shrub and grass, bog, alpine tundra, barrens, snow and ice, and cultural features. Color coded maps and acreage summaries of the major land cover categories were generated for selected USGS quadrangles (1:250,000) which lie within the drainage basin. The project was completed within six months.

Morrissey, L. A.↗

Feature Identification and Location Experiment

The Feature Identification and Location Experiment (FILE), which was flown on the second Space Shuttle flight to test a technique for real-time, autonomous classification of water, vegetation and bare land as well as clouds, snow and ice, senses earth radiation in spectral bands centered at 0.65 and 0.85 microns. The radiance ratio classification algorithm has successfully made automatic data selection decisions. A classification image obtained on the mission is providing data needed to evaluate the FILE algorithm and overall system performance.

Sivertson, W. E., Jr.↗

Impact of LANDSAT MSS Sensor Differences on Change Detection Analysis

Change detection techniques were used to pinpoint differences in the multispectral band scanners on LANDSAT 2, 3, and 4 satellites. The method of analysis was to co-register 512 by 512 pixel subwindows for all data pairs followed by scattergram generation and analysis. In all cases, the LANDSAT-4 data were used as the base to which other images were registered. There appear to be no major problems preventing use of LANDSAT-4 MSS with previous MSS sensors for charge detection, provided the interference noise can be removed or minimized. This noise may result in detection of spurious changes, as well as affect other uses of the data, including image classification. Analysis of dark (water and forests), rather than light features will be most impacted because the noise will form a higher percentage of the total response at low DN values. Any data normalizations for change detection should be based upon the data, rather than solely upon calibration information. While the observed relative radiometric transfer function between LANDSAT 3 and 4 was approximately as predicted, there were still significant deviations. Normalizing based upon data content also can have the advantage of allowing simultaneous normalization of the atmosphere as well as the radiometry.

Likens, W. C.↗

Monsoon flood boundary delineation and damage assessment using space borne imaging radar and Landsat data

Space-borne synthetic aperture radar (SAR) data acquired by the Shuttle Imaging Radar-B (SIR-B) Program and Landsat Multispectral Scanner Subsystem (MSS) Data from Landsat 4 were used to map flood boundaries for the assessment of flood damage in the Peoples Republic of Bangladesh. The cloud penetrating capabilities of the L-band radar provided a clear picture of the hydrologic conditions of the surface during a period of inclement weather at the end of the wet phase of the 1984 monsoon. The radar image data were digitally processed to geometrically rectify the pixel geometry and were filtered to subdue radar image speckle effects. Contrast enhancement techniques and density slicing were used to create discrete land-cover categories corresponding to surface conditions present at the time of the Shuttle overflight. The radar image classification map was digitally registered to a spectral signature classification map of the area derived from Landsat MSS data collected two weeks prior to the SIR-B mission. Classification accuracy comparisons were made between the radar and MSS classification maps, and flood boundary and flood damage assessment measurements were made with the merged data by adding the classifications and inventorying the land-cover classes inundated at the time of flooding.

Imhoff, Marc L.↗

General-Purpose Image-Data Program

Image Database computer program, IBASE, is general-purpose imagery-information system. Use accomplished either by commands or through hierarchy of menus. Analytical capabilities of IBASE include contigency tables, image filtering (low-, high-, and band-pass), proximity maps, clustering, histograms, regression, slope calculations, scaling, and Boolean manipulations. Also has interface to Cheshire Image Classification expert system. Written in FORTRAN 77.

Engle, Steven W.↗

The power of neural nets

Implementation of the Hopfield net which is used in the image processing type of applications where only partial information about the image may be available is discussed. The image classification type of algorithm of Hopfield and other learning algorithms, such as the Boltzmann machine and the back-propagation training algorithm, have many vital applications in space.

Ryan, J. P.↗

Nature and origin of mineral coatings on volcanic rocks of the Black Mountain, Stonewall Mountain, and Kane Springs Wash volcanic centers, Southern Nevada

Comparative lab spectra and Thematic Mapper imagery investigations at 3 Tertiary calderas in southern Nevada indicate that desert varnish is absorbant relative to underlying host rocks below about 0.7 to 1.3 microns, depending on mafic affinity of the sample, but less absorbant than mafic host rocks at higher wavelengths. Desert varnish occurs chiefly as thin impregnating films. Distribution of significant varnish accumulations is sparse and localized, occurring chiefly in surface recesses. These relationships result in the longer wavelength bands and high 5/2 values over felsic units with extensive desert varnish coatings. These lithologic, petrochemical, and desert varnish controlled spectral responses lead to characteristic TM band relationships which tend to correlate with conventionally mappable geologic formations. The concept of a Rock-Varnish Index (RVI) is introduced to help distinguish rocks with a potentially detectable varnish. Felsic rocks have a high RVI, and those with extensive desert varnish behave differently, spectrally, from those without extensive varnish. The spectrally distinctive volcanic formations at Stonewall Mountain provide excellent statistical class segregation on supervised classification images. A binary decision rule flow-diagram is presented to aid TM imagery analysis over volcanic terrane in semi-arid environments.

Taranik, James V.↗

Automated site characterization for robotic sample acquisition systems

A mobile, semi-autonomous vehicle with multiple sensors and on-board intelligence is proposed for performing preliminary scientific investigations on extraterrestrial bodies prior to human exploration. Two technologies, a hybrid optical-digital computer system based on optical correlator technology and an image and instrument data analysis system, provide complementary capabilities which might be part of an instrument package for an intelligent robotic vehicle. The hybrid digital-optical vision system could perform real-time image classification tasks using an optical correlator with programmable matched filters under control of a digital microcomputer. The data analysis system would analyze visible and multiband imagery to extract mineral composition and textural information for geologic characterization. Together these technologies would support the site characterization needs of a robotic vehicle for both navigational and scientific purposes.

Scholl, Marija S.↗

Mission operations technology

Developments in the area of spacecraft operations are examined that can be utilized in mission and spacecraft designs to enhance the efficiency of planetary and other mission operations. The technology enhancements described address four major systems: the spacecraft, the tracking and data system, the spaceflight operations center, and the flight projects. Specific technological advances are detailed in the areas of telemetry monitoring and fault analysis, scheduling systems, and scientific data analysis. The Spacecraft Health Automated Reasoning Prototype and the Engineering Analysis Subsystem Environment can provide real-time monitoring and analysis with limited workforce resources. The Multimission Automation for Real-time Verification of Spacecraft Engineering Link, the Operation Mission Planner, and the Sky Image Classification and Archiving Tool are other examples of systems developed by NASA that enhance operations technology by reducing the need for human input.

Varsi, Giulio↗

Remote sensing of Earth terrain

Research findings are summarized for projects dealing with the following: application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated Mie scatterers with size distribution and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; theoretical modeling for passive microwave remote sensing of earth terrain; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

Kong, J. A.↗

Mapping sub-tropical vegetation using multi-frequency, multi-polarization SAR data

In 1990 the NASA/JPL airborne synthetic aperture radar DC-8 (Airsar) was flown over an area in northern Belize and the surrounding countries of Guatemala and Mexico. The three-frequency polarimetric radar signatures of a variety of natural areas have been extracted, and many have a unique radar signature. Scattering mechanisms which may explain these signatures and results of an image classification technique are presented.

Freeman, A.↗

Remote sensing of Earth terrain

Progress report on remote sensing of Earth terrain covering the period from Jan. to June 1993 is presented. Areas of research include: radiative transfer model for active and passive remote sensing of vegetation canopy; polarimetric thermal emission from rough ocean surfaces; polarimetric passive remote sensing of ocean wind vectors; polarimetric thermal emission from periodic water surfaces; layer model with tandom spheriodal scatterers for remote sensing of vegetation canopy; application of theoretical models to active and passive remote sensing of saline ice; radiative transfer theory for polarimetric remote sensing of pine forest; scattering of electromagnetic waves from a dense medium consisting of correlated mie scatterers with size distributions and applications to dry snow; variance of phase fluctuations of waves propagating through a random medium; polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory; branching model for vegetation; polarimetric passive remote sensing of periodic surfaces; composite volume and surface scattering model; and radar image classification.

Kong, J. A.↗

Multi-Scale Fractal Analysis of Image Texture and Pattern

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images of the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimensional-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

Emerson, Charles W.↗

Multi-Scale Fractal Analysis of Image Texture and Pattern

Analyses of the fractal dimension of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed (10 to 80 meters). A similar analysis of Landsat Thematic Mapper images of the East Humboldt Range in Nevada taken four months apart show a more complex relation between pixel size and fractal dimension. The major visible difference between the spring and late summer NDVI images is the absence of high elevation snow cover in the summer image. This change significantly alters the relation between fractal dimension and pixel size. The slope of the fractal dimension-resolution relation provides indications of how image classification or feature identification will be affected by changes in sensor spatial resolution.

Emerson, Charles W.↗

Teaching Soil Science in Primary and Secondary Schools

Earth's thin layer of soil is a fragile resource, made up of minerals, organic materials, air, water, and billions of living organisms. Soils plays a variety of critical roles that sustain life on Earth. If we think about soil, we tend to see it first as the source of most of the food we eat and the fibers we use, such as wood and cotton. Few students realize that soils also provide the key ingredients to many of the medicines (including antibiotics), cosmetics, and dyes that we use. Fewer still understand the importance of soils in integrating, controlling, and regulating the movement of air, water, materials, and energy between the hydrosphere, lithosphere, atmosphere, and biosphere. Because soil sustains life, it offers both a context and a natural laboratory for investigating these interactions. The enclosed poster, which integrates soil profiles with typical landscapes in which soils form, can also help students explore the interrelationships of Earth systems and gain an understanding of our soil resources. The poster, produced jointly by the American Geological Institute and the Soil Science Society of America, aims to increase awareness of the importance of soil, as does the GLOBE (Global Learning and Observations To Benefit the Environment) Program. Vice President Al Gore instituted the GLOBE Program on Earth Day of 1993 to increase environmental awareness of individuals throughout the world, contribute to a better scientific understanding of the Earth, and help all students reach higher levels of achievement in science and mathematics. GLOBE functions as a partnership between scientists, students, and teachers in which scientists design protocols for specific measurements they need for their research that can be performed by K-12 students. Teachers are trained in the GLOBE protocols and teach them to their students. Students make the measurements, enter data via the Internet to a central data archive, and the data becomes available to scientists and the general community. Students benefit by having a "hands-on"experience in science, math, and technology, using their local environment as a learning laboratory, as well as contact with scientists and other students around the world. Soil investigations have become an essential component of GLOBE. The protocols that have been developed so far within the GLOBE program include GPS Location, Atmosphere/Climate, Soil Characterization, Soil Moisture and Temperature, Land Cover/Biometry, Hydrology, and Satellite Image Classification. For the GLOBE Soil Characterization Protocol, students explore the physical. chemical, and morphological properties of the soil at their study site. They are asked to dig a pit or use an auger to about 1 meter at at least 2 sites.

Levine, Elissa R.↗

Multi-Scale Fractal Analysis of Image Texture and Pattern

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely scale-independent. Self-similarity is a property of curves or surfaces where each part is indistinguishable from the whole. The fractal dimension D of remote sensing data yields quantitative insight on the spatial complexity and information content contained within these data. Analyses of Normalized Difference Vegetation Index (NDVI) images of homogeneous land covers near Huntsville, Alabama revealed that the fractal dimension of an image of an agricultural land cover indicates greater complexity as pixel size increases, a forested land cover gradually grows smoother, and an urban image remains roughly self-similar over the range of pixel sizes analyzed(l0 to 80 meters). The forested scene behaves as one would expect-larger pixel sizes decrease the complexity of the image as individual clumps of trees are averaged into larger blocks. The increased complexity of the agricultural image with increasing pixel size results from the loss of homogeneous groups of pixels in the large fields to mixed pixels composed of varying combinations of NDVI values that correspond to roads and vegetation. The same process occur's in the urban image to some extent, but the lack of large, homogeneous areas in the high resolution NDVI image means the initially high D value is maintained as pixel size increases. The slope of the fractal dimension-resolution relationship provides indications of how image classification or feature identification will be affected by changes in sensor resolution.

Emerson, Charles W.↗