Geology topics

G.H. Rosenfield

Publications and source records attributed to G.H. Rosenfield.

8 recordsLinked to original sources

USGS1987

Stratification of a cityscape using census and land use variables for inventory of building materials

A cityscape (or any landscape) can be stratified into environmental units using multiple variables of information. For the purposes of sampling building materials, census and land use variables were used to identify similar strata. In the Metropolitan Statistical Area of a cityscape, the census tract is the smallest unit for which census data are summarized and digitized boundaries are available. For purposes of this analysis, census data on total population, total number of housing units, and number of singleunit dwellings were aggregated into variables of persons per square kilometer and proportion of housing units in single-unit dwellings. The level 2 categories of the U.S. Geological Survey's land use and land cover data base were aggregated into variables of proportion of residential land with buildings, proportion of nonresidential land with buildings, and proportion of open land. The cityscape was stratified, from these variables, into environmental strata of Urban Central Business District, Urban Livelihood Industrial Commercial, Urban Multi-Family Residential, Urban Single Family Residential, Non-Urban Suburbanizing, and Non-Urban Rural. The New England region was chosen as a region with commonality of building materials, and a procedure developed for trial classification of census tracts into one of the strata. Final stratification was performed by discriminant analysis using the trial classification and prior probabilities as weights. The procedure was applied to several cities, and the results analyzed by correlation analysis from a field sample of building materials. The methodology developed for stratification of a cityscape using multiple variables has application to many other types of environmental studies, including forest inventory, hydrologic unit management, waste disposal, transportation studies, and other urban studies. Multivariate analysis techniques have recently been used for urban stratification in England. ?? 1987 Annals of Regional Science.

The Annals of Regional Science↗

USGS1986

Determination of total, commonality, and uniqueness of interpreted structural elements from remotely sensed data in Alaska

Statistical analysis is conducted to determine the unique value of real- and synthetic-aperture side-looking airborne radar (SLAR) to detect interpreted structural elements. SLAR images were compared to standard and digitally enhanced Landsat multispectral scanner (MSS) images and to aerial photographs. After interpretation of the imagery, data were cumulated by total length in miles and by frequency of counts. Maximum uniqueness is obtained first from real-aperture SLAR, 58.3% of total, and, second, from digitally enhanced Landsat MSS images, 54.1% of total. ?? 1986 Plenum Publishing Corporation.

Mathematical Geology↗

USGS1986

Analysis of thematic map classification error matrices.

The classification error matrix expresses the counts of agreement and disagreement between the classified categories and their verification. Thematic mapping experiments compare variables such as multiple photointerpretation or scales of mapping, and produce one or more classification error matrices. This paper presents a tutorial to implement a typical problem of a remotely sensed data experiment for solution by the linear model method.-from Author

Photogrammetric Engineering and Remote Sensing↗

USGS1986

A coefficient of agreement as a measure of thematic classification accuracy.

The classification error matrix typically contains tabulated results of accuracy evaluation for a thematic classification, such as a land-use and land-cover map. Diagonal elements of the matrix represent counts correct. The usual designation of classification accuracy has been total percent correct. Nondiagonal elements of the matrix have usually been neglected. A coefficient of agreement is determined for the interpreted map as a whole, and individually for each interpreted category. These coefficients utilize all cell values in the matrix.-from Authors

Photogrammetric Engineering and Remote Sensing↗

USGS1982

Analyzing thematic maps and mapping for accuracy

Two problems which exist while attempting to test the accuracy of thematic maps and mapping are: (1) evaluating the accuracy of thematic content, and (2) evaluating the effects of the variables on thematic mapping. Statistical analysis techniques are applicable to both these problems and include techniques for sampling the data and determining their accuracy. In addition, techniques for hypothesis testing, or inferential statistics, are used when comparing the effects of variables. A comprehensive and valid accuracy test of a classification project, such as thematic mapping from remotely sensed data, includes the following components of statistical analysis: (1) sample design, including the sample distribution, sample size, size of the sample unit, and sampling procedure; and (2) accuracy estimation, including estimation of the variance and confidence limits. Careful consideration must be given to the minimum sample size necessary to validate the accuracy of a given. classification category. The results of an accuracy test are presented in a contingency table sometimes called a classification error matrix. Usually the rows represent the interpretation, and the columns represent the verification. The diagonal elements represent the correct classifications. The remaining elements of the rows represent errors by commission, and the remaining elements of the columns represent the errors of omission. For tests of hypothesis that compare variables, the general practice has been to use only the diagonal elements from several related classification error matrices. These data are arranged in the form of another contingency table. The columns of the table represent the different variables being compared, such as different scales of mapping. The rows represent the blocking characteristics, such as the various categories of classification. The values in the cells of the tables might be the counts of correct classification or the binomial proportions of these counts divided by either the row totals or the column totals from the original classification error matrices. In hypothesis testing, when the results of tests of multiple sample cases prove to be significant, some form of statistical test must be used to separate any results that differ significantly from the others. In the past, many analyses of the data in this error matrix were made by comparing the relative magnitudes of the percentage of correct classifications, for either individual categories, the entire map or both. More rigorous analyses have used data transformations and (or) two-way classification analysis of variance. A more sophisticated step of data analysis techniques would be to use the entire classification error matrices using the methods of discrete multivariate analysis or of multiviariate analysis of variance.

Open-File Report↗

USGS1982

Sample design for estimating change in land use and land cover ( Pennsylvania).

The methodology of sample design which is applied to estimating change in land use and land cover is general and extendable to determination of change in any type of thematic mapping that is time variant. Land-use maps of the State of Pennsylvania at a scale of 1:250,000 were compiled circa 1958 with land use classified into six categories. The more detailed land-use and land-cover mapping of the State of Pennsylvania at a scale of 1:250,000 was completed by the U.S. Geological Survey circa 1977. With some rearrangement of these categories, the recent maps are very nearly compatible with a combination of five categories of the earlier maps. -from Author

Photogrammetric Engineering and Remote Sensing↗

USGS1981

Analysis of variance of thematic mapping experiment data.

As an example of the methodology, data from an experiment using three scales of land-use and land-cover mapping have been analyzed. The binomial proportions of correct interpretations have been analyzed untransformed and transformed by both the arcsine and the logit transformations. A weighted analysis of variance adjustment has been used. There is evidence of a significant difference among the three scales of mapping (1:24 000, 1:100 000 and 1:250 000) using the transformed data. Multiple range tests showed that all three scales are different for the arcsine transformed data. - from Author

Photogrammetric Engineering and Remote Sensing↗

USGS1980

Applications of statistics to thematic mapping.

Two statistical problems occurring in the effort to analyze thematic maps and mapping are determining the accuracy of thematic content and comparing factors studied in thematic mapping. Statistical procedures applicable to thematic mapping involve sampling, determining accuracy, and comparing factors. A sampling procedure using an unaligned pattern within a square grid network is applicable for use with thematic maps. Sample size may be determined using the binomial distribution based upon the confidence interval to define the true mean of the population within certain limits. The confidence interval may also be used to define the upper and lower limits of the accuracy of the thematic map. - from Authors

Photogrammetric Engineering and Remote Sensing↗