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terrain analysis data. Items 3. and 4. above constitute Module II of the system which can be modified easily to support DMA supplied digital terrain analysis data when it is defined and avail able. D.M.A. Factor Overlays V__________________J Overlay Video Display , Complex Map Overlays Figure 2: Data Flow through DigiTAS Computer—Aided Design (CAD) System * Digitizing * Editting DigiTAS Data Base Creation Module * Uector to Raster Conversion I DigiTAS Complex Overlay Synthesis Module * Cross—Country Movement * Concealment Computer—Aided Design (CAD) System * Printing * Plotting DigiTAS Data Structure Two approaches were considered in selecting the DigiTAS data structure, the first being to design a data structure optimized specifically for DigiTAS and the second being to base the design on the proposed DMA terrain data structure. The second approach was adopted to make the system as compatible as possible with the proposed DMA product as 441
well as making interim use of data derived from DMA' s terrain factor overlays. The design of the data structure for DigiTAS is therefore driven by several goals: - retain all information content of the planning and tactical terrain analysis overlays that are digitized - adhere to the proposed tactical terrain data (TTD) specifications to allow data to be easily subsetted from TTD when available - balance the tradeoff between data compression and data manipulation There are two basic components of the issue of data structure: data record structure (data content per unit area) and database structure (unit area content per cell). These are essentially independent of one another and are addressed below. Data Record (Unit Area) Factor Vegetation a. type canopy closure b. summer c. winter d. height e. stem diameter f. stem spacing g. roughness h. undergrowth i. misc. other Surface Configuration Surface Materials a. type b. state of ground c. depth of material d. surface roughness e. misc. other of Categories TTADB TTD 24 5 N/A 10 LUT LOT LUT 2 N/A 20 3 2 5(LUT) N/A 26 5 5 11 13 15 11 2•p 21 5 3 21 fetal bits to encode LUT - factors determined from a look up # of Bits DigiTAS 3 3 4 4 4 4 1 0 4 5 3 2 5 0 47 table Table 1: Data Content of Terrain Databases The DigiTAS encoding scheme aligns the categories described above as closely as possible with individual bytes in the data record to facilitate access to any specific item while keeping the data as compact as possible: byte: bit: category; byte: bit: category: 112 I 3 I 4 | 01234 5671012 3 456710123 456710123 45671 l.a.ll.bll.clhll.d.ll.e.ll.f.ll.g.| 2. | Vegetation ISurfj Conf 5|6| 01234 567101 23456 7| 3.a. |3.b|3c| 3.d. | | Surface Materials! Table 2: DigiTAS Bit-mapped Data Record 442
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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
Page 402 and 403: The future skill level, and trainin
Page 404 and 405: €6€ COMPUTER SCIENTIST ELECTRIC
Page 406 and 407: U* '^ OUTPUT \ / REVIEWIM. CORRECTI
Page 408 and 409: We may conceptually divide a VNA in
Page 410 and 411: most interest for transmitting navi
Page 412 and 413: necessary) in such a display. This
Page 414 and 415: ENHANCEMENT AND TESTING OF A MICROC
Page 416 and 417: make maximum use of the limited, lo
Page 418 and 419: I Text Display Window (Toggle On/Of
Page 420 and 421: as well, using the PLINK86 Plus ove
Page 422 and 423: AN INTEGRATED PC BASED CIS FOR INST
Page 424 and 425: RAW DATA INPUT DATA BASE MAPh ANALY
Page 426 and 427: Figure 3. Example of output from SH
Page 428 and 429: Figure 8. CONTOUR of elevation on v
Page 430 and 431: Figure 11. COLOR map on printer of
Page 432 and 433: IDRISI : A COLLECTIVE GEOGRAPHIC AN
Page 434 and 435: felt to be negligible compared to t
Page 436 and 437: Although the IDRISI system was prim
Page 438 and 439: data file, and a second backwards t
Page 440 and 441: TABLE 1 : IDRISI PROGRAM MODULES IN
Page 442 and 443: CLASSLESS CHOROPLETH MAPPING WITH M
Page 444 and 445: polygon. The process of selecting s
Page 446 and 447: There are a number of places where
Page 448 and 449: COMPUTER-ASSISTED TERRAIN ANALYSIS
Page 450 and 451: 2. Input. A digitizing tablet to al
Page 454 and 455: Database Structure Currently, DMA-p
Page 456 and 457: RESULTS OF THE DANE COUNTY LAND REC
Page 458 and 459: E. G.
Page 460 and 461: section maps of tax parcels maintai
Page 462 and 463: Public Land Survey System (PLSS) co
Page 464 and 465: Sheets, Proc. ACSM, 1:153-161. Chri
Page 466 and 467: von Meyer, N.R. 1984b. Westport Ine
Page 468 and 469: While meeting the above criteria pr
Page 470 and 471: oundary line. An example of the sam
Page 472 and 473: Four groups of approximately thirty
Page 474 and 475: LEGEND MULTIPLE BOUNDARIES STATE, C
Page 476 and 477: TABLE 2 shows that more respondents
Page 478 and 479: What features are considered when d
Page 480 and 481: position is insignificant. Thus, th
Page 482 and 483: ASSESSING COMMUNITY VULNERABILITY T
Page 484 and 485: Yale University was selected for st
Page 486 and 487: distribution of hazardous materials
Page 488 and 489: »++ 0000000001000OCCCOOOOOOCOOOOCO
Page 490 and 491: 44* 444 444 ICO 9 CO 9CO to CO ECO
Page 492 and 493: IMPROVEMENT OF GBF/DIME FILE COORDI
Page 494 and 495: Establishment of Control Points In
Page 496 and 497: transformation parameters for a par
Page 498 and 499: of using a fixed set of transformat
Page 500 and 501: vertex coordinates into exact corre
Page 502 and 503:
Friedman, J., Baskett, F. and Shust
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and small freehold land. It does no
Page 506 and 507:
The next step in the planning proce
Page 508 and 509:
TSO on UNB's IBM 3090 mainframe com
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3. Kettela, E.G. 1975. Aerial spray
Page 512 and 513:
The integration of developing techn
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and photographic processes are used
Page 516 and 517:
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
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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
Page 536 and 537:
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
Page 546 and 547:
EXPERT SYSTEM INTERFACE TO A GEOGRA
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ASPENEX automates the analysis of s
Page 550 and 551:
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
Page 564 and 565:
Map retrieval is also crucial to na
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elative coordinate accuracy is very
Page 568 and 569:
destination does not require knowin
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PRESENTATION The extremes of styles
Page 572 and 573:
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
Page 598 and 599:
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
Page 604 and 605:
REFERENCES Cooke, D.F., Vehicle Nav
Page 606 and 607:
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
Page 626 and 627:
Table 2. Length of Sessions and The
Page 628 and 629:
Table 5. Fuzzy Membership Values fo
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Table 7. Results of Zimraermann's M
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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
Page 656 and 657:
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
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which represents the terrain by a t
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leaf for 4 and 5). Chen and Tobler
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fixed polynomial order for each run
Page 668 and 669:
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
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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 728 and 729:
distribution). If the thresholds ar
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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