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A UNIFIED SYSTEM FOR TERRAIN ANALYSIS AND MAPPING FROM DEM AND DTM Professor Stanley H. Collins School of Engineering, University of Guelph Guelph, Ontario and George C. Moon Collins & Moon Limited 435 Stone Road West, Suite 215 Guelph, Ontario. Computer technology was originally introduced into terrain analysis and mapping in two distinct develop ments. In one of these, map production units adopted digitization of terrain features and computer graphics to reduce the costs of production. This development is now proceeding at a very high rate, and has already resulted in some maps that are completely computer- drawn. Engineering plans and cadastral maps have also been completely computerized by a few institut ions. The other line of development was inaugurated by geographers, whose original goal was to derive numerical parameters to characterize and describe various terrain types. For this purpose, much work was done on fitting analytical surfaces to digital elevation data, and in such exercises as cluster analysis and trend analysis of thematic data. It now seems reasonable to say that analytical surface- fitting is dead, except perhaps for local smoothing operations. The statistical techniques have some value in mapping such variables as population, traffic patterns and the like, but seem inappropriate for deriving physical terrain properties or combinations of properties. 124
To an every-increasing degree, the computer is now being used to provide direct and quantitative answers to simple but important questions such as the ones described in this paper. Most of the change in emphasis has arisen from the advance of digital elec tronic techniques, including more rapid and accurate data capture as well as the tremendous increase in capacity and speed of the computer itself. The present authors happened to adopt this approach from the outset (Collins, 1975), and the result has been the development of a powerful series of programs. All of them are intended for economical processing of terrain information, and some of them produce terrain parameters that are unique and highly useful. (Collins and Moon, 1978; Collins, Moon and Fetter 1979). This paper will describe in a more complete form the approach that is being used by the authors for analysing large amounts of terrain data, typically involving models with 10^ or more points. Methods of Data Storage and Analysis There are two methods of data capture which lead directly and naturally into two different methods of data storage. There has been a tendency to preserve this differentiation into the data-analysis stage. One method of data capture, exemplified by contouring, profiling, and outline drawing in photointerpretation, is the polygon method. Terrain information is digit ized in continuous or discontinuous strings of points, each with x and y coordinates and one coded attribute. The other method is the grid-cell method. Coarse grid- cell techniques have been used for many years by geographers, hydrologists and others to record and combine broad terrain features. More recently, remote sensing with its many forms of digitized images has provided new data in a dense-grid form, and dense grids of elevations have been provided by the Gestalt orthophoto system (Brnjac et al, 1976). Storage in polygon (and isolated single point) form is inherently economical, because it involves storing only the data that are essential to describe each significant terrain feature. Some terrain analyses have been carried out by working directly from the polygon structure, but generally speaking it is diffi cult to derive terrain descriptions from combinations 125
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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
Page 89 and 90: disc); - the satellite spin-speed w
Page 91 and 92: line start. These parameters are se
Page 93 and 94: PRACTICAL APPLICATIONS FOR DIGITAL
Page 95 and 96: need for early warning of impending
Page 97 and 98: In order to manipulate classes of f
Page 99 and 100: depends mainly on the density of fe
Page 101 and 102: A DATA STRUCTURE FOR A RASTER MAP D
Page 103 and 104: FIG. 2. A border with indicated max
Page 105 and 106: pointers associated with the max-po
Page 107 and 108: y-max 1 z \7 'x-min \x-max 3 x-min
Page 109 and 110: DIGITAL TERRAIN MODELS SESSIONS Int
Page 111 and 112: Their programs have been developed
Page 113 and 114: that the purpose of the digital ter
Page 115 and 116: equirement for such a program is th
Page 117 and 118: equivalent to locating the lines of
Page 119 and 120: Brassel, K.,1974,"A Model of Americ
Page 121 and 122: It is not the intention of this pap
Page 123 and 124: One feature in this should be empha
Page 125 and 126: neighbouring data points to estimat
Page 127 and 128: Lawson, C.L., 1977. Software for C-
Page 129 and 130: EDIT SYSTEM HARDWARE The IPIN Edit
Page 131 and 132: Each edit terminal will also contai
Page 133 and 134: FIGURE 2. PLOT OF GEOMORPHIC DATA 1
Page 135 and 136: a 0° 0 0 + 0 o 0 FIGURE 4. SELECTE
Page 137 and 138: FIGURE 5. CONTOUR PLOT OF INTERPOLA
Page 139: absorbed in the merger if the diffe
Page 143 and 144: potential storage volumes of depres
Page 145 and 146: Soil type sand, Vegetation trees -^
Page 147 and 148: References Brnjac, M; Carlsen, L; M
Page 149 and 150: is particularly important to allow
Page 151 and 152: (b) If Z-coordinate of the vertex B
Page 153 and 154: Figure 3a. TIN DTM Projection Figur
Page 155 and 156: URBAN MAPPING SESSIONS Introduction
Page 157 and 158: Norfolk, and Hampton Virginia. Part
Page 159 and 160: MAPPING SERVICES IN FAIRFAX COUNTY,
Page 161 and 162: If errors are detected they are res
Page 163 and 164: Some are only printed as the stocks
Page 165 and 166: URBAN MAPPING AND RELATED AUTOMATED
Page 167 and 168: tersection matching program was wri
Page 169 and 170: The selection of coding schemes wil
Page 171 and 172: cartography and are firmly committe
Page 173 and 174: main purpose of this paper. Five of
Page 175 and 176: The project was undertaken specific
Page 177 and 178: play and analysis. By breaking from
Page 179 and 180: The operating system environment is
Page 181 and 182: INTERACTIVE COMPUTER MAPPING* Thoma
Page 183 and 184: - By displaying variables in map fo
Page 185 and 186: with a start - head- and an end -ta
Page 187 and 188: Rovner, P.D and Feldman, J.A., 1968
Page 189 and 190: 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
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Implementation The development plan
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ECQBASE OF BRITAIN: status report o
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1. Coastlines (high water mark) inc
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much statistical data, e.g. , from
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Figure 1 Scale of digitisation of p
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I. Introduction A DATA STRUCTURE FO
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One obvious division of the state i
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Figure 2 illustrates this structure
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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'
Page 445 and 446:
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
Page 451 and 452:
Steven D. Clark Petroleum Informati
Page 453 and 454:
Richard Davis NOAA, NOS 6001 Execut
Page 455 and 456:
John Durkin Suiranagraphics 35 Bren
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E. Porrest A-E-C Automation Newslet
Page 459 and 460:
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
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
Page 479 and 480:
Dirck L. Rotty USDA Forest Service
Page 481 and 482:
Craig L. Shafer NFS 18 & C Street,
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Bobby Staudt M & S Computing 406 Au
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Laure Thompson George Mason Univers
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D.J. Walker Image Graphics 107 Ardm
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Alberta Auringer Wood Chairperson,
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AUTHOR INDEX - VOLUME II Allam, M.
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Schmidt, Warren E. ...............
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