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cells. The third and final task is to assemble boundary segments into a polygonal representation. This involves identifying all polygons formed, smoothing or filtering borders, and ensuring that each polygon has proper closure in the face of boundary and resolution constraints. Cell Classification versus Contour Interpolation Two basic strategies are available for converting grids to polygons. In cell classification, each cell is assigned to a class based on its value. This classified matrix is then scanned and a border generated whenever a cell's value differs from a neighbor's. In this method, all elevation class boundaries follow cell borders. Fig. 1: (a) Cells Classified; (b) Edges Smoothed; (c) Interpolated Contours This technique is satisfactory when the spatial resolution of the grid is fine enough. 'Staircase' lines resulting from following cell borders can then be smoothed. When the spatial resolution of the grid is poor, additional height values can be interpolated within each cell. These heights can be used to locate borders with finer resolution than the original cell possessed. This interpolation may involve resampling the grid with finer resolution, using a distance weighted average to interpolate values for the new cells. This new matrix can then be classified and processed. 322
An alternative to grid resampling is to interpolate the position of borders within the original cells. As grids tend to be large (and redundant) , resampling adds further bulk (hence processing effort) to the data. By allowing contours to pass through cells, smooth borders can be produced without resampling. _A Conversion Algorithm Many algorithms for generating contours exist (see, for example, Calcomp 1968; Dayhoff, 1968; Murray, 1968; Coulthard, 1969). Most existing algorithms follow contours throughout a data grid (or randomly accessable subsets of a data grid). While this directly produces the desired result — contour lines in the form of strings of coordinates — random access memory requirenments may be burdensome. As contour lines may start and end anywhere in the grid, large sections of the grid must be available for processing in random access memory for the contour following approach to be efficient. Since all cells of the grid must be scanned for possible contours anyway, it seems sensible to minimize random access memory requirements by separating the segment generation process from the segment linking process. With such a strategy, each process can be performed using sequential scans of the data . The conversion algorithm has two principle steps — contouring and structuring. In the first step, the data grid is scanned and processed to generate a contour segment file. For each segment, the elevation class on the left and right sides of the segment are recorded as well as the endpoints of the segment. In the second step, structuring, the segment file is processed to generate a polygon boundary file. This involves linking together segments to form borders and identifying the polygons thus created. Contouring Phase Contour segments are generated on a row by row basis using the grid values in the current row and the the two ajacent rows, within each row, each cell is processed independently to locate and output contour segments. All such segments which fall in the cell will be identified before passing on to the cell in the next column. Segments are derived by decomposing the rectangular cell into eight triangles: 323
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'/1UTO QIRTO IV Proceedings of the
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SPONSORED BY: Proceedings of the Vo
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FOREWORD This is the fourth confere
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PREFACE The technical articles cont
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The Use of Computer Generated Maps
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Interactive Computer Mapping ......
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A Formal Model of a Cartographic In
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PHOTOGRAMMETRY SESSIONS Introductio
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William 0. Lucoff of Cal. State at
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widths may be varied at random from
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command codes to the minicomputer a
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Figure 2 Computer Controller EXPOSU
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— 1 X 0 u_ ABCDE M X ^ ^j to C£
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Figure 12 Portion of 48"X60" Chart
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3. THE GAS SYSTEM Chicago Aerial Su
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mode and guides the operator throug
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Figure 1 - Input Edit Figure 2 - Li
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Figure 7 - illegal Elevations Figur
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L Figure 11-Matching Between Models
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1. Street trees are defined as any
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exists between the calculated data
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Trom a conversation with Robert Lee
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II. The Alternatives Various conven
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With error correction as the final
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1. Introduction PRACTICAL EXPERIENC
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instruments with digital mapping te
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the patterns and stores the digital
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o Provides the capability to conver
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II.System Description Figure 1 is a
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Status signals are located on the m
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which have been digitized and recor
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Figure 4 Digitized/Recorded Image C
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IMAGE PROCESSING The Image Processi
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II. Background The work reported in
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coordinates from topographic maps.
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polation techniques are available i
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egistrations. In all areas where re
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THE INTERACTIVE IMAGE SYSTEM FOR TH
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The operator may type in commands w
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input, each request being terminate
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The language elements invoke indepe
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IMAGE PROCESSING AND NAVIGATION FOR
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4. Image Acquisition and Amplitude
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disc); - the satellite spin-speed w
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line start. These parameters are se
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PRACTICAL APPLICATIONS FOR DIGITAL
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need for early warning of impending
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In order to manipulate classes of f
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depends mainly on the density of fe
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A DATA STRUCTURE FOR A RASTER MAP D
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FIG. 2. A border with indicated max
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pointers associated with the max-po
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y-max 1 z \7 'x-min \x-max 3 x-min
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DIGITAL TERRAIN MODELS SESSIONS Int
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Their programs have been developed
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that the purpose of the digital ter
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equirement for such a program is th
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equivalent to locating the lines of
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Brassel, K.,1974,"A Model of Americ
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It is not the intention of this pap
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One feature in this should be empha
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neighbouring data points to estimat
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Lawson, C.L., 1977. Software for C-
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EDIT SYSTEM HARDWARE The IPIN Edit
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Each edit terminal will also contai
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FIGURE 2. PLOT OF GEOMORPHIC DATA 1
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a 0° 0 0 + 0 o 0 FIGURE 4. SELECTE
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FIGURE 5. CONTOUR PLOT OF INTERPOLA
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absorbed in the merger if the diffe
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To an every-increasing degree, the
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potential storage volumes of depres
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Soil type sand, Vegetation trees -^
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References Brnjac, M; Carlsen, L; M
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is particularly important to allow
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(b) If Z-coordinate of the vertex B
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Figure 3a. TIN DTM Projection Figur
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URBAN MAPPING SESSIONS Introduction
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Norfolk, and Hampton Virginia. Part
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MAPPING SERVICES IN FAIRFAX COUNTY,
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If errors are detected they are res
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Some are only printed as the stocks
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URBAN MAPPING AND RELATED AUTOMATED
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tersection matching program was wri
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The selection of coding schemes wil
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cartography and are firmly committe
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main purpose of this paper. Five of
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The project was undertaken specific
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play and analysis. By breaking from
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The operating system environment is
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INTERACTIVE COMPUTER MAPPING* Thoma
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- By displaying variables in map fo
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with a start - head- and an end -ta
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Rovner, P.D and Feldman, J.A., 1968
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eading this complex type of map, (2
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y a law pertaining to persons 65 an
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So far the analysis has been concer
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enta separation to the family age g
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Mortality maps have been widely use
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1970 population values, growth rate
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CANCER MORTALITY BY CENSUS TRACT 19
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References Burbank, F., Epidemiolog
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Computer graphics is changing all t
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time to define the uses to which th
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tually complete - we had a meeting
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EXPLORATION AND UTILITY SYSTEMS SES
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AUTOMATED MAPPING AND FACILITIES MA
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turned out to be a boon for automat
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As an example, one utility had five
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suburb of Denver, is a group of eng
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Introduction CADAE * (COMPUTER AIDE
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using CADAE, but the convenience an
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fractions of an inch to 1/64 or in
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Now that the viability of CADAE has
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"LANDFORM" LAND ANALYSIS AND DISPLA
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(2) Information Display (3) Design
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scales, and perspective views can b
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ENGINEERING APPLICATIONS OF DIGITAL
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Once the Map Grids are complete, th
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TOPOLOGICAL MODELS FOR ARCHITECTURA
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dimension, may be oriented in two w
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1-cells, and the 0-cells on the bou
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IX. One and two-dimensional structu
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looking from c^ to c9 near side far
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Figure 4 File Layout for Model of a
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DATA BASES, SMALL SYSTEMS There wer
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The consistency requirements are se
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A 0-cell is A 1-cell is a A 2-cell
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is a 2-ditnensional surface, and pr
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Our Algorithm From the topological
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(a) graph \ (b) disk: node 5 lO (c)
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as earthquake damage assessment, lo
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data is relatively simple. Problems
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In theory, the structure of such a
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BASIS resides on a minicomputer ope
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DATA BASES, LARGE SYSTEMS SESSIONS
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Robert Haralick and Linda Shapiro o
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COMPUTER-ASSISTED ENVIRONMENTAL DAT
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System (GRIDS) and Calma Mapping Sy
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Results Space does not permit the r
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encoded data appear to be very sign
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NATIONAL OCEAN SURVEY—AUTOMATED I
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centered at NOS Headquarters, but r
Page 287 and 288: separately. There are also five of
Page 289 and 290: graphic, chart base, and labels may
Page 291 and 292: Introduction GEOMODEL - INTEGRATED
Page 293 and 294: ace, income, miles of bus-lines, or
Page 295 and 296: phrase pointer Figure Ib. 1-cell Fe
Page 297 and 298: Implementation The development plan
Page 299 and 300: ECQBASE OF BRITAIN: status report o
Page 301 and 302: 1. Coastlines (high water mark) inc
Page 303 and 304: much statistical data, e.g. , from
Page 305 and 306: Figure 1 Scale of digitisation of p
Page 307 and 308: I. Introduction A DATA STRUCTURE FO
Page 309 and 310: One obvious division of the state i
Page 311 and 312: Figure 2 illustrates this structure
Page 313 and 314: Raster or grid form is another form
Page 315 and 316: For each type of spatial data struc
Page 317 and 318: The following questions are possibl
Page 319 and 320: 4. Freeman, H., "Computer Processin
Page 321 and 322: also be generalized to remove exces
Page 323 and 324: Figure I. On the left, a map of zon
Page 325 and 326: The other important role the error
Page 327 and 328: REFERENCES Corbett, J. (1975). "Top
Page 329 and 330: The fundamental building block of a
Page 331 and 332: discussed previously are of the COD
Page 333 and 334: [2] Bonczek, R. H.; Holsapple, C. W
Page 335 and 336: REFERENCE BASE REFERENCE LINES NAP
Page 337: Polygon data, in contrast, results
Page 341 and 342: Should this table already contain a
Page 343 and 344: Murray, F. W. (1968) A_ Method of O
Page 345 and 346: ships between units, and thereby fe
Page 347 and 348: ture, encode, reduce, edit, format,
Page 349 and 350: could be assigned to each 40-acre g
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Page 353 and 354: RIDS-CURRENT TECHNOLOGY IN RESOURCE
Page 355 and 356: The RID system is designed to overl
Page 357 and 358: Data Input Once the relevant data h
Page 359 and 360: Data Manipulation Timber Contour Cu
Page 361 and 362: THE DEVELOPMENT OF A NATIONAL SMALL
Page 363 and 364: III. The National Small-Scale Data
Page 365 and 366: cally-structured data base is under
Page 367 and 368: Appendix A: HAWAII: Hydrography U>
Page 369 and 370: INTERACTIVE CARTOGRAPHY, SMALL SYST
Page 371 and 372: options but it also extends our res
Page 373 and 374: sis techniques) information not pre
Page 375 and 376: media forming input to the system i
Page 377 and 378: D. CIS Data Base Limitations There
Page 379 and 380: input space into a set of 8 x 8 sub
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Page 385 and 386: and heat from power plants into wat
Page 387 and 388: The present and future Low-resoluti
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Development of GIMMAP at the Kansas
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The second area of development is a
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GROUP Fig. 1
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MOVING INTERACTIVE THEMATIC MAPPING
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directives. Both map and data files
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Parameters are commonly of the form
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7. Conclusions In the s:!x months C
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INTERACTIVE CARTOGRAPHY, LARGE SYST
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developed at LBL has been particula
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printed at a common scale and forma
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1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.
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V. Production Sequence The most imp
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1. Introduction MULTIPLE SYSTEM INT
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measurements during map compilation
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Photogrammetric —— > Digitizer/
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intersections. These are a few exam
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Introduction ENERGY ANALYSIS BY MEA
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enabled us to undertake runs consit
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Cost (k $) (D CD M M
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which seek to incorporate powerful
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ELECTRON BEAM RECORDERS FOR AUTOMAT
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data files are supplied as an 8 Bit
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signals representative of map featu
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composite photograph prepared to sh
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Figure 5 16 AAIPS Approach Charts R
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Figure 8 - LANDSAT Image Recorded i
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AUTO-CARTO IV STAFF AND COMMITTEES
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University of Kansas Mike Hogben A'
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Efi Arazi, President Sci-Tex Corp.,
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Peter F. Bermel Chief, Eastern Mapp
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Sherry K. Brown Princeton Universit
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Steven D. Clark Petroleum Informati
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Richard Davis NOAA, NOS 6001 Execut
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John Durkin Suiranagraphics 35 Bren
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E. Porrest A-E-C Automation Newslet
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Barry J. Glick Middlebury College M
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Jim Hargis M & S Computing Co. 14 I
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Howard C. Hopps Dept. of Pathology
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Lee P. Johnston GeoGraphic Decision
Page 467 and 468:
Herbert Kressler Defense Mapping Sc
Page 469 and 470:
D. Richard Lycan Center for Pop. Re
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Robert K. McKinney Weyerhaeuser Co.
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Joel L. Morrison Dept. of Geography
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David Osiecki 83 Gerber Rd. South W
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A.D. Poole Phillips Petroleum Co. 2
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Dirck L. Rotty USDA Forest Service
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Craig L. Shafer NFS 18 & C Street,
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Bobby Staudt M & S Computing 406 Au
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Laure Thompson George Mason Univers
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D.J. Walker Image Graphics 107 Ardm
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Alberta Auringer Wood Chairperson,
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AUTHOR INDEX - VOLUME II Allam, M.
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Schmidt, Warren E. ...............
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