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A FORMAL MODEL OF A CARTOGRAPHIC INFORMATION BASE Introduction Timothy L. Nyerges Department of Geography The Ohio State University Columbus, Ohio 43210 A hierarchical web grammar for a cartographic informa tion base combines a web grammar (graph grammar) intro duced by Pfaltz and Rosenfeld [6] with a phrase struct ure grammar discussed by Youngman [9]. A web grammar is appropriate because of its natural two-dimensional character; and a phrase structure grammar is appropriate because it conveys conceptual notions about internal cartographic structure. The combination of these grammars provide a linguistic formalism for a carto graphic information base. An information base is an extended notion of the data base concept; it integrates conceptual information and program modules into a data base to increase data processing flexibility. Data Base Models The three types of data base models are: hierarchical, network and relational [3;4]. The hierarchical model is a subset of the network type, and can be formulated as if it is a directed network. The relational model has been shown to be relationally equivalent to the network model under certain transformations. That is, when the relational model is inverted so that an attribute, rather than a relation, is a primary key a psuedo- pointer structure is set up. This pointer structure is similar to that in a network model [1;5]. 312
The fundamental building block of a data base is a record type. A record type consists of one or more data items. The data items name actual data in a record occurrence of a given record type. A one-to-many rela tionship defined between two record types is called a set. One of the record types is declared the owner of the set and the other the member. Each record occur rence of the owner record type "owns" zero, one or more record occurrences of the member record type. The schema of a data base consists of data items, record types and set relationships between record types. Actual data is related to the schema through the data item names and record types. The schema, depicted by a graph, is thus a logical description of the actual data occurrences. Two properties of a data base can be characterized by a linguistic model: (a) the structure of the data base and (b) the storage and retrieval capabilities of the data base. It must be emphasized that a grammar derived for a data base does not necessarily describe a data base in a unique manner, but what is important is that it is a formal characterization. Linguistic Models and Data Bases A linguistic model for a hierarchical data base is a context free grammar [1;9], The grammar GH is a triple: GH = (V,I,R), where V is a set of vocabulary elements; I = 1 is an initial symbol; and R is a set of production rules. The set V is composed of two, non-empty, finite, disjoint subsets; VN = {1,2,3,4,5,6 }is the set of non terminal labels denoting record types; and VT is the set of terminal elements representing data. The symbol I initiates a set of productions which generate a schema for a hierarchical data base (See Figure 1). The drawbacks to the hierarchical model are obvious. There is no provision for sharing data elements between records, thus redundancy may occur. The network model ameliorates this problem because it provides for a relationship whereby data can be shared. Consequently, the primary difference between the hierarchical model and the network model is that a member of a set may have only one owner in the hierarchical case, but a member record may have more than one owner record in the network case. 313
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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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Page 279 and 280: Results Space does not permit the r
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Page 283 and 284: NATIONAL OCEAN SURVEY—AUTOMATED I
Page 285 and 286: centered at NOS Headquarters, but r
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Page 291 and 292: Introduction GEOMODEL - INTEGRATED
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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
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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: REFERENCES Corbett, J. (1975). "Top
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 and 338: Polygon data, in contrast, results
Page 339 and 340: An alternative to grid resampling i
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
Page 351 and 352: more on chain encoding rather than
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
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input space into a set of 8 x 8 sub
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esolution of the system and the num
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impractical to use this terminal fo
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and heat from power plants into wat
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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
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Herbert Kressler Defense Mapping Sc
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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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