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distribution). If the thresholds are exceeded, then an expert system might be used to decide on one or some of the factors that can be altered to reduce the threshold. These various alternatives include the reduction of symbol size and/or base data, and generalisation. CONCLUSION A human cartographer must first be able to identify conflicts in map design, and have at his disposal methods of resolving those conflicts. An essential prerequisite for a cartographic expert system must be equivalent methods for identifying and resolving spatial conflicts. It is apparent that the solution to any spatial conflict involves first identifying the amount and types of data that lie in the immediate vicinity. Methods for efficiently searching the database for conflicts will depend on the format of the database. Only once the components of the conflicts have been identified can an optimum choice be made from the 'possible solutions' (see Figure 1). The approach outlined in this paper differs from other attempts to automate map design in that it views the problem of map complexity as a whole, not as a set of sequential design stages. No cartographer makes a map by selecting the data, symbolising, placing, adding text and finally drawing the key; rather they modify their decisions during the design, both at the global level (in deciding the maximum acceptable information content) and at a local level (where information is obscured because it is clustered together). If expert systems are to draw maps (and not just technical drawings) then they must have the equivalent cartographic senses; eyes with which to discern, knowledge with which to make decisions, and an inference system that enables it to change decisions during the design phase. If a quantitative model can be developed that can optimally resolve clusters of points, it should be feasible to extend the method to include the similar types of problems found in line labelling and text placement situations. Further research is required specifically to algorithmically determine the degree of contiguity between lines (the amount of overlap), and calculate a value for the degree of enclosure. Alternative methods for resolving worst case clusters must also be identified (see figure 6). REFERENCES Barr, A. and Feigenbaum, E.A. 1982. The Handbook of Artificial Intelligence, 3 Volumes. London, Pitman. Green, N.P., Finch, S., and Wiggins, J. 1985. 'State of the Art in Geographical Information Systems' Area 17(4) pp295-301. Mackaness.W.A., Fisher,P.F., and Wilkinson.G.G. 1985. The Design of a_ Cartographic Expert System Final report to NERC Contract F3/G6/304 Matsuyama, T., Hao, L.V. and Nagao, M. 1984. 'A file organisation for Geographic Information Systems Based on Spatial Proximity' Computer Vision Graphic and Image Processing 26 (3). pp303-318 Mather, P.M. 1976. Computational Methods of Multivariate Analysis in Physical Geography London: John Wiley. 717
Monmonier, M.S. 1984. Geographic information and cartography. Progress in Human Geography 8, 381-391. Morrison, J.L. 1980. Systematizing the role of "feedback" from the map percipient to the cartographer in cartographic communication models Paper read to the International Cartographic Association, Tokyo. Page, E.S. and Wilson, L.B. 1978. Information Representation and Manipulation in a Computer 2nd edition. Cambridge University Press. Peuquet D.J. 1984. 'Data Structures for a Knowledge Based Geographic Information System' <strong>Proceedings</strong> Of The International Symposium On Spatial Data Handling Aug 20-241984 Zurich,Switzerland Vol 17 PP372-391. Smith, T.R., and Pazner, M. 1984. 'Knowledge Based Control of Search and Learning in a large scale GIS' <strong>Proceedings</strong> Of The International Symposium On Spatial Data Handling Aug 20-24 1984 Zurich, Switzerland Vol 2, pp498-519. 718
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Proceedings Eighth International Sy
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1987 by the American Society for Ph
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A NOTE ON THE FUTURE OF AUTO-CARTO
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Algorithms for spatial search or qu
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Research into electronic maps and a
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Sandhu, Jatinder 403 Shea, K. Stuar
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integration of the findings on tech
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departments of municipalities are p
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systems, similar cost reduction in
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exist here: it is rarely possible t
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REFERENCES Chris man, N. and Nieman
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THE USER PROFILE FOR DIGITAL CARTOG
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second is to reduce all lines to a
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OVERLAY PROCESSING IN SPATIAL INFOR
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digital terrain models, or magnetic
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(2-dimensional) or volumes (3-dimen
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whereas the lattice induced by spat
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5.2 Overlay Operation One of the mo
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permit the determination of the len
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more about the quality of the avail
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of the user interface and would res
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FUNDAMENTAL PRINCIPLES OF GEOGRAPHI
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of continuous space (the model of A
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look like is transmitted through th
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(Sullivan and others, 1985). On the
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PRESCRIPTIONS To carry out the prin
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AN ADAPTIVE METHODOLOGY FOR AUTOMAT
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They reorganize available space and
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Global Filtering Basics: This filte
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If the geometry is determined throu
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SYSTEMATIC SELECTION OF VERY IMPORT
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Improvements The first improvement
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RESULTS ANALYSIS There are two test
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Figure 4. A TIN generated from VIP
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only or the most important one. Unt
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terrain surface, may have in corres
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Advantages of determining the Media
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egards points, only the endpoints o
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contours some measures of size and
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MEASURING THE DIMENSION OF SURFACES
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dimension of an entity, is constant
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terrain. In order to avoid a sampli
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APPLICATIONS TO DIGITAL ELEVATION M
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1.20 1.16 • D I M 1.12 E N S 1.06
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Stability of Map Topology and Robus
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The 0-cells in the usual topologica
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Notice in Figure 1 that the interme
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Algorithm for computing robustness
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We may sum the forces by a straight
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and computational algorithms, which
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The geopositioning model presented
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It should be noted that only the fr
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While Voronoi polygons have often b
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additional vector rotation about th
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inconsistency. The problem stems fr
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Chain Intersection Determining chai
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node(6,[h(l8),t(l9),t(24),h(21)]).
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Sliver Removal. We remove a sliver
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Little, J.J. and Peucker, T.K. 1979
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measured control points. In this pa
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TEST RESULTS For testing the above
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A SPATIAL DECISION SUPPORT SYSTEM F
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data by time period, by category, a
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BASIC version of the PLACE suite re
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procedural language. The classifier
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FIGURE 1: SOFTWARE COMPONENTS FOR S
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Realistic Flow Analysis Using a Sim
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TIN FORMAT VS. MATRIX FORMAT The pr
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One of the major challenges involve
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Because TINFLOW is a PC-based GIS,
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Art; I DitH ot twin 1.1610 Strew He
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RATIONALE Gridded surface data sets
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5. For each polygon, for each cell
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A mapping function was used to topo
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CONCLUSIONS This depression-finding
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Methods For spatial analusis The tw
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1. Sampling to determine the sample
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A simcle multiscale model . Instead
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Complex multiscale models. The one-
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Mandelbrot, B.B., 198E. The Fractal
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A number of authors have proved the
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Once having the Fourier-transf arm
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From the above listed aspects (2) i
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A considerably large number of labo
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Oliver,M.A., R.Webster (1936) Semi-
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model can be used as the basis for
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ts phase space by analogy to phase
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Figure 3. Classified 64 by 64 raste
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in the delimitation of domains in p
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Mark, D.M. and Aronson, P.B. 1984,
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To make decisions about this world,
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Limitations inherent to the modeliz
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operations delimiting rights to the
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Uncertainty absorption is very diff
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Minsky, M. L. 1965, Matter, Minds,
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data, covering extremely large area
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Figure 1. a) Test data set with, tr
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Figure 2. Four pyramids - line segm
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convenient to consider grids to be
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REFERENCES Davis, J.C., 1973, Stati
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the data element, in this case an a
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EXPERIENCE WITH R-TREES IN A CIS LA
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REFERENCES Guttman, A. 1984, R-Tree
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World Shoreline Vectors Shoreline v
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Table 4. Applications of gridded el
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classes desired for a given applica
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Table 6. The impact of block size o
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Jones, Christopher B. and Abraham,
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DISADVANTAGES OF A SINGLE COVERAGE
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faster and less complex than genera
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NOS detailed source data 20 meter r
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si '- /W^ ?f ? ( " ( I?
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REFERENCES Aronson P. and Morehouse
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with the purpose of optimizing geom
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purposes, the value 1/e may be thou
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V describing points/ / y/ B / /•*
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clarity, the number of describing p
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ACKNOWLEDGMENTS The author wishes t
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INTRODUCTION In any application of
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7T 0 — 7T X Hay River Figure 1: A
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0 — 7T Alluvial fan contour Figur
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Peucker, 1973) can be used here; th
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Mark, D. M., 1985, Fundamental spat
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•©—e—©—e- Figure 1.1: Spl
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SLAU- 9/1000 Figure 1.5: Results of
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t-0 I.I 7.4 /.6 1.8 2.0 Figure 2.1:
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THE TIGER STRUCTURE Christine Kinne
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to another tail record. There are f
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Since records are fixed length, a n
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areal data is stored, but additiona
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KEY TO SUBFILE ABBREVIATIONS (CONTI
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TOPOLOGICAL ENTITIES Corbett's topo
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TOPOLOGICAL RULES The preceding def
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File and the new linear feature ref
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Encoding and Referencing (TIGER) Sy
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of the boundary are found and corre
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CONCLUSION The GTUB routines have b
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SELECTION OF EQUIPMENT The least ef
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operations. The site and staff for
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RESULTS Table one shows the numeric
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would no longer have to determine a
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THE DATA BASE ADVANTAGE Most of the
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SUMMARY AND CONCLUSIONS The major d
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the complexity o-f I/O processing.
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is on one and only one topological
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•features represented in the data
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intersection is -found -for this -f
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An easy implementation o-f spatial
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organisations most precious asset -
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no reason why we should not model t
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- A VERTEX identifies a unique spat
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to the organisation and indexing of
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the retrieval of data from the disp
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original goals, through design, and
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Contents and Queries Each geographi
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number of tables required. On the o
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generic, db-internal read/write/del
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we are guaranteed that each occurre
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The db bottlenecks we found were, f
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Bibliography [1] Date, C.J. 1983 -
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model is an object-oriented extensi
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SPECIALIZATIONS FOR SPATIAL DATA Th
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for each x in S, for each y in S if
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entity IMAGE PIXELS(IMAGE) - set of
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Orenstem, J.A. 1984, "A Class of Da
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understand the data model on which
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Internally, KGIS is implemented on
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AREA > 10; Spatial relationships be
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Once established, a GEOVIEW remains
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___________, 1985, THE USE OF SPATI
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• the cross sections, profiles an
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• Rigid and homogeneous ores can
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Borehole data \ Geologist's ^^ know
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Figure 3 : A Portion of the Ore Bod
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REFERENCES Baumgart, E.G. (1975) -
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This paper is organized into five s
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yields the resulting table: Poly* 1
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tightly bound to the map; there is
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A partial example of the relational
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REFERENCES Chrisman N. and Niemann,
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GEOGRAPHIC DATABASE TOPOLOGY SPATIA
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of a coordinate in n-space, usually
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Airport refines Aviation; — This
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THE dbmap SYSTEM Donald F. Cooke Ge
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procedurally, like Pascal, FORTRAN
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een lassoed (and line-segments in o
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Figure 4 Result of Lasso Operation
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The goal of a DSS is to help decisi
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chosen structure must provide a mea
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First, a general schema diagram is
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Hopkins, L.D., and Armstrong, M.P.
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******* DATABASE IDENTIFICATION AND
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Because of these limitations, furth
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cannot share the data. A minicomput
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Historically the whole orientation
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To reach the stated goal of this pa
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mapping techniques conceptualized a
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The future skill level, and trainin
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€6€ COMPUTER SCIENTIST ELECTRIC
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U* '^ OUTPUT \ / REVIEWIM. CORRECTI
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We may conceptually divide a VNA in
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most interest for transmitting navi
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necessary) in such a display. This
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ENHANCEMENT AND TESTING OF A MICROC
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make maximum use of the limited, lo
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I Text Display Window (Toggle On/Of
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as well, using the PLINK86 Plus ove
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AN INTEGRATED PC BASED CIS FOR INST
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RAW DATA INPUT DATA BASE MAPh ANALY
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Figure 3. Example of output from SH
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Figure 8. CONTOUR of elevation on v
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Figure 11. COLOR map on printer of
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IDRISI : A COLLECTIVE GEOGRAPHIC AN
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felt to be negligible compared to t
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Although the IDRISI system was prim
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data file, and a second backwards t
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TABLE 1 : IDRISI PROGRAM MODULES IN
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CLASSLESS CHOROPLETH MAPPING WITH M
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polygon. The process of selecting s
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There are a number of places where
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COMPUTER-ASSISTED TERRAIN ANALYSIS
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2. Input. A digitizing tablet to al
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terrain analysis data. Items 3. and
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Database Structure Currently, DMA-p
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RESULTS OF THE DANE COUNTY LAND REC
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E. G.
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section maps of tax parcels maintai
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Public Land Survey System (PLSS) co
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Sheets, Proc. ACSM, 1:153-161. Chri
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von Meyer, N.R. 1984b. Westport Ine
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While meeting the above criteria pr
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oundary line. An example of the sam
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Four groups of approximately thirty
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LEGEND MULTIPLE BOUNDARIES STATE, C
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TABLE 2 shows that more respondents
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What features are considered when d
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position is insignificant. Thus, th
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ASSESSING COMMUNITY VULNERABILITY T
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Yale University was selected for st
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distribution of hazardous materials
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»++ 0000000001000OCCCOOOOOOCOOOOCO
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44* 444 444 ICO 9 CO 9CO to CO ECO
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IMPROVEMENT OF GBF/DIME FILE COORDI
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Establishment of Control Points In
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transformation parameters for a par
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of using a fixed set of transformat
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vertex coordinates into exact corre
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Friedman, J., Baskett, F. and Shust
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and small freehold land. It does no
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The next step in the planning proce
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TSO on UNB's IBM 3090 mainframe com
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3. Kettela, E.G. 1975. Aerial spray
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The integration of developing techn
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and photographic processes are used
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Figure 4 EXAMPLE OF PUBLISHED FIRM
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EXAMPLE OF COMPUTER-GENERATED FIRM
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BIBLIOGRAPHY Federal Emergency Mana
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more detailed introduction to exper
Page 524 and 525:
MAPEX is a rule-based system for au
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discrimination nets, Click et al (1
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example, FES (Goldberg et al, 1984.
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Pereira, L.M., P. Sabatier, and E.
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e flexible enough to address a wide
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intermediate hypotheses are "posted
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All cited rules become part of the
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The Geographic Information System L
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geographic knowledge system applies
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In view of this it is not suprising
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placement, the main area of cartogr
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EXPERT SYSTEM INTERFACE TO A GEOGRA
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ASPENEX automates the analysis of s
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Rule-Base Creation SYSTEM OPERATION
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the rulebase created by the aspen e
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AUTOMOBILE NAVIGATION IN THE PAST E
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oadside equipment to provide equipp
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algorithm and provides step-by-step
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DRIVER INPUTS • DESTINA1ION • R
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Vehicular Technology Conference, 35
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Map retrieval is also crucial to na
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elative coordinate accuracy is very
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destination does not require knowin
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PRESENTATION The extremes of styles
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REFERENCES Ashkenazi, V. 1986, Coor
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decision-making, learning, and natu
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that these travellers felt that wri
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e weak, if present at all. Since ma
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Figure 2: An example of a distorted
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directions were produced in real ti
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Figure 1. Concept of an Automatic V
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AVL COMPONENTS AND THEIR FUNCTIONS
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OUTPUT FACILITIES V7MIC1Z «IflT KA
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need extensive customizing. This cu
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PRACTICAL EXPERIENCE WITH AVL 2000
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ACKNOWLEDGEMENT This research has b
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separate AVL system is needed (spec
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Sources Two plausible sources of a
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o t=z ATTRIBUTE RELATIONSHIP ENTITY
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(a) optimal route between the pair
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REFERENCES Cooke, D.F., Vehicle Nav
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THE BBC DOMESDAY SYSTEM: A NATION-W
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which are not commonplace: it permi
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Geochenrstrj Climate VNater fiature
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(ii) measure area and distance in m
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Rhind D.W. and Mounsey H.M. (1986).
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language expression. One of the mot
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This process begins from a position
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E(l(k)) be the expectation of I ( k
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There are several approaches to con
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In this paper we will discuss preml
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Table 2. Length of Sessions and The
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Table 5. Fuzzy Membership Values fo
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Table 7. Results of Zimraermann's M
Page 632 and 633:
Chamberlain, D.D. and R.F. Boyce. 1
Page 634 and 635:
ACCESSING LARGE SPATIAL DATA BASES
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WORKSTATION #2 1 - IBM-AT; 640K, 20
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RECORD 1 —— coordinates 1-256 f
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Future developments include the pol
Page 642 and 643:
Once features of two coverages have
Page 644 and 645:
Figure 3a Partial street network co
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Figure 3e Coverages aligned with 50
Page 648 and 649:
Solving the Feature Matching Proble
Page 650 and 651:
References Chen, Z. and A. Guevara,
Page 652 and 653:
determined that a conversion of dra
Page 654 and 655:
PAT GRP NUM 1 2 3 4 5 6 7 8 9 10 11
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various raster and vector operation
Page 658 and 659:
Figure 4a - Portion of scan-digitiz
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the set of points. This will introd
Page 662 and 663:
which represents the terrain by a t
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leaf for 4 and 5). Chen and Tobler
Page 666 and 667:
fixed polynomial order for each run
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RESULTS As noted above, the program
Page 670 and 671:
REFERENCES Chen, Z.-T., and Tobler,
Page 672 and 673:
Shortcomings in Existing Raster-to-
Page 674 and 675:
Template design parameters are base
Page 676 and 677:
RESULTS REPORT type RESULTS REPORT
Page 678 and 679: Significance of the AFT Technology
Page 680 and 681: REFERENCES Antell, R.E. (1983), "Th
Page 682 and 683: Grid systems do not permit vertical
Page 684 and 685: SCHEMA structures an urban model ar
Page 686 and 687: The second data structure regards t
Page 688 and 689: The resulting polygon "hole" is the
Page 690 and 691: REFERENCES Brassel, Kurt E., and Do
Page 692 and 693: The link between these two bodies o
Page 694 and 695: The same technique of Fourier analy
Page 696 and 697: The similarities between this and t
Page 698 and 699: In many respects, a terrain model c
Page 700 and 701: AN ALGORITHM FOR LOCATING , CANDIDA
Page 702 and 703: The left and right boundaries of a
Page 704 and 705: limits. The overall problem of gene
Page 706 and 707: To find the cluster limits, the sim
Page 708 and 709: next box. The entry (m = s) is ther
Page 710 and 711: Figure 3.-Portion of test data set
Page 712 and 713: PRACTICAL EXPERIENCE WITH A MAP LAB
Page 714 and 715: £ X lfk = 1 k=1,2,...,K. (1) i If
Page 716 and 717: Deleted Labels The optimization alg
Page 718 and 719: Figure 2. Point Symbol Labels With
Page 720 and 721: AUTOMATIC RECOGNITION AND RESOLUTIO
Page 722 and 723: FUNCTION REQUIRED l)ls a point on a
Page 724 and 725: distance by finding the square root
Page 726 and 727: Proportional Radial Enlargement As
Page 730 and 731: CALCULATING BISECTOR SKELETONS USIN
Page 732 and 733: Thiessen centroid than to any other
Page 734 and 735: there are exactlv n boundary skelet
Page 736 and 737: AREA MATCHING IN RASTER MODE UPDATI
Page 738 and 739: THE AREA MATCHING PROCESS This proc
Page 740 and 741: defaults are made of very short seg
Page 742 and 743: POLYGONIZATION AND TOPOLOGICAL EDIT
Page 744 and 745: If no label exists between the chai
Page 746 and 747: these internal (non-boundary) chain
Page 748 and 749: However, a cartographic database ne
Page 750 and 751: "WYSIWYG" MAP DIGITIZING: REAL TIME
Page 752 and 753: with tolerance circles such that it
Page 754 and 755: CONCLUSION For many years a major i
Page 756 and 757: implementation methodology and the
Page 758 and 759: SPLIT SCREEN o o oo SIDE BY SIDE o
Page 760 and 761: determined applicability aided by s
Page 762 and 763: the 384 LPI resolution patch used t
Page 764 and 765: TESTING A PROTOTYPE SPATIAL DATA EX
Page 766 and 767: 2. An Overview of MAPS The MAPS spa
Page 768 and 769: containment tree can be used to eff
Page 770 and 771: ROLE: BUILDING UNKNOWN MEDICAL CENT
Page 772 and 773: and the segment direction within ea
Page 774: seg : nodes: points south west: 20.
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