Presentation is loading. Please wait.

Presentation is loading. Please wait.

Copyright, 1998-2014 © Qiming Zhou GEOG3600. Geographical Information Systems GIS Data Modelling.

Similar presentations

Presentation on theme: "Copyright, 1998-2014 © Qiming Zhou GEOG3600. Geographical Information Systems GIS Data Modelling."— Presentation transcript:


2 Copyright, © Qiming Zhou GEOG3600. Geographical Information Systems GIS Data Modelling

3 2 GIS data modelling  What is a data model?  GIS data models  CAD, graphical and image GIS data models  Raster data model  Vector data model  Object data model

4 GIS Data Modelling3 What is a data model?  The heart of any GIS is the data model.  A data model is a set of constructions for describing and representing selected aspects of the real world in a computer.  There is no single type of GIS data model that is best for all circumstances.

5 GIS Data Modelling4 The role of a data model in GIS People Interpretation and Explanation Operational GIS Analysis and Presentation GIS Data Model Description and Representation Real World

6 GIS Data Modelling5 Levels of data model abstraction  Reality: real world phenomena  Conceptual model: human-oriented model of selected objects and processes in relevance, often partially structured  Logical model: implementation-oriented representation of reality, often expressed in the form of diagrams and lists  Physical model: portrays the actual application in a GIS, often comprises tables stored as files or databases.

7 GIS Data Modelling6 Levels of abstraction Reality Conceptual model Logical model Physical model Increasing abstraction Human- oriented Computer- oriented

8 Conceptual model GIS Data Modelling7 A road: Centre line (position) Edge line (width) Shoulder Number of lanes One way/two way Speed limit Traffic conditions Pavement Underground structure Intersections Date of completion Maintenance date … Road Line Area Attributes Centre line Network Intersection Main section Shoulder Speed limit No. of Lines

9 Logical model GIS Data Modelling8 RoadLine-idArea-idRoad No.Name… Line-idS-NodeE-NodeVerticesLength… Area-idLeft edgeRight edgePavementArea… Verticesx,y, …, … … Verticesx,y, …, … … Verticesx,y, …, … …

10 Physical model GIS Data Modelling9 Road R-lineR-area R-… … Record 1Line-idArea-idRoad No.Name… Record 2Line-idArea-idRoad No.Name… Record nLine-idArea-idRoad No.Name… File: Road Record 1S-NodeE-NodeVerticesLength… Record 2S-NodeE-NodeVerticesLength… Record nS-NodeE-NodeVerticesLength… File: R-line Road

11 GIS Data Modelling10 GIS data models  CAD, graphical and image GIS data models  Raster data model  Vector data model  Object data model

12 GIS Data Modelling11 Geographical data models used in GIS Data modelApplication Computer-aided designSimple mapping ImageImage processing and simple grid analysis Raster/gridSpatial analysis and modelling Vector/geo-relational topological Operations on vector geometric features NetworkNetwork analysis Triangulated irregular network (TIN) Terrain analysis ObjectOperations on all types entities

13 GIS Data Modelling12 CAD, graphical and image GIS data models  The earliest GIS were based on very simple models.  CAD data model:  Local drawing coordinates  Objects do not have unique identifiers.  No relationship details between objects are stored.  Simple graphical data model: cartography  Image model: field data rather than objects.

14 GIS Data Modelling13 The CAD data model A CAD model focuses on feature drawing only so that it does not represent any kind of relationships between objects.

15 GIS Data Modelling14 Simple graphical data model A simple graphical data model is adequate to make a cartographic representation of Hong Kong SAR.

16 GIS Data Modelling15 Image data model Image data: On the left is the false colour composite of Landsat ETM image using Band 4, 3 and 2. On the right is the classification of the image using 6 bands of the Landsat ETM images (excluding Band 6).

17 GIS Data Modelling16 Raster data model  Raster data model uses an array of cells, or pixels, to represent real-world objects.  Difference between raster and image data models:  Image data do not have attribute table attached so that they have only one attribute field.  Raster data have attribute table that can be joint to other tables so that they can have multiple attribute fields.  Applications: image data: image processing; raster data: spatial analysis and modelling

18 GIS Data Modelling17 Grid with attributes

19 GIS Data Modelling18 Data structure of raster data model  Cartographic model (database)  Map layer (overlay, coverage, grid)  Zone (region)  Location

20 GIS Data Modelling19 Hierarchy of the raster data structure Cartographic Model Map layer Zone Orientation Resolution Title Map layer Value Label Zone Location Row coordinate Column coordinate

21 GIS Data Modelling20 Cartographic model  The data for an area can be visualised as maps or layers.  A cartographic model is a set of data describing selected characteristics of each location within a bounded geographic area in the form of map-like layers.

22 GIS Data Modelling21 Cartographic model (cont.) Topography Soil types Forest types Buildings Real world Soils

23 GIS Data Modelling22 Map layer  A map layer is a set of data describing a single characteristic of each location within a bounded geographical area.  Only one item of information is available for each location within a single layer.  Major components of a layer are its resolution, orientation and zones.

24 GIS Data Modelling23 Map layer (cont.) Australia New South Wales Victoria Queensland South Australia West Australia Tasmania YY XX Northern Territory N 

25 GIS Data Modelling24 Zone  A zone is a set of contiguous location that exhibit the same characteristic.  Term class is often used to refer to all individual zones that have the same characteristics.  Major components of a zone are its value, label and locations.

26 GIS Data Modelling25 Zone and class

27 GIS Data Modelling26 Value and label of a zone  Value  The item of information stored in a layer for each cell or pixel  Cells in the same zone have the same value  Label  “Additional” information associated with each zone  Can be numeric or alphabetic (i.e. numbers or text)

28 GIS Data Modelling27 Zone (cont.) Australia New South Wales Victoria Queensland South Australia West Australia Tasmania YY XX Northern Territory N  State IDState NameCapitalPopulation 02New South WalesSydney QueenslandBrisbane

29 GIS Data Modelling28 Location  A location is the smallest unit of geographical space for which data a recorded (also called cell or pixel).  A location is defined as that a portion of the cartographic plane is uniquely identified by an ordered pair of coordinates (row and column numbers).

30 GIS Data Modelling29 Vector data model  Simple features  Topological features  Network data model  TIN data model

31 GIS Data Modelling30 Vector representations pointlinearea Scalecity wells highway political boundary streams agriculture land urban land city highway airport

32 Multiple representation GIS Data Modelling31 Small-scale representation of cities as points Large-scale representation of cities as areas

33 GIS Data Modelling32 Simple features Point numberx, y coordinates 1(2, 8) 2(3, 3) 3(12, 7) 4(9, 4) Line numberx, y coordinates 1(1, 6), (4, 8), (8, 6), (13, 8) 2(1, 3), (4, 4), (9, 2), (13, 5) Polygon numberx, y coordinates 1(2, 5), (3, 8), … (2, 5) 2(6, 4), (8, 4), … (6, 4)

34 GIS Data Modelling33 The “spaghetti” structure Original map Map expressed in Cartesian coordinates FeatureNumberLocation Point Line Polygon X Y (single point) X 1 Y 1, X 2 Y 2, …, X n Y n (string) X 1 Y 1, X 2 Y 2, …, X 1 Y 1 (closed loop)

35 GIS Data Modelling34 Topological features  Topological features are simple features structured using topological rules.  Topology is the science and mathematics of relationships.  In GIS, topology is used to validate the geometry of vector datasets.

36 GIS Data Modelling35 Arcs  When planar enforcement is used, area objects in one layer cannot overlap and must exhaust the space of a layer.  Every piece of boundary line is a common boundary between two areas.  The stretch of common boundary between two junctions (nodes) may be called edge, chain, or arc.  Arcs have attributes which identify the polygons on either side (“left” or “right”).  In what direction by which we can define “left” or “right”?  Arcs are fundamental for topological features.

37 GIS Data Modelling36 Arcs (cont.) Start node End note vertex An Arc

38 GIS Data Modelling37 Arc-node structure N3 N1 N2 N6 N5 N4 a1 a2 a3 a4 a5 a6 A B C Polygon topology PolygonArcs A B C a1, a5, a3 a2, a5, 0, a6 a6 0Outside map Node topology NodeArcs N1 N2 N3 a1, a3, a4 a1, a2, a5 a2, a3, a5 N4a4 N5 N6 0 a6 Arc coordinates Arc Start X, Y a1 a2 a3 40,60 70,50 10,25 a440,60 a5 a6 10,25 55,27 Intermediate X, Y End X, Y 70,60 70,10; 10,10 10,60 30,50 20,27; 30,30; 50,32 55,15; 40,15; 45,27 70,50 10,25 40,60 30,40 70,50 55,27 Arc topology Arc Start Node a1 a2 a3 N1 N2 N3 a4N4 a5 a6 N3 N6 End Node Left Polygon Right Polygon N2 N3 N1 N2 N A A B A B A A B C

39 GIS Data Modelling38 Topological features

40 GIS Data Modelling39 Network data model

41 GIS Data Modelling40 TIN data model X-Y Coordinates node#coordinates x1, y1 x2, y2 x3, y3... x11, y11 Z Coordinates node#z_value z1... z2 z3 z A B C D E F G H I J K L M N Triangle Table node# A B C D E F G H I J K L M N 1, 6, 7 1, 7, 8 1, 2, 8 2, 8, 9 2, 3, 9 3, 4, 9 4, 9, 10 4, 5, 10 5, 10, 11 5, 6, 11 6, 7, 11 7, 8, 9 7, 9, 10 7, 10, 11 Id# area slope …

42 GIS Data Modelling41 Creating TIN from contours

43 GIS Data Modelling42 TIN surface

44 GIS Data Modelling43 Object-oriented concepts  An object is a self-contained package of information describing the characteristics and capabilities of an entity under study.  In a geographical object data model, the real world is modelled as a collection of objects and relationships between them.  Each entity in the GIS is an object.  A collection of objects of the same type is called a class.

45 GIS Data Modelling44 Object data model  For GIS purposes it is not sufficient merely to hold data on map elements in the data base. It must also be possible to access the operations to be performed on these elements.  An object is an entity that has a state represented by the values of local variables (instance variables) and a set of operations or methods (instance methods).  Individual objects belong to a class that defines the type of object.  Each class has a superclass from which it can inherit both instance variables and methods.

46 Example: Landuse Landuse object definitionPolygon object definition Superclass (object)Superclass (Landuse) Class variables Class-id Class name Class variables Polygon-id Borderline-id Instance variables List of polygons Class descriptions Instance variables List of borderlines Area Instance methods Re-class Calculate class statistics Instance methods Draw Calculate centroid GIS Data Modelling45 Boderline object definition Superclass (polygon) Class variables (node-id, …) Instance variables (start-node, end-node, …) Instance methods (edit vertices, …)

47 Landuse object structure GIS Data Modelling46 Object Landuse Class 1 Class 2 Class 3 Polygon Borderline Polygon 1 Polygon 3 Polygon 2 Borderline 1 Borderline 2 Borderline 3 Borderline 4

48 GIS Data Modelling47 Implementation of O-O model

49 GIS Data Modelling48 Three key hallmarks of object orientation  Polymorphism  Encapsulation  Inheritance

50 GIS Data Modelling49 Polymorphism Application Geospatial database access objects Geospatial database CoverageCAD data Polymorphism Applications Data components Data sources

51 GIS Data Modelling50 Encapsulation Feature Data set Encapsulation Table Data set Object Class Relationship Class Feature Class

52 GIS Data Modelling51 Inheritance Simple Road Feature Inheritance Standard feature types Custom feature types Complex Road Feature Road Feature Road central line Road edge Overpass

53 GIS Data Modelling52 Advantages  The ‘natural’ model: directly corresponds to the object found in reality.  Completeness: every object is completely bounded with a defined ‘shell’.  Inheritance: a class can include subclasses that can inherit both its data and methods.  Openness: allows to modify and expand instance variables and methods.

54 GIS Data Modelling53 Summary  The heart of a GIS is the data model it employs.  With increasing level of abstraction, models are created from human-oriented conceptual, logical to computer-oriented physical models  There is no single type of GIS data model that is best for everything.  Commonly used data models include:  CAD, graphical and image data models  Raster data model  Vector data model  Object-oriented data model

Download ppt "Copyright, 1998-2014 © Qiming Zhou GEOG3600. Geographical Information Systems GIS Data Modelling."

Similar presentations

Ads by Google