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Table 1. Comparison of Early Systems —————————————————— ORRHIS The Oak Ridge Modeling Information System PIOS The Polygon Information Overlay System LOIR The New York Land Use and Natural Resource Information System CGIS The Canada Geographic Information System ^S. SYSTBt PROCESS ^X. 1972 1971 MLMIS The Minnesota Land Management Information System ———————————————————— 1969 1967 1964 pate Initiated flying spot scanner small grid manual manual ! digitizer large grid medium grid polygon Basic Technology Data Capture drum scanner Encoding fine polygon .polygon, linear, and point data from source map are transferred to a mylar, category by category, and the mylar is photographed each step scan to detect darkened areas, each darkening representing a category Graphic Data Pre-processing polygons and classi fications drawn on stable base mylar none air photo interpret. compile on quad maps scribe polygon boundaries. number polygons and mark centers U) K) digitize polygon boundaries mark sense card manual coding to OTM (1 km2 ) grid and keypunch scan for presence of line segment, digitize polygon centers Data Capture Techniques none none vectorization of bits indicating presence of lines or boundaries between areas vector; polygon, distancedirection notation Sncoded Data Data Deduction reduction of sum cells to 3.75 second or larger grids sliver and gap removal geodetic hierarchal grid, predominant or percentage quick look plots vector, polygon chain of x, y coordinates grid, predominant use grid, percentages of each grid in par ticular land uses Mode delete, change, rotate, shift polygons redundant interpreta tion, machine echo plot of coding sample field check gap and spike removal, edge matching Editing
could be assigned to each 40-acre grid. The LUNR system employed 130 land use categories for larger, 1 km^ (247 acres), grids. Consequently, pre dominant assignment of land use to grids was inappro priate and the amount or area of land uses in each grid was encoded. This disparity between attribute resolution and spatial resolution results in a loss of information because the land use detail inherent in a detailed classification is lost when aggregated to a 1 km grid. This loss takes a form where one can not determine where within a grid unit the different uses occur and how they are related spatially. ORRMIS utilized both a hierarchy of categories for land use and a hierarchy of geodetic grid cells. A grid cell size of 7V is used in conjunction with nine categories of land use, 2V grid cell size with 46 categories, and 30' grid cell size corresponds to 235 categories. If the technology employed captures a large part of the graphic content of maps or photos, there is an associa ted and large problem of data reduction, editing, ag gregation and formatting. On the other hand pre processing of map data and/or abstracting (or recording only part of the map content, say by imposing a large grid) simplifies the amount of reducing or processing of encoded data to develop formatted data for use. CGIS is an example of a system which requires pre processing of map data because of strict input require ments, considerable data reduction software, and severe editing requirements to insure quality data. PIOS re quires considerably less pre-processing and data reduc tion, although the edit requirements are again severe, so severe that strict polygon systems (those that main tain vector data throughout overlay) are rarely used now. MLMIS and LUNR require little pre-processing, reduction, or editing because of the level of abstrac tion inherent in those systems; they are for coarse level inventories of large regions. ORRMIS, like CGIS, requires considerable pre-processing to prepare for scanning and data reduction to translate an extremely fine mesh of scan line cells to the geodetic grids. Another complication of the ORRMIS is the merging of separate scan data, a separate scan for each land use category, into a single data set containing all land uses. The ORRMIS data capture technology works well 333
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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
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separately. There are also five of
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graphic, chart base, and labels may
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Introduction GEOMODEL - INTEGRATED
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ace, income, miles of bus-lines, or
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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 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: ture, encode, reduce, edit, format,
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
Page 379 and 380: input space into a set of 8 x 8 sub
Page 381 and 382: esolution of the system and the num
Page 383 and 384: impractical to use this terminal fo
Page 385 and 386: and heat from power plants into wat
Page 387 and 388: The present and future Low-resoluti
Page 389 and 390: Development of GIMMAP at the Kansas
Page 391 and 392: The second area of development is a
Page 393 and 394: GROUP Fig. 1
Page 395 and 396: MOVING INTERACTIVE THEMATIC MAPPING
Page 397 and 398: 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
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
Page 487 and 488:
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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