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1: 250000 BASIS BAY AREA SPATIAL INFORMATION SYSTEM FIGURE 1 - Plot of coastal features in a portion of the area covered by BASIS, shown at four different scales (original plot has been photographically reduced so scales are no longer correct). 248
data is relatively simple. Problems arise with size, however: a combination of factors such as a large region, small cells, and many data types lead to large storage requirements. Storing up to eighty separate data items for each of two million grid cells - and being able to quickly access any one of those cells - is a considerable task on any size computer system. It is made even more difficult on a small system with limitations in memory size, disk capacity, and I/O speed. Operating a large geographic data base on a relatively small computer system, then, requires considerable attention to the design of data management structure. Design of the structure for BASIS had, as a major objective, on-line access to the entire data base. This type of access is essential for efficient updating and editing. Also, access to only part of the data base (some data types for the entire region or all data for a part of the region) would be inadequate for many applicat ions. Two major elements in the structure of a grid cell data management system are the location of the data for any specified ground location and the arrangement of the data base on some mass storage mechanism such as a disk. The BASIS approach to this problem of data management relies on two key concepts: direct access to data grouped by kilometer cell, and bit plane coding. Direct access techniques The first concept deals with the relationship of data space and "ground" space; that is, how to establish the correspondence between a given location on the earth (a defined grid cell) and the space on the disk (file name and record number) where data concerning that location on earth is stored. This correspondence is, of course, fundamental to any geoprocessing system. The linkage should, if possible, support direct access; that is, the data for a cell anywhere in the region should be accessible without having to search. This relationship is established in BASIS by using a lookup table, which is arranged so that table position corresponds directly to ground position (e.g., the location of the data for the cell at Row 126, Column 249
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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
Page 213 and 214: AUTOMATED MAPPING AND FACILITIES MA
Page 215 and 216: turned out to be a boon for automat
Page 217 and 218: As an example, one utility had five
Page 219 and 220: suburb of Denver, is a group of eng
Page 221 and 222: Introduction CADAE * (COMPUTER AIDE
Page 223 and 224: using CADAE, but the convenience an
Page 225 and 226: fractions of an inch to 1/64 or in
Page 227 and 228: Now that the viability of CADAE has
Page 229 and 230: "LANDFORM" LAND ANALYSIS AND DISPLA
Page 231 and 232: (2) Information Display (3) Design
Page 233 and 234: scales, and perspective views can b
Page 235 and 236: ENGINEERING APPLICATIONS OF DIGITAL
Page 237 and 238: Once the Map Grids are complete, th
Page 239 and 240: TOPOLOGICAL MODELS FOR ARCHITECTURA
Page 241 and 242: dimension, may be oriented in two w
Page 243 and 244: 1-cells, and the 0-cells on the bou
Page 245 and 246: IX. One and two-dimensional structu
Page 247 and 248: looking from c^ to c9 near side far
Page 249 and 250: Figure 4 File Layout for Model of a
Page 251 and 252: DATA BASES, SMALL SYSTEMS There wer
Page 253 and 254: The consistency requirements are se
Page 255 and 256: A 0-cell is A 1-cell is a A 2-cell
Page 257 and 258: is a 2-ditnensional surface, and pr
Page 259 and 260: Our Algorithm From the topological
Page 261 and 262: (a) graph \ (b) disk: node 5 lO (c)
Page 263: as earthquake damage assessment, lo
Page 267 and 268: In theory, the structure of such a
Page 269 and 270: BASIS resides on a minicomputer ope
Page 271 and 272: DATA BASES, LARGE SYSTEMS SESSIONS
Page 273 and 274: Robert Haralick and Linda Shapiro o
Page 275 and 276: COMPUTER-ASSISTED ENVIRONMENTAL DAT
Page 277 and 278: System (GRIDS) and Calma Mapping Sy
Page 279 and 280: Results Space does not permit the r
Page 281 and 282: encoded data appear to be very sign
Page 283 and 284: NATIONAL OCEAN SURVEY—AUTOMATED I
Page 285 and 286: 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
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For each type of spatial data struc
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The following questions are possibl
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4. Freeman, H., "Computer Processin
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also be generalized to remove exces
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Figure I. On the left, a map of zon
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The other important role the error
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REFERENCES Corbett, J. (1975). "Top
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The fundamental building block of a
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discussed previously are of the COD
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[2] Bonczek, R. H.; Holsapple, C. W
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REFERENCE BASE REFERENCE LINES NAP
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Polygon data, in contrast, results
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An alternative to grid resampling i
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Should this table already contain a
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Murray, F. W. (1968) A_ Method of O
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ships between units, and thereby fe
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ture, encode, reduce, edit, format,
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could be assigned to each 40-acre g
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more on chain encoding rather than
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RIDS-CURRENT TECHNOLOGY IN RESOURCE
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The RID system is designed to overl
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Data Input Once the relevant data h
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Data Manipulation Timber Contour Cu
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THE DEVELOPMENT OF A NATIONAL SMALL
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III. The National Small-Scale Data
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cally-structured data base is under
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Appendix A: HAWAII: Hydrography U>
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INTERACTIVE CARTOGRAPHY, SMALL SYST
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options but it also extends our res
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sis techniques) information not pre
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media forming input to the system i
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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
Page 455 and 456:
John Durkin Suiranagraphics 35 Bren
Page 457 and 458:
E. Porrest A-E-C Automation Newslet
Page 459 and 460:
Barry J. Glick Middlebury College M
Page 461 and 462:
Jim Hargis M & S Computing Co. 14 I
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Howard C. Hopps Dept. of Pathology
Page 465 and 466:
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
Page 471 and 472:
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
Page 481 and 482:
Craig L. Shafer NFS 18 & C Street,
Page 483 and 484:
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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