1. Presented by Rehana Jamal (GIS Expert & Geographer) Dated: 02.12.14 Advance Applications of RS/GIS in Geo-Environmental Conservation Subject Lecture# 9&10 M.Phil & P.hd Topic 02 Dec-141 Spatial Data Models and Structure

2. 2 Spatial database is a spatial Model of Reality Introduction The real world is too complex for our direct understanding so we create “Models” of reality having similarity with selected aspects of the real world. Models are in form of layers Layer is a heterogeneous collection of geometries having the same attribute set. 02 Dec-14

3. 3 Spatial Data Models facilitate  Early analysis of properties, e.g. storage cost, querying ability  Reuse of shared data among multiple applications  Exchange of data across organization  Conversion of data to new software / environment 02 Dec-14 Why Spatial Data Model? Data structures are complex for GIS because they must include information pertaining to entities with respect to:  position  topological relationships  attribute information. It is the topologic and spatial aspects of GIS that distinguish it from other types of databases. First Second

4. 4 Raster data-- represent the landscape as a rectangular matrix of square cells. Or Set of cells on a grid that represents an entity (entity -- symbol/color -- cells). Vector data --represent features as discrete points, lines, and polygons. Or an entity is represented by nodes and their connecting arc or line segment (entity -- points, lines or areas -- connectivity) Object data– an entity is represented by an object which has as one of its attributes spatial information. Types of Spatial Data Structure 02 Dec-14 Three types of representations for geographic data

5. 5 Raster data models incorporate the use of a grid-cell data structure where the geographic area is divided into cells identified by row and column. This data structure is commonly called raster. Raster data Model The term raster implies a regularly spaced grid other tessellated data structures do exist in grid based GIS systems. Raster data structure represents geographical space by dividing the space into a series of units known as pixels(picture element). 02 Dec-14

6. VECTOR CHARACTERISTICS POINT × LINE POLYGON 6 × × ×× × × × 02 Dec-146

7. 7 Point Line Polygon Vector dataRaster data 02 Dec-14

8. DATA MODELS OF RASTER AND VECTOR REAL WORLD 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 GRID RASTER VECTOR 802 Dec-14

9. Pond Lake River Reality – Hydrography in Vector data Pond Lake River Reality overlaid with a grid 110 11 111 111 2 2 22 2 2 11 000000000 0000000 00000000 00000000 0000000000 00000000000 Resulting raster Creating a Raster 0 = No Water Feature 1 = Water Body 2 = River 9 Creating a Vector 02 Dec-14

10. 10 A point is represented by an explicit x,y coordinate in vector format, but as a raster, it is represented as a single cell —the smallest unit of a raster. By definition, a point has no area but is converted to a cell representing area. Point 02 Dec-14

11. 11 In vector format, a line is an ordered list of x,y coordinates, but in raster format it is represented as a chain of spatially connected cells with the same value. When there is a break between the chain of same-valued cells, it represents a break in the line feature, which could represent different features such as two roads or two rivers that do not intersect. Lines 02 Dec-14

12. 12 A vector polygon is an enclosed area defined by an ordered list of x,y coordinates in which the first and last coordinates are the same, thereby representing area. By contrast, a raster polygon is a group of contiguous cells with the same value that most accurately portray the shape of the area. Polygonal, or area, data is best represented by a series of connected cells. Examples of polygonal features include buildings, ponds, soils, forests, swamps, and fields. Polygons 02 Dec-14

13. 13 Raster data model  Divide the world into square cells  Register the corners to the earth  Represent discrete objects as collections of one or more cells  Represent fields by assigning attribute values to cells Oak savannah Grassland Mixed conifer Douglas fir Legend Fig. Raster representation, each colour represents a different value of a nominal- scale field denoting land cover class 02 Dec-14

14.  grids (ArcGIS & ArcInfo specific)  graphical images (TIFF, JPEG, BMP, GIF, etc.)  USGS DEM (Digital Elevation Model)  remotely-sensed images (Landsat, SPOT, Quick bird, World View 1, AVHRR etc) Types of Raster Data 02 Dec-1414

15. 15 Spatial resolution refers to the dimension of the cell size representing the area covered on the ground OR spatial resolution refers to the cell size (the area covered on the ground and represented by a single cell). Therefore, if the area covered by a cell is 5 x 5 meters, the resolution is 5 meters. The higher the resolution of a raster, the smaller the cell size and, thus, the greater the detail. 02 Dec-14

16. 16 Coarser Spatial resolution High Spatial resolution 02 Dec-14

17. 17 Discrete Continuous Discrete objects/data and Continuous surfaces/objects/data Data Structure for Continuous Surface Model 02 Dec-14

18. 18 Vector data model x y Point Line/arc Polygon Node Vertex × × × × × × Line segment Node 02 Dec-14

19. 19 Topological data Structure (model) Topology Topology is that branch of mathematics used to define spatial relationships between entities (ESRI 1992). For example, an area or polygon is defined by a set of lines which makes up its boundaries. In this case the line is the border between two polygons. The connectivity or contiguity of these features is referred to as their topology structure (ESRI 1992). By sorting information about the location of a feature relative to other features, topology provides the basis for many kinds of geographic analysis without having access to the absolute locations held in the coordinate files (ESRI 1992). Topological data Structure 02 Dec-1419

20. 20 Topological data Structure (model) The Topological data model is termed Arc-Node data model.  Arc the basic logical entity, a series of point that starts and end at a node.  Node is an intersection point where two or more arcs meet. A node can also occur at the end of a dangling arc i.e. and arc that is not connected to another arc such as the end of a dead-end street.  Polygon is comprised of a closed chain of arcs that represents the boundary of the area.  Point is encoded as a single XY co-ordinate pair. Point is considered as the polygon with no area. 02 Dec-14

21. Vector GIS data models 21  Spaghetti model  Topological vector model  TIN (Triangular Irregular Network) 02 Dec-14

22. Spaghetti model 2202 Dec-14

23. 23 0 10 20 30 40 50 60 70 70 60 50 40 30 20 10 0 a6.D.N5 a7 N6 N1 N2 N3 N4 a1 a2 a3 a4 a5 A B C E E X-axis Y-axis Spatial data encoding o Node Topology o Arc Topology o Polygon Topology o Arc coordinate data Topological Data Model or Structure/Arc-Node Data Model 02 Dec-14

24. 24 A1,4,5 B2,4,6 C3,5,6 A BC i.1 4 ii.4 4 iii.6 4 iv.4 1 Node X Y 1 2 3 4 5 6 2 3 4 5 6 1 i ii iii iv 1iiiiOA 2iivBO 3iiiivOC 4iiiAB 5iiiiiAC 6iiivCB LineFromToLeftRight Poly Lines O = “outside” polygon 1 2 3 45 6 Topological Data Model or structure/Arc-Node Data Model 02 Dec-14

25. The Triangulated Irregular Network (TIN) data model is an alternative to the raster and vector data models for representing continuous surfaces. The Triangulated Irregular Network (TIN) data model TIN Data Model Four Tables for TIN Model  Node Table it lists each triangle and the nodes which define it.  Edge Table it lists three triangles adjacent to each facets. The triangles that border the boundary of the TIN show only two adjacent facets.  XY Co-ordinate Table it lists the co-ordinate values of each node.  Z Table it is the altitude value of each node. 02 Dec-1425

26. 26 Topological Relationships between Spatial Objects or Spatial relationship in Topological data model  Containment  Contiguity/Adjacency  Connectivity 02 Dec-14

27. 27 Raster data Vector data Object data 02 Dec-14 Three types of representations for geographic data Summary Spatial Data Models and Structure  Spaghetti model  Topological vector model  TIN (Triangular Irregular Network)

28. 28 Possible Exam Questions Q1.Differentiate the following: 5 Marks each i.Raster and Vector data model ii.Data model and Data structure iii.Spaghetti and Topological data model iv.Raster and Vector data model Q2.Write a note on the following: 5 Marks each i.TIN data model ii.Spaghetti data model iii.Raster and Vector data model Q3.Describe in detail with diagrams the “Spatial data models”. 15 Marks 02 Dec-14

29. 29 References:  www.yahoo.com  www.esri.com  “Geographic Information System” by Stan Aronoff  (http://www.olemiss.edu/depts/geology/courses/ge4 70/RasterDataModel.htm#8b.1) 02 Dec-14