SEARCH · Engineering Papers

Results for “unsupervised classification”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 73 records · Page 4

All sources NASA NTRS DOE OSTI

NASA NTRS1977

Applications of LANDSAT data to the integrated economic development of Mindoro, Phillipines

LANDSAT data is seen as providing essential up-to-date resource information for the planning process. LANDSAT data of Mindoro Island in the Philippines was processed to provide thematic maps showing patterns of agriculture, forest cover, terrain, wetlands and water turbidity. A hybrid approach using both supervised and unsupervised classification techniques resulted in 30 different scene classes which were subsequently color-coded and mapped at a scale of 1:250,000. In addition, intensive image analysis is being carried out in evaluating the images. The images, maps, and aerial statistics are being used to provide data to seven technical departments in planning the economic development of Mindoro. Multispectral aircraft imagery was collected to compliment the application of LANDSAT data and validate the classification results.

Wagner, T. W.↗

NASA NTRS1980

LANDSAT signature development program

LANDSAT signature development program (LSDP) automatically produces unsupervised classification of scene from LANDSAT data tape. Program is effective enough to be useful to sophisticated remote sensing analyst yet is simple enough to be utilized by ground truth investigators who have only basic understanding of computer and remote sensing procedures.

Bland, R. A.↗

NASA NTRS1980

A hill-sliding strategy for initialization of Gaussian clusters in the multidimensional space

A hill sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimate of sample data for the first step of iterative unsupervised classification. Each cluster was assumed to posses a unimodal normal distribution. A clustering function proposed distinguished elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with LANDSAT multispectral scanner data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill sliding clustering technique developed herein has the potential applicability to decomposition any multivariate mixture distribution into a number of unimodal distributions when an appropriate distribution function to the data set is employed.

Park, J. K.↗

NASA NTRS1982

Digital overlay of cartographic information on Landsat MSS data for soil surveys

Cartographic soils data were digitized, spatially registered, and merged with processed Landsat image data. The Landsat Multispectral Scanner Subsystem (MSS) image data were used to generate a thematic map representing different soil surface characteristics and an enhanced image. The thematic map was generated using supervised and unsupervised classification procedures. The enhanced image was generated by performing a linear contrast stretch on data altered by a principal components transformation. Although both procedures yielded images useful for soil unit delineation, image enhancement was determined to be more suitable because it was more expedient and inexpensive. Enhanced images cost $0.06 per hectare, spectral classifications cost $0.08 per hectare. The overlay of cartographic data on Landsat data facilitates comparisons between the various processing methods used for soil unit boundary determination, delineation, and verification. This technique also provides for accurate and expedient spatial referencing for field observations and cartographic correlation.

Imhoff, M. L.↗

NASA NTRS1978

LANDSAT image differencing as an automated land cover change detection technique

Image differencing was investigated as a technique for use with LANDSAT digital data to delineate areas of land cover change in an urban environment. LANDSAT data collected in April 1973 and April 1975 for Austin, Texas, were geometrically corrected and precisely registered to United States Geological Survey 7.5-minute quadrangle maps. At each pixel location reflectance values for the corresponding bands were subtracted to produce four difference images. Areas of major reflectance differences are isolated by thresholding each of the difference images. The resulting images are combined to obtain an image data set to total change. These areas of reflectance differences were found, in general, to correspond to areas of land cover change. Information on areas of land cover change was incorporated into a procedure to mask out all nonchange areas and perform an unsupervised classification only for data in the change areas. This procedure identified three broad categories: (1) areas of high reflectance (construction or extractive), (2) changes in agricultural areas, and (3) areas of confusion between agricultural and other areas.

Stauffer, M. L.↗

NASA NTRS1981

Development and implementation of a low cost micro computer system for LANDSAT analysis and geographic data base applications

Since the implementation of the GRID and IMGRID computer programs for multivariate spatial analysis in the early 1970's, geographic data analysis subsequently moved from large computers to minicomputers and now to microcomputers with radical reduction in the costs associated with planning analyses. Programs designed to process LANDSAT data to be used as one element in a geographic data base were used once NIMGRID (new IMGRID), a raster oriented geographic information system, was implemented on the microcomputer. Programs for training field selection, supervised and unsupervised classification, and image enhancement were added. Enhancements to the color graphics capabilities of the microsystem allow display of three channels of LANDSAT data in color infrared format. The basic microcomputer hardware needed to perform NIMGRID and most LANDSAT analyses is listed as well as the software available for LANDSAT processing.

Faust, N.↗

NASA NTRS1981

Application of LANDSAT data to monitor land reclamation progress in Belmont County, Ohio

Strip and contour mining techniques are reviewed as well as some studies conducted to determine the applicability of LANDSAT and associated digital image processing techniques to the surficial problems associated with mining operations. A nontraditional unsupervised classification approach to multispectral data is considered which renders increased classification separability in land cover analysis of surface mined areas. The approach also reduces the dimensionality of the data and requires only minimal analytical skills in digital data processing.

Bloemer, H. H. L.↗

NASA NTRS1983

Integration of environmental and spectral data for sunflower stress determination

Stress in sunflowers was assessed in western and northwestern Minnesota. Weekly ground observations (acquired in 1980 and 1981) were analyzed in concert with large scale aerial photography and concurrent LANDSAT data. Using multidate supervised and unsupervised classification procedures, it was found that all crops grown in association with sunflowers in the study area are spectrally separable from one another. Under conditions of extreme drought, severely stressed plants were differentiable from those not severely stressed, but between-crop separation was not possible. Initial regression analyses to estimate sunflower seed yield showed a sensitivity to environmental stress during the flowering and seed development stages. One of the most important biological factors related to sunflower production in the Red River Valley area was found to be the extent and severity of insect infestations.

Lillesand, T.↗

NASA NTRS1982

A Temporal Approach to Monitor Surface Mine Reclamation Progress via LANDSAT

Using LANDSAT satellite imagery, the mine reclamation process can be studied on a temporal and continuing basis. Not only can the progress of reclamation be readily monitored, but also a breakdown in the mining reclamation process can be detected. In viewing reclamation, it is important to monitor the mined site well past initial revegation stages. With present mining law and bonding procedures, fast revegetational growth is encouraged, often leading to poor soil fertilizing and inappropriate stabilizing species. As a result, the initial reclamation may exhibit good qualities for one or two years but then may experience vegetational deterioration after the state has relinquished the mining company from it's responsibility. It is this small-scale breakdown in the reclamation process that was detected using an unsupervised classification technique with eight-year temporal LANDSAT imagery coverage.

Davis, A. L.↗

NASA NTRS1982

Profile modeling for crop discrimination

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.

Badhwar, G. D.↗

NASA NTRS1987

Program for Analysis and Enhancement of Images

Land Analysis System (LAS) is collection of image-analysis computer programs designed to manipulate and analyze multispectral image data. Provides user with functions ingesting various sensor data, radiometric and geometric corrections, image registration, training site selection, supervised and unsupervised classification, Fourier domain filtering, and image enhancement. Sufficiently modular and includes extensive library of subroutines to permit inclusion of new algorithmic programs. Commercial package International Mathematical & Statistical Library (IMSL) required for full implementation of LAS. Written in VAX FORTRAN 77, C, and Macro assembler for DEC VAX operating under VMS 4.0.

Lu, Yun-Chi↗

NASA NTRS1988

Canopy reflectance modeling in a tropical wooded grassland

The Li-Strahler canopy reflectance model, driven by LANDSAT Thematic Mapper (TM) data, provided regional estimates of tree size and density in two bioclimatic zones in Africa. This model exploits tree geometry in an inversion technique to predict average tree size and density from reflectance data using a few simple patameters measured in the field and in the imagery. Reflectance properties of the trees were measured in the study sites using a pole-mounted radiometer. The measurements showed that the assumptions of the simple Li-Strahler model are reasonable for these woodlands. The field radiometer measurements were used to calculate the normalized difference vegetation index (NDVI), and the integrated NDVI over the canopy was related to crown volume. Predictions of tree size and density from the canopy model were used with allometric equations from the literature to estimate woody biomass and potential foliar biomass for the sites and for the regions. Estimates were compared with independent measurements made in the Sahelian sites, and to typical values from the literature for these regions and for similar woodlands. In order to apply the inversion procedure regionally, an area must first be stratified into woodland cover classes, and dry-season TM data were used to generate a stratum map of the study areas with reasonable accuracy. The method used was unsupervised classification of multi-data principal components images.

Simonett, David↗

NASA NTRS1987

Vegetation spatial variability and its effect on vegetation indices

Landsat MSS data were used to simulate low resolution satellite data, such as NOAA AVHRR, to quantify the fractional vegetation cover within a pixel and relate the fractional cover to the normalized difference vegetation index (NDVI) and the simple ratio (SR). The MSS data were converted to radiances from which the NDVI and SR values for the simulated pixels were determined. Each simulated pixel was divided into clusters using an unsupervised classification program. Spatial and spectral analysis provided a means of combining clusters representing similar surface characteristics into vegetated and non-vegetated areas. Analysis showed an average error of 12.7 per cent in determining these areas. NDVI values less than 0.3 represented fractional vegetated areas of 5 per cent or less, while a value of 0.7 or higher represented fractional vegetated areas greater than 80 per cent. Regression analysis showed a strong linear relation between fractional vegetation area and the NDVI and SR values; correlation values were 0.89 and 0.95 respectively. The range of NDVI values calculated from the MSS data agrees well with field studies.

Ormsby, J. P.↗

NASA NTRS1990

Mesoscale monitoring of the soil freeze/thaw boundary from orbital microwave radiometry

A technique was developed for mapping the spatial extent of frozen soils from the spectral characteristics of the 10.7 to 37 GHz radiobrightness. Through computational models for the spectral radiobrightness of diurnally heated freesing soils, a distinctive radiobrightness signature was identified for frozen soils, and the signature was cast as a discriminant for unsupervised classification. In addition to large area images, local area spatial averages of radiobrightness were calculated for each radiobrightness channel at 7 meteorologic sites within the test region. Local area averages at the meteorologic sites were used to define the preliminary boundaries in the Freeze Indicator discriminate. Freeze Indicator images based upon Nimbus 7, Scanning Multichannel Microwave Radiometer (SMMR) data effectively map temporal variations in the freeze/thaw pattern for the northern Great Plains at the time scale of days. Diurnal thermal gradients have a small but measurable effect upon the SMMR spectral gradient. Scale-space filtering can be used to improve the spatial resolution of a freeze/thaw classified image.

Dobson, Craig↗

NASA NTRS1991

Near ground level sensing for spatial analysis of vegetation

Measured changes in vegetation indicate the dynamics of ecological processes and can identify the impacts from disturbances. Traditional methods of vegetation analysis tend to be slow because they are labor intensive; as a result, these methods are often confined to small local area measurements. Scientists need new algorithms and instruments that will allow them to efficiently study environmental dynamics across a range of different spatial scales. A new methodology that addresses this problem is presented. This methodology includes the acquisition, processing, and presentation of near ground level image data and its corresponding spatial characteristics. The systematic approach taken encompasses a feature extraction process, a supervised and unsupervised classification process, and a region labeling process yielding spatial information.

Sauer, Tom↗

NASA NTRS1992

Identification of sea ice types in spaceborne synthetic aperture radar data

This study presents an approach for identification of sea ice types in spaceborne SAR image data. The unsupervised classification approach involves cluster analysis for segmentation of the image data followed by cluster labeling based on previously defined look-up tables containing the expected backscatter signatures of different ice types measured by a land-based scatterometer. Extensive scatterometer observations and experience accumulated in field campaigns during the last 10 yr were used to construct these look-up tables. The classification approach, its expected performance, the dependence of this performance on radar system performance, and expected ice scattering characteristics are discussed. Results using both aircraft and simulated ERS-1 SAR data are presented and compared to limited field ice property measurements and coincident passive microwave imagery. The importance of an integrated postlaunch program for the validation and improvement of this approach is discussed.

Kwok, Ronald↗

NASA NTRS1992

Radiobrightness decision criteria for freeze/thaw boundaries

A freeze indicator (FI), based on a low 37-GHz radiobrightness and a low 10.7, 18, and 37-GHz radiobrightness spectral gradient, has been used to classify frozen surfaces in the northern Great Plains. By modeling the radiometer beampatterns as Gaussian, freeze/thaw boundaries can be located at the (fine) resolution of the 37-GHz channel. The performance of the freeze indicator, and subsequent boundary location estimate, depends on the accuracy of the boundary decision criteria. It is shown that decision criteria based on clustering and unsupervised classification yield good performance. A simple algorithm for registering coarse-resolution FI boundaries to equivalent boundaries in fine-resolution 37-GHz radiobrightness images is also presented.

Zuerndorfer, B.↗

NASA NTRS1992

Linear mixing model applied to coarse resolution satellite data

A linear mixing model typically applied to high resolution data such as Airborne Visible/Infrared Imaging Spectrometer, Thematic Mapper, and Multispectral Scanner System is applied to the NOAA Advanced Very High Resolution Radiometer coarse resolution satellite data. The reflective portion extracted from the middle IR channel 3 (3.55 - 3.93 microns) is used with channels 1 (0.58 - 0.68 microns) and 2 (0.725 - 1.1 microns) to run the Constrained Least Squares model to generate fraction images for an area in the west central region of Brazil. The derived fraction images are compared with an unsupervised classification and the fraction images derived from Landsat TM data acquired in the same day. In addition, the relationship betweeen these fraction images and the well known NDVI images are presented. The results show the great potential of the unmixing techniques for applying to coarse resolution data for global studies.

Holben, Brent N.↗