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Results for “co-occurrence”

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NASA NTRS1988

Cloud field classification based upon high spatial resolution textural features. I - Gray level co-occurrence matrix approach

Stratocumulus, cumulus, and cirrus clouds were identified on the basis of cloud textural features which were derived from a single high-resolution Landsat MSS NIR channel using a stepwise linear discriminant analysis. It is shown that, using this method, it is possible to distinguish high cirrus clouds from low clouds with high accuracy on the basis of spatial brightness patterns. The largest probability of misclassification is associated with confusion between the stratocumulus breakup regions and the fair-weather cumulus.

Welch, R. M.↗

NASA NTRS1983

Texture functions in image analysis: A computationally efficient solution

A computationally efficient means for calculating texture measurements from digital images by use of the co-occurrence technique is presented. The calculation of the statistical descriptors of image texture and a solution that circumvents the need for calculating and storing a co-occurrence matrix are discussed. The results show that existing efficient algorithms for calculating sums, sums of squares, and cross products can be used to compute complex co-occurrence relationships directly from the digital image input.

Cox, S. C.↗

NASA NTRS1974

Spectral and textural processing of ERTS imagery

A procedure is developed to simultaneously extract textural features from all bands of ERTS multispectral scanner imagery for automatic analysis. Multi-images lead to excessively large grey tone N-tuple co-occurrence matrices; therefore, neighboring grey N-tuple differences are measured and an ellipsoidally symmetric functional form is assumed for the co-occurrence distribution of multiimage greytone N-tuple differences. On the basis of past data the ellipsoidally symmetric approximation is shown to be reasonable. Initial evaluation of the procedure is encouraging.

Haralick, R. M.↗

NASA NTRS1974

Use of feature extraction techniques for the texture and context information in ERTS imagery: Spectral and textural processing of ERTS imagery

The author has identified the following significant results. A procedure was developed to extract cross-band textural features from ERTS MSS imagery. Evolving from a single image texture extraction procedure which uses spatial dependence matrices to measure relative co-occurrence of nearest neighbor grey tones, the cross-band texture procedure uses the distribution of neighboring grey tone N-tuple differences to measure the spatial interrelationships, or co-occurrences, of the grey tone N-tuples present in a texture pattern. In both procedures, texture is characterized in such a way as to be invariant under linear grey tone transformations. However, the cross-band procedure complements the single image procedure by extracting texture information and spectral information contained in ERTS multi-images. Classification experiments show that when used alone, without spectral processing, the cross-band texture procedure extracts more information than the single image texture analysis. Results show an improvement in average correct classification from 86.2% to 88.8% for ERTS image no. 1021-16333 with the cross-band texture procedure. However, when used together with spectral features, the single image texture plus spectral features perform better than the cross-band texture plus spectral features, with an average correct classification of 93.8% and 91.6%, respectively.

Haralick, R. H.↗

NASA NTRS1977

Quantitative comparison of combined gas chromatographic/mass spectrometric profiles of complex mixtures

The paper describes a method called HISLIB for automatic quantitative comparison of gas chromatographic/mass spectrometric (GC/MS) results obtained on complex mixtures of organic compounds. The method is based on comparing new mixtures to 'historical' libraries of previous results. Co-occurrence of components is determined by matching relative retention indices (RRIs) and mass spectra after background removal and resolution of overlapping GC components. Internal standards are used to quantify the relative concentrations of components. Applications of HISLIB include validation of analytical procedures to isolate complex mixtures; development of historical libraries which might include complete summaries of all past observations, compilations of controls, or any other selected subset of results; improvement of the quality of existing libraries of mass spectral data; and detection of differences in kind and/or amounts of individual components. Limitations of the method are mentioned along with causes of their occurrence.

Smith, D. H.↗

NASA NTRS1982

The use of large-scale aerial photography for interpreting Landsat digital data in an elk habitat-analysis project

Large-scale aerial photography was used to interpret Landsat multispectral scanner data processed through an unsupervised classifier. After scale adjustment and interpretation by application of an elk-habitat photointerpretation legend, the photographs were registered with the spectral classification, and the co-occurrence of spectral picture elements with photointerpreted habitat classes was tabulated. Analysis of the resulting table of data permitted the description of spectral classes in terms meaningful and useful to elk research and management unit in the Blue Mountains of northeastern Oregon.

Isaacson, D. L.↗

NASA NTRS1983

The influence of sensor and flight parameters on texture in radar images

Texture is known to be important in the analysis of radar images for geologic applications. It has previously been shown that texture features derived from the grey level co-occurrence matrix (GLCM) can be used to separate large scale texture in radar images. Here the influence of sensor parameters, specifically the spatial and radiometric resolution and flight parameters, i.e., the orientation of the surface structure relative to the sensor, on the ability to classify texture based on the GLCM features is investigated. It was found that changing these sensor and flight parameters greatly affects the usefulness of the GLCM for classifying texture on radar images.

Frost, V. S.↗

NASA NTRS1983

The Influence of Sensor and Flight Parameters on Texture in Radar Images

Texture is known to be important in the analysis of radar images for geologic applications. It was previously shown that texture features derived from the grey-level co-occurrence matrix (GLCM) can be used to separate large scale texture in radar images. The influence of sensor parameters, specifically the spatial and radiometric resolution and flight parameters, i.e., the orientation of the surface structure relative to the sensor, on the ability to classify texture based on the GLCM features is investigated. It was found that changing these sensor and flight parameters greatly affects the usefulness of the GLCM for classifying texture on radar images.

Frost, V. S.↗

NASA NTRS1984

The influence of sensor and flight parameters on texture in radar images

Frost, V. S.↗

NASA NTRS1985

Sulfur transformations at the hydrogen sulfide/oxygen interface in stratified waters and in cyanobacterial mats

Stratified water bodies allow the development of several microbial plates along the water column. The microbial plates develop in relation to nutrient availability, light penetration, and the distribution of oxygen and sulfide. Sulfide is initially produced in the sediment by sulfate-reducing bacteria. It diffuses along the water column creating a zone of hydrogen sulfide/oxygen interface. In the chemocline of Solar Lake oxygen and sulfide coexist in a 0 to 10 cm layer that moves up and down during a diurnal cycle. The microbial plate at the chemocline is exposed to oxygen and hydrogen sulfide, alternating on a diurnal basis. The cyanobacteria occupying the interface switch from anoxygenic photosynthesis in the morning to oxygenic photosynthesis during the rest of the day which results in a temporal build up of elemental sulfur during the day and disappears at night due to both oxidation to thiosulfate and sulfate by thiobacilli, and reduction to hydrogen sulfide by Desulfuromonas sp. and anaerobically respiring cyanobacteria. Sulfate reduction was enhanced in the light at the surface of the cyanobacterial mats. Microsulfate reduction measurements showed enhanced activity of sulfate reduction even under high oxygen concentrations of 300 to 800 micrometer. Apparent aerobic SO sub 4 reduction activity is explained by the co-occurrence of H sub 2. The physiology of this apparent sulfate reduction activity is studied.

Cohen, Y.↗

NASA NTRS1992

Feature detection in satellite images using neural network technology

A feasibility study of automated classification of satellite images is described. Satellite images were characterized by the textures they contain. In particular, the detection of cloud textures was investigated. The method of second-order gray level statistics, using co-occurrence matrices, was applied to extract feature vectors from image segments. Neural network technology was employed to classify these feature vectors. The cascade-correlation architecture was successfully used as a classifier. The use of a Kohonen network was also investigated but this architecture could not reliably classify the feature vectors due to the complicated structure of the classification problem. The best results were obtained when data from different spectral bands were fused.

Augusteijn, Marijke F.↗

NASA NTRS1995

A relational metric, its application to domain analysis, and an example analysis and model of a remote sensing domain

An objective and quantitative method has been developed for deriving models of complex and specialized spheres of activity (domains) from domain-generated verbal data. The method was developed for analysis of interview transcripts, incident reports, and other text documents whose original source is people who are knowledgeable about, and participate in, the domain in question. To test the method, it is applied here to a report describing a remote sensing project within the scope of the Earth Observing System (EOS). The method has the potential to improve the designs of domain-related computer systems and software by quickly providing developers with explicit and objective models of the domain in a form which is useful for design. Results of the analysis include a network model of the domain, and an object-oriented relational analysis report which describes the nodes and relationships in the network model. Other products include a database of relationships in the domain, and an interactive concordance. The analysis method utilizes a newly developed relational metric, a proximity-weighted frequency of co-occurrence. The metric is applied to relations between the most frequently occurring terms (words or multiword entities) in the domain text, and the terms found within the contexts of these terms. Contextual scope is selectable. Because of the discriminating power of the metric, data reduction from the association matrix to the network is simple. In addition to their value for design. the models produced by the method are also useful for understanding the domains themselves. They can, for example, be interpreted as models of presence in the domain.

Mcgreevy, Michael W.↗

NASA NTRS1996

Reporter Concerns in 300 Mode-Related Incident Reports from NASA's Aviation Safety Reporting System

A model has been developed which represents prominent reporter concerns expressed in the narratives of 300 mode-related incident reports from NASA's Aviation Safety Reporting System (ASRS). The model objectively quantifies the structure of concerns which persist across situations and reporters. These concerns are described and illustrated using verbatim sentences from the original narratives. Report accession numbers are included with each sentence so that concerns can be traced back to the original reports. The results also include an inventory of mode names mentioned in the narratives, and a comparison of individual and joint concerns. The method is based on a proximity-weighted co-occurrence metric and object-oriented complexity reduction.

McGreevy, Michael W.↗

NASA NTRS1997

Computer Supported Indexing: A History and Evaluation of NASA's MAI System

Computer supported or machine aided indexing (MAI) can be categorized in multiple ways. The system used by the National Aeronautics and Space Administration's (NASA's) Center for AeroSpace Information (CASI) is described as semantic and computational. It's based on the co-occurrence of domain-specific terminology in parts of a sentence, and the probability that an indexer will assign a particular index term when a given word or phrase is encountered in text. The NASA CASI system is run on demand by the indexer and responds in 3 to 9 seconds with a list of suggested, authorized terms. The system was originally based on a syntactic system used in the late 1970's by the Defense Technical Information Center (DTIC). The NASA mainframe-supported system consists of three components: two programs and a knowledge base (KB). The evolution of the system is described and flow charts illustrate the MAI procedures. Tests used to evaluate NASA's MAI system were limited to those that would not slow production. A very early test indicated that MAI saved about 3 minutes and provided several additional terms for each document indexed. It also was determined that time and other resources spent in careful construction of the KB pay off with high-quality output and indexer acceptance of MAI results.

Silvester, June P.↗

NASA NTRS1997

Computer Supported Indexing: A History and Evaluation of NASA's MAI System

Computer supported indexing systems may be categorized in several ways. One classification scheme refers to them as statistical, syntactic, semantic or knowledge-based. While a system may emphasize one of these aspects, most systems actually combine two or more of these mechanisms to maximize system efficiency. Statistical systems can be based on counts of words or word stems, statistical association, and correlation techniques that assign weights to word locations or provide lexical disambiguation, calculations regarding the likelihood of word co-occurrences, clustering of word stems and transformations, or any other computational method used to identify pertinent terms. If words are counted, the ones of median frequency become candidate index terms. Syntactical systems stress grammar and identify parts of speech. Concepts found in designated grammatical combinations, such as noun phrases, generate the suggested terms. Semantic systems are concerned with the context sensitivity of words in text. The primary goal of this type of indexing is to identify without regard to syntax the subject matter and the context-bearing words in the text being indexed. Knowledge-based systems provide a conceptual network that goes past thesaurus or equivalent relationships to knowing (e.g., in the National Library of Medicine (NLM) system) that because the tibia is part of the leg, a document relating to injuries to the tibia should he indexed to LEG INJURIES, not the broader MeSH term INJURIES, or knowing that the term FEMALE should automatically be added when the term PREGNANCY is assigned, and also that the indexer should be prompted to add either HUMAN or ANIMAL. Another way of categorizing indexing systems is to identify them as producing either assigned- or derived-term indexes.

Silvester, June P.↗

NASA NTRS1997

Surface-Based Observations of Contrail Occurrence Over the US, Apr. 1993 to Apr. 1994

Surface observers stationed at 19 U.S. Air Force Bases and Army Air Stations recorded the daytime occurrence of contrails and cloud fraction on an hourly basis for the period April 1993 through April 1994. Each observation uses one of four main categories to report contrails as unobserved, non-persistent, persistent, and indeterminate. Additional classification includes the co-occurrence of cirrus with each report. The data cover much of the continental U.S. including locations near major commercial air routes. The mean annual frequency of occurrence in unobstructed viewing conditions is 13 percent for these sites. Contrail occurrence varied substantially with location and season. Most contrails occurred during the winter months and least during the summer with a pronounced minimum during July. Although nocturnal observations are not available, it appears that the contrails have a diurnal variation that peaks during mid morning over most areas. Contrails were most often observed in areas near major commercial air corridors and least often over areas far removed from the heaviest air traffic. A significant correlation exists between mean contrail frequency and aircraft fuel usage above 7 km suggesting predictive potential for assessing future contrail effects on climate.

Minnis, Patrick↗

NASA NTRS1999

ISCCP Cloud Properties Associated with Standard Cloud Types Identified in Individual Surface Observations

Individual surface weather observations from land stations and ships are compared with individual cloud retrievals of the International Satellite Cloud Climatology Project (ISCCP), Stage C1, for an 8-year period (1983-1991) to relate cloud optical thicknesses and cloud-top pressures obtained from satellite data to the standard cloud types reported in visual observations from the surface. Each surface report is matched to the corresponding ISCCP-C1 report for the time of observation for the 280x280-km grid-box containing that observation. Classes of the surface reports are identified in which a particular cloud type was reported present, either alone or in combination with other clouds. For each class, cloud amounts from both surface and C1 data, base heights from surface data, and the frequency-distributions of cloud-top pressure (p(sub c) and optical thickness (tau) from C1 data are averaged over 15-degree latitude zones, for land and ocean separately, for 3-month seasons. The frequency distribution of p(sub c) and tau is plotted for each of the surface-defined cloud types occurring both alone and with other clouds. The average cloud-top pressures within a grid-box do not always correspond well with values expected for a reported cloud type, particularly for the higher clouds Ci, Ac, and Cb. In many cases this is because the satellites also detect clouds within the grid-box that are outside the field of view of the surface observer. The highest average cloud tops are found for the most extensive cloud type, Ns, averaging 7 km globally and reaching 9 km in the ITCZ. Ns also has the greatest average retrieved optical thickness, tau approximately equal 20. Cumulonimbus clouds may actually attain far greater heights and depths, but do not fill the grid-box. The tau-p(sub c) distributions show features that distinguish the high, middle, and low clouds reported by the surface observers. However, the distribution patterns for the individual low cloud types (Cu, Sc, St) occurring alone overlap to such an extent that it is not possible to distinguish these cloud types from each other on the basis of tau-p(sub c) values alone. Other cloud types whose tau-p(sub c) distributions are indistinguishable are Cb, Ns, and thick As. However, the tau-p(sub c) distribution patterns for the different low cloud types are nevertheless distinguishable when all occurrences of a low cloud type are included, indicating that the different low types differ in their probabilities of co-occurrence with middle and high clouds.

Hahn, Carole J.↗

NASA NTRS2000

Overcast Clouds Determined By Trmm Measurements

Using the Tropical Rainfall Measuring Mission (TRMM) Visible and Infra-Red Scanner (VIRS) and TRMM Microwave Radiometer (TMI) measurements, this study retrieves cloud optical depth (tau), liquid water path (LWP), and the frequency of co-occurrence of ice and water clouds based on radiative transfer models. Results show that LWP values for warm non-precipitating clouds are approximately 0.06mm and cold clouds have large ice water amount (approximately 0.1mm). The cloud systems with significant amounts of water below ice occur about 10 to approximately 20% of the time.

Lin, Bing↗