ASPRS

PE&RS April 1997

VOLUME 63, NUMBER 4
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
JOURNAL OF THE AMERICAN SOCIETY FOR PHOTOGRAMMETRY AND REMOTE SENSING

Peer Reviewed Articles

367-370 Map Conversion and the UTM Grid
Frederick J. Doyle

Abstract
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Problems related to datum and coordinate conversion, Universal Transverse Mercator (UTM) map grids, International Terrestrial Reference Frame (ITRF), and terrain elevations derived from Global Positioning System (GPS) survey techniques are reviewed in this paper, and the geometric foundation for coordinate systems and map products are presented. Professional mapping societies must provide education on these problems as related to the need to extend the utility of the large scale maps of the United States into the 21st century. Mapping agencies such as the USGS will be required to take steps necessary to insure the currency of the 1:24 000-scale map series. 

371-375 Datum Shifts for UTM Coordinates
R. Welch and A. Homsey

Abstract
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The USGS 1:24 000-scale topographic maps and associated digital map products of the United States are cast on the North American Datum of 1927 (NAD 27). However, NAD 27 has been replaced by the North American Datum of 1983 (NAD 83). While shifts to translate the latitude/longitude (lat/long) graticule coordinates to NAD 83 are documented, no information is readily available on the shifts in metres needed to convert NAD 27 UTM Northing and Easting grid coordinates to NAD 83 values. These shifts may be determined with computer software such as the US Army Topographic Engineering Center (TEC) CORPSCON package or the commercially available Blue Marble Geographics Geographic Calculator program, and, when plotted at 2degrees intervals (lat/long) for the contiguous 48 states, show a remarkable consistency within the 6-degree-wide UTM zones, changing gradually from south to north. The shifts depicted in the graphical plots provide the map user with the values needed to quickly convert NAD 27 UTM grid coordinates to NAD 83 values.

377-380 The Gridded Map
Alden P. Colvocoresses

Abstract
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Today, the most suitable coordinate referencing system for large- scale maps is the Universal Transverse Mercator (UTM) grid. Most of the developed world now uses the UTM (or its equivalent) grid on its larger-scale maps, but the United States basic map series at 1:24 000 scale generally fails to do so. The evolution of hand- held Global Positioning System (GPS) units capable of delivering position accuracies to better than 10 m makes large-scale map gridding an item of immediate concern. Proper and complete gridding of this series should now be a top priority of the nation's mapping program.

381-383 Field Validation of the UTM Gridded Map
N.G. Terry, Jr.

Abstract
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Testing was conducted to evaluate the benefits of the UTM coordinate system and a fully gridded map for land-navigation and coordinate measurement tasks. Under field conditions, 20 of 22 test participants preferred the UTM coordinate system to the latitude/longitude (lat/long) system, and all participants favored maps with the full UTM grid to maps on which the grid is represented as marginal tick marks. A full UTM grid allowed coordinates to be measured quickly with a pocket-size coordinate reader to accuracies of approximately 10 m, as compared to 100 m when the map has only marginal UTM tick marks. In order to facilitate the integrated use of maps with GPS and GIS technologies, it is recommended that full UTM grids be printed on all 1:24 000-scale maps.

385-392 A Simulation Comparison of Three Marginal Area Estimators for Image Classification
Ding Yuan

Abstract
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Area estimations are often obtained through classifying surveyed or remotely sensed data along with necessary adjustment. In this paper, three marginal area estimators, including the direct estimator, inverse estimator, and additive estimator for image classification, were compared using Monte Carlo simulations. The results suggested that, under minimum constraints for the acceptable image classifer and under our simulation environment: both inverse and direct estimators were asymptotically unbiased and asymptotically zero-dispersed as sampling fraction increased; the direct estimator normally has a smaller bias than the inverse estimator, but the inverse estimator normally had smaller dispersion than the direct estimator when the sampling fraction was small; the additive estimator was not asymptotically unbiased and was competitive with the other two methods only when sampling fraction and number of classes were both small. Simulated feasible regions for the three marginal area estimators are presented in this paper. 

393-395 Quality Assessment of Polygon Labeling
Gerardo Bocco and Hugo Riemann

Abstract
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The high costs in time and resources of data validation makes the correct selection of a simple but robust adjustment method crucial. This paper describes an approach suitable for a polygon labeling assessment. The approach uses the geometric distribution where the sample size is a function of the desired confidence level of the database. It allows the detailed random verification of a selected map. All the area is equally exposed to testing and, if needed, to correction. 

397-402 Sensitivity of Selected Landscape Pattern Metrics to Land-Cover Misclassification and Differences in Land-Cover Composition
James D. Wickham, Robert V. O'Neill, Kurt H. Riitters, Timothy G. Wade, and K. Bruce Jones

Abstract
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Calculation of landscape metrics from land-cover data is becoming increasingly common. Some studies have shown that these measurements are sensitive to differences in land-cover composition, but none are known to have tested also their sensitivity to land-cover misclassification. An error simulation model was written to test the sensitivity of selected landscape pattern metrics to misclassification, and regression analysis was used to determine if these metrics were significantly related to differences in land-cover composition. Comparison of sensitivity and regression results suggests that differences in land-cover composition need to be about 5% greater than the misclassification rate to be confident that differences in landscape metrics are not due to misclassification.

403-414 Evaluating the Uncertainty of Area Estimates Derived from Fuzzy Land-Cover Classification
Frank Canters

Abstract
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The use of remotely sensed data as input into geographical information systems has promoted new interest in issues related to the accuracy of multispectral classification. This paper investigates the impact of classification uncertainty on the estimation of area from satellite derived land-cover data. Applying four variants of the maximum-likelihood classifier, it is shown that the estimated area for different land-cover classes is highly influenced by the methods which are used for classifier training. To evaluate the uncertainty of area estimates, a new error modeling strategy is proposed. Assuming that attribute uncertainty in image classification is field- based rather than pixel-based, the image is segmented in fields according to similarities in the probability vectors of adjacent pixels. In simulating uncertainty, this field structure is explicitly taken into account. Using different strategies for image segmentation, it is shown that the spatial correlation of classification uncertainty has a major impact on the assessment of the uncertainty of area estimates.

415-424 Effect of Database Errors on Intervisibility Estimation
Ronald E. Huss and Mark A. Pumar

Abstract
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One of the most common uses of digital terrain databases is in the evaluation of intervisibility, or clear line of sight, between points in space. These evaluations are often used to make decisions regarding deployment of equipment or personnel. However, there will be errors or discrepancies between the database and the true terrain, and, because of these discrepancies, the visibility in the field will differ from that predicted using the database. This paper describes a method for calculating the probability of visibility over an area for a given error specification. Results are described showing the sensitivity of visibility uncertainty to database error and terrain roughness. Sensitivity to other parameters is discussed. The results show that databases are very good for predicting masking but are less reliable for predicting visibility. Also, the reliability of the visibility predictions increases with increasing terrain roughness. 

425-434 Exploring and Evaluating the Consequences of Vector-to-Raster and Raster-to-Vector Conversion
Russell G. Congalton

Abstract
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Spatial data can be represented in two formats, raster (grid cell) or vector (polygon). It is inevitable that conversion of the data between these two formats be essential to the best use of the data. Most geographic information systems (GIS) now provide software for such a conversion. The objective of this study was to explore and evaluate the consequences of data conversion on the accuracy of the resulting data layer. Simple shapes were chosen to document the results of the raster-to- vector and vector-to-raster conversion processes. These shapes included a square, a triangle (not aligned with the grid), a circle, a hole within the circle, and a non-convex shape. Error matrices were employed to represent the changes in area through the conversion process. A second set of data including a circle, a thin rectangle, and a wide rectangle were used to examine the effect of grid cell size on both presence/absence of a feature as well as to maintain the feature's shape. Finally, recommendations for continuing this work and its application to information derived from remotely sensed data were presented.
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