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Hallada, W. A.

Publications and source records attributed to Hallada, W. A..

Topological grid structure - A data structure for earth science modeling

The automated analysis of land surface features is increasingly important to earth scientists. User-friendly algorithms for studying these features can be integrated into geographic information systems through the use of topological grid structure, which maintains the simplicity and transportability of standard grid structure while providing the essential capability to treat groups of contiguous, identically-classified pixels (corresponding to lakes, forests, fields, etc.) as distinct spatial entities.

Goldberg, M.

Image sharpening for mixed spatial and spectral resolution satellite systems

Two methods of image sharpening (reconstruction) are compared. The first, a spatial filtering technique, extrapolates edge information from a high spatial resolution panchromatic band at 10 meters and adds it to the low spatial resolution narrow spectral bands. The second method, a color normalizing technique, is based on the ability to separate image hue and brightness components in spectral data. Using both techniques, multispectral images are sharpened from 30, 50, 70, and 90 meter resolutions. Error rates are calculated for the two methods and all sharpened resolutions. The results indicate that the color normalizing method is superior to the spatial filtering technique.

Hallada, W. A.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

Hallada, W. A.

Comparison of Land Cover Information from LANDSAT MSS and Airborne TMS for Hydrological Applications: Preliminary Results

Land cover information for the Clinton River Basin (Michigan) derived from LANDSAT multispectral scanner (MSS) data was compared with that from airborne thematic mapper simulator (TMS) to investigate the probable capabilities of the thematic mapper (TM) launched aboard LANDSAT-4 in July 1982. The preliminary findings for one 7.5 minute topographic map, Mt. Clemens West, are reported. Significant improvements in land cover classification accuracy were obtained using TMS data as compared with MSS data. Overall mapping accuracy increased from 49 to 61 percent with an improvement from 71 to 84 percent in the residential category. A combination of four bands with one band in each major region of the spectrum (visible, near IR, middle IR and thermal IR) provided as good a discrimination of land cover as all seven TM bands. Based on the improved land cover classification accuracy of TM, TM data has the potential to provide more useful and effective input to US Army Corps of Engineers flood forecasting and flood damage prediction/assessment models.

Gervin, J. C.

LANDSAT Applications for the State of Delaware

The first phase of a cooperative demonstration project between the Eastern Regional Remote Sensing Applications Center and the Delaware Department of Natural Resources and Environmental Control is summarized. Separate land cover classifications were performed for three counties in Delaware using multiseasonal LANDSAT data from April 3 and July 20, 1974. The objective of the New Castle County and Kent County classifications was to provide general land cover information with special emphasis on existing farmland and deciduous and coniferous forest, respectively. A detailed study of existing inland and coastal wetland vegetation communities was attempted for Sussex County. Detailed accuracy assessments were conducted for general land cover in New Castle and Kent Counties and for wetland communities in Sussex County. The classifications were combined to provide a statewide Level I land cover map and acreage statistics. Based on these results, the participating state agencies determined that LANDSAT is a viable tool for mapping and monitoring land cover within the state.

Gervin, J. C.