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At least 1,405 records · Page 78

Land cover classification accuracy as a function of sensor spatial resolution

The benefits obtained from sensor systems for monitoring earth resources will depend on the application and interpretation methods used. A frequently used analysis method is supervised per-pixel multispectral classification with a typical application being land cover classification. An investigation is conducted to evaluate the effect of spatial resolution on the ability to classify land cover types with per-pixel digital image classification techniques. Attention is also given to the documentation of changes in scene noise and the percentage of boundary pixels as a function of spatial resolution, in order to improve the understanding of the interrelationship between classification accuracy and spatial resolution. It is found that scene noise varies considerably between land cover categories. Changes in scene noise with coarsening resolution occur at different rates for different categories.

Markham, B. L.↗

Fanning - A classification algorithm for mixture landscapes applied to Landsat data of Maine forests

It is pointed out that typical landscapes include a relatively small number of 'pure' land cover types which combine in various proportions to form a myriad of mixture types. Most Landsat classifications algorithms used today require a separate user specification for each category, including mixture categories. Attention is given to a simpler approach, which would require the user to specify only the 'pure' types. Mixture pixels would be classified on the basis of the proportion of the area covered by each pure type within the pixel. The 'fanning' algorithm quantifies varying proportions of two 'pure' land cover types in selected mixture pixels. This algorithm was applied to 200,000 ha of forest land in Maine, taking into account a comparison with standard inventory information. Results compared well with a discrete categories classification of the same area.

Ungar, S. G.↗

A quantitative applications-oriented evaluation of Thematic Mapper design specifications

Simulated Thematic Mapper data sets were created from aircraft Multispectral Scanner data in order to predict the sensitivity of applications-oriented classification results to variations in selected sensor parameters. It was found that band-to-band misregistration as little as 0.3 pixel can have a pronounced effect on the classification of both field-center pixels and pixels associated with edges and small objects in the scene. It was also determined that a significant improvement in classification accuracy could be achieved if the resolution of the thermal band of the Thematic Mapper were comparable to the resolution of its other spectral bands.

Swain, P. H.↗

Sensitivity of geographic information system outputs to errors in remotely sensed data

The sensitivity of the outputs of a geographic information system (GIS) to errors in inputs derived from remotely sensed data (RSD) is investigated using a suitability model with per-cell decisions and a gridded geographic data base whose cells are larger than the RSD pixels. The process of preparing RSD as input to a GIS is analyzed, and the errors associated with classification and registration are examined. In the case of the model considered, it is found that the errors caused during classification and registration are partially compensated by the aggregation of pixels. The compensation is quantified by means of an analytical model, a Monte Carlo simulation, and experiments with Landsat data. The results show that error reductions of the order of 50% occur because of aggregation when 25 pixels of RSD are used per cell in the geographic data base.

Ramapriyan, H. K.↗

LANDSAT-4 image data quality analysis

Work done on evaluating the geometric and radiometric quality of early LANDSAT-4 sensor data is described. Band to band and channel to channel registration evaluations were carried out using a line correlator. Visual blink comparisons were run on an image display to observe band to band registration over 512 x 512 pixel blocks. The results indicate a .5 pixel line misregistration between the 1.55 to 1.75, 2.08 to 2.35 micrometer bands and the first four bands. Also a four 30M line and column misregistration of the thermal IR band was observed. Radiometric evaluation included mean and variance analysis of individual detectors and principal components analysis. Results indicate that detector bias for all bands is very close or within tolerance. Bright spots were observed in the thermal IR band on an 18 line by 128 pixel grid. No explanation for this was pursued. The general overall quality of the TM was judged to be very high.

Anuta, P. E.↗

Photon-counting array detectors for space and ground-based studies at ultraviolet and vacuum ultraviolet /VUV/ wavelengths

The Multi-Anode Microchannel Arrays (MAMAs) are a family of photoelectric photon-counting array detectors, with formats as large as (256 x 1024)-pixels that can be operated in a windowless configuration at vacuum ultraviolet (VUV) and soft X-ray wavelengths or in a sealed configuration at ultraviolet and visible wavelengths. This paper describes the construction and modes of operation of (1 x 1024)-pixel and (24 x 1024)-pixel MAMA detector systems that are being built and qualified for use in sounding-rocket spectrometers for solar and stellar observations at wavelengths below 1300 A. The performance characteristics of the MAMA detectors at ultraviolet and VUV wavelengths are also described.

Timothy, J. G.↗

Autonomous earth feature classification - Shuttle and aircraft flight test results

The Feature Identification and Location Experiment (FILE) flown on the Shuttle STS-2 mission November 12-14, 1981, tested a technique for autonomous real-time classification of selected earth features, i.e., water; bare land; vegetation; and clouds, snow, and ice. A second instrument, designed for aircraft flights, flew over regions of the west and east coasts of the United States and across the country. In each instrument, two bore-sighted CCD cameras image earth scenes in two spectral bands. Each camera includes a 100-element by 100-element detector array, and classification circuits. A simple algorithm and logic circuit provides classification decisions within a few microseconds. The experiment records the number of picture elements (pixels) representing each feature and the reflected solar radiation for each band. After flight, pixel-by-pixel classification images are constructed and compared with 70-mm color photographs taken simultaneously with the CCD-camera data.

Sivertson, W. E., Jr.↗

Quantile Data Analysis of Image Data

Quantile data analysis and functional statistical inference methods are introduced and applied to provide representations of spectral data which may lead to simple statistical discriminators effective for the estimation of ground truth from satellite spectral measurements. To estimate the ground truth of a pixel, the probability of each possible ground truth is estimated, given observed (estimated) quantile theoretic statistical characteristics of the multispectral image data corresponding to the pixel and its neighboring pixels. A strategy for determining which statistical characteristics discriminate best is described. Results are reported of quantile data analysis of an extensive collection of training files of image data.

Parzen, E.↗

Comparison of the information content of data from the LANDSAT 4 Thematic Mapper and the multispectral scanner

Evaluation of information contained in data from the visible and near-IR channels of LANDSAT 4 TM and MSS for five agricultural scenes shows that the TM provides a significant advance in information gathering capability as expressed in terms of bits per pixel or bits per unit area. The six reflective channels of the TM acquire 18 bits of information per pixel out of a possible 48 bits, while the four MSS channels acquire 10 bits of information per pixel out of a possible 28 bits. Thus the TM and MSS are equally efficient in gathering information (18/48 to approximately 10/28), contrary to the expected tendency toward lower efficiency as spatial resolution is improved and spectral channels are added to an observing system. The TM thermal IR data appear to be of interest mainly for mapping water bodies, which do not change temperature during the day, for assessing surface moisture, and for monitoring thermal features associated with human activity.

Price, J. C.↗

Assessment of Thematic Mapper Band-to-band Registration by the Block Correlation Method

The design of the Thematic Mapper (TM) multispectral radiometer makes it susceptible to band-to-band misregistration. To estimate band-to-band misregistration a block correlation method is employed. This method is chosen over other possible techniques (band differencing and flickering) because quantitative results are produced. The method correlates rectangular blocks of pixels from one band against blocks centered on identical pixels from a second band. The block pairs are shifted in pixel increments both vertically and horizontally with respect to each other and the correlation coefficient for each shift position is computed. The displacement corresponding to the maximum correlation is taken as the best estimate of registration error for each block pair. Subpixel shifts are estimated by a bi-quadratic interpolation of the correlation values surrounding the maximum correlation. To obtain statistical summaries for each band combination post processing of the block correlation results performed. The method results in estimates of registration error that are consistent with expectations.

Card, D. H.↗

Investigation of TM Band-to-band Registration Using the JSC Registration Processor

The JSC registration processor performs scene-to-scene (or band-to-band) correlation based on edge images. The edge images are derived from a percentage of the edge pixels calculated from the raw scene data, excluding clouds and other extraneous data in the scene. Correlations are performed on patches (blocks) of the edge images, and the correlation peak location in each patch is estimated iteratively to fractional pixel location accuracy. Peak offset locations from all patches over the scene are then considered together, and a variety of tests are made to weed out outliers and other inconsistencies before a distortion model is assumed. Thus, the correlation peak offset locations in each patch indicate quantitatively how well the two TM bands register to each other over that patch of scene data. The average of these offsets indicate the overall accuracies of the band-to-band registration. The registration processor was also used to register one acquisition to another acquisition of multitemporal TM data acquired over the same ground track. Band 4 images from both acquisitions were correlated and an rms error of a fraction of a pixel was routinely obtained.

Yao, S. S.↗

Geodetic Accuracy of LANDSAT-4 Multispectral Scanner and Thematic Mapper Data

The geodetic accuracy of an MSS or TM scene is assessed using a minicomputer and appropriate software, a digitizer, and an image display device. The calculated image location of a selected feature is compared with the actual image location obtained though visual inspection of the image on the display. Measurements of 15 to 20 features evenly distributed throughout the image provide an estimate of the geodetic accuracy of the scene. Tests of two system-corrected MSS scenes measured geodetic registration root-mean-square (RMS) errors of approximately 3,200 m or 57 pixels. Tests of two TM system-corrected scenes measured RMS errors of approximately 1,250 and 1,000 m, or 44 and 35 pixels, respectively. All errors were primarily translational, implying good internal scene registration of both MSS and TM data. The one MSS GCP-corrected scene which was evaluated had an RMS error of approximately 325 m or 6 pixels.

Thormodsgard, J. M.↗

Spatial and spectral simulation of Landsat images of agricultural areas

A Landsat scene simulation capability was developed to study the effects of small fields and misregistration on Landsat-based crop proportion estimation procedures. The simulation employs a pattern of ground polygons each with a crop ID, planting date, and scale factor. Historical greenness/brightness crop development profiles generate the mean signal values for each polygon. Historical within-field covariances add texture to pixels in each polygon. The planting dates and scale factors create between-field/within-crop variation. Between field and crop variation is achieved by the above and crop profile differences. The Landsat point spread function is used to add correlation between nearby pixels. The next effect of the point spread function is to blur the image. Mixed pixels and misregistration are also simulated. Previously announced in STAR as N82-32813

Pont, W. F., Jr.↗

Picture-Element Comparator

Proposed circuit, called "neighborhood comparison operator," compares data from neighboring picture elements (pixels) to find peaks, ridges, and valleys in picture data. Circuit also able to expand or shrink pixel regions. Circuit concept developed for image-processing computers. Circuit handles data stream of 12-bit pixels rather than conventional 8 or 16 bits. Consist entirely of standard logic chips.

Gennery, D. B.↗

Scene segmentation through region growing

A computer algorithm to segment Landsat Thematic Mapper (TM) images into areas representing surface features is described. The algorithm is based on a region growing approach and uses edge elements and edge element orientation to define the limits of the surface features. Adjacent regions which are not separated by edges are linked to form larger regions. Some of the advantages of scene segmentation over conventional TM image extraction algorithms are discussed, including surface feature analysis on a pixel-by-pixel basis, and faster identification of the pixels in each region. A detailed flow diagram of region growing algorithm is provided.

Latty, R. S.↗

Evaluation of selected detector arrays for space applications

The development of a high density Schottky barrier Infrared Charged Coupled Device (IRCCD) type image sensor for earth observation was initiated. A dual band 512 pixel linear array was developed, which was capable of being butted end to end to make an arbitrarily long linear array. Measurement made on palladium silicide IRCCDs that were two-dimensional 63 x 32 pixel arrays were summarized. The test data on a 512 pixel linear array is also summarized.

Lowrance, J. L.↗

Automated matching of pairs of SIR-B images for elevation mapping

During the SIR-B mission in October 1984, a significant number of overlapping synthetic aperture radar (SAR) images of various ground areas was collected. This has offered the first opportunity to perform stereo analyses on images from space that cover large ground areas to determine elevation information. This paper presents the preliminary results of an investigation to obtain elevation data from stereo pairs of SIR-B images. First, the accuracy with which elevation information can be derived from SIR-B image pairs is evaluated theoretically. It is shown that elevation accuracy is a function of the slant range resolution, the incidence angles with which the stereo pair is obtained, the accuracies in spacecraft state estimation, and determination of corresponding pixels in the stereo pair. Next, a hierarchical method is developed to match the corresponding pixels. This method involves iterative removal of local distortions and correlations of pairs of local neighborhoods in the two images. Since it is necessary to perform the matching at every pixel in the image, it is very computationally intensive. Therefore, it has been implemented on the Massively Parallel Processor (MPP) at the Goddard Space Flight Center (GSFC). The MPP's speed permits two iterations of this technique to operate on a pair of 512 x 512 images within 7 s. Results of applying this algorithm of SIR-B images of Mount Shasta, CA, are shown. The matching algorithm performs well in regions of the image with significant features. An approximate elevation image derived from the matching process corresponds to published topographic map data, except for certain obvious discontinuities.

Ramapriyan, H. K.↗

Cloud cover estimation using bispectral satellite measurements

An algorithm has been developed for cloud cover estimation using bispectral satellite measurements. Based on the distribution of pixels in albedo-brightness temperature space, a number of threshold values are applied to identify those pixels which are most likely totally cloud filled. Mean cloudy-column albedo in a region much larger than a single pixel is then estimated and cloud cover computed. The algorithm has been applied to the International Satellite Cloud Climatology Project Geostationary Meteorological Satellite B2 data. Locations of tropical convective cells and the passage of fronts in higher latitudes are identified. Since these features represent the states of large-scale atmospheric circulations, it is concluded that the algorithm can yield consistent cloud data sets useful for climate studies.

Chou, M.-D.↗