CARTOGRAPHIC RULES OF FEATURES DEFINITION IN
CUSTOMIZED GIS SYSTEMS
Wieslawa Zyszkowska
University of Wroclaw,
Poland
zyszkowska@geogr.uni.wroc.pl
Abstract
The paper discusses the problem of determining the proper cartographic form of features on three stages of spatial modelling in GIS environment: definition of DLM, transform DLM to DCM and transform of DCM to map. On each stage the following aspects are considered: the map purpose, the approach, the type of expression, the type of spatial pattern of geographic objects, the type of borders, the dimension of objects, the reference unit, measurement scale level, the preparation level, variables number, variable length, interpolation procedures, calculations Some examples of resolution of different problems will be presented.
Two of very basic GIS functions, spatial information analysis and presentation, are strictly connected with cartography which defines the rules of proper and effective means of presentation of geographic space objects and properties established by spatial analysis. In GIS domain many attempts were made to improve the manner in which the effects of GIS analysis are presented on the screen or other outputs and we can say that in contemporary GIS packets the graphic possibilities are quite good. But if we we would like to define GIS adapted to customs needs, we should realise that maps are means of visualisation and communication of information and look on map not only as a nice picture but as model of geographical reality, image of hypotheses on spatial events distribution and relations. Cartographic methods have been developed for centuries and now we have many good manuals that could be used by GIS users for making good maps (Robinson et all. 1995, Kraak and Ormeling 1996). However many of them do not have a time (or even will) to read cartographic books and the utilize GIS graphic means without thinking of cartographic rules. There is a trend to improving the cartographic function of GIS by adding more and more options from graphic programs. It were sufficient if we would make only a pretty picture instead of map. If we would like to define a model of geographical space, we should put in GIS some means to this process. The paper discusses the basic aspects of the defining of these means by determining the proper graphic form of features in GIS environment on three stages of use of GIS: defining of digital geographical space model (DGSM), transforming DGSM to digital cartographic model (DCM) and transforming it to a map. The idea of models is adopted from ATKIS concepts of DLM and DCM. The following aspects are considered: map purpose , approach, distribution of geographical objects or places, borders between places, objects/places dimensions and reference units, measurement scale - formulation level, data transformation level, variables number, variables length, visual variables, grouping methods, interpolation procedures, calculations The paper is concerned only with static approach, maps presenting one state of phenomena, in one point or period of time. Dynamic approaches should be analysed in separate approach. Also the cartographic generalisation is not disscussed, although it is the process of basic importance. Only some aspects of cartographic feature defining consisting generalisation procedure are considered.
I. Definition of DGSM
In defining of DGSM we start from the concept of amorphic space that is to be modeled. To determine its properties we should separate some objects and/or places in the space to which some properties refer and try to define their boundaries. As we know there are three types of objects/places - points, lines, areas which could have different spatial distribution, compact or continuous and different boundaries. These object/places are characterised by different attributes. We could choose an analytic or synthetic attempt to the modeling. In the first attempt we would like to present objects or places or their classes separately, without transformation of the data. In the second one we are going to present spatial relationships between the objects or places or relationships between their attributes. In this case some transformations are needed. Each map is a presentation of the spatial distribution of phenomena. To elaborate a model we should determine some properties of events as well as their spatial pattern. A. Goal of presentation A1. Inventory A2. Presentation of spatial properties A3.
Presentation of surface B. Character of distribution of geographical objects or places B1. Dispersed B2. Compact B3. Continuous C. Borders between places C1. Clear defined, sharp - line symbol C2. Fuzzy - band or strips C3. Undetermined - without boundary line on a map D. Objects/places dimensions - reference unit D1. 0D - points D1a. localisation and identification D1b. localisation without identification D1c. Localisation with attributes D2. 1D - lines D2a. localisation and identification D2b. localisation without identification D2c. Localisation with attributes D3. 2D - area D3a. Localisation and identification D3b. Localisation without identification D3c. Localisation with attributes D4. 3D - surface D4a. 2D geometric properties - isolines (z constant) D4b. 3D surface shape - (x,y constant), shadowing -go to TIN or GRID D4c. Morphometric properties - gradient and aspect
E. Data transformation level
E1. Rough -
E1a. without grouping
E1b. absolute
E2. Processed -
E2a. grouped
E2b. relative
E2c. interpolated
F. Formulation level - measurement scale
The formulation level refers to measurement level (Robinson et all
1995) F1. without differentiation F2. Qualitative attributes F2a.
Dichotomic F2b. Hierarchical F2c. Nominal F3. Interim, both
quantitative and qualitative - order F4. Quantitative attributes F4a.
Interval F4b. Scalar
G. Variables number
G1. One
G2. Two
G3. Three or more
H. Variables length
H1. One - simple map
H2. Two - binary approach
H3. Three or more - grouping
I. Visual variables
I1. Size
I2. Form
I3. Orientation
I4. Color
I5. Brightness
I6. Texture
I7. Spatial frequency (the two last are proposed instead of Bertin's grain (Bertin 1967) J. Grouping methods J1. Qualitative attributes
J1a. Classification J1b. Typology J2. Quantitative attributes J2a.
Classes number J2b. classes limits K. Interpolation procedures (only some possibilities are presented) K1. Inverse distance K2. Kriging K3.
Minimum curvature L. Calculations L1. Statistical parameters L2.
Morphometric parameters
II. Transforming DGSM to DCM
On this stage we determine links between chosen points of model definition. Three examples will be presented: 1. Simple map of one phenomena distribution 2. soil map 3. population density map III. Transform of DCM to map (on screen or other output) This stage the variables have been choosing and their computer/graphic parameters defining, for example the percentage of colors, numbers of points/ linear/ patch markers, some graphic modelling options, like smoothing.
The paper disscusses only some aspects of feature definition for customised GIS. Defining all feature combinations and possibilities of their graphic presentations is impossible in one paper. But the proposition is thought to provoke a discussion on this important problem and in obtaining the improvement of map efficacy in GIS environment.
References