GG3019/GG4027/GG5019 www.abdn.ac.uk/geospatial An Introduction to Geographical Information Technology and GIS Systems and Geospatial Data Analysis David R. Green G12 – 2324 d.r.green@abdn.ac.uk www.abdn.ac.uk/geospatial

Website www.abdn.ac.uk/geospatial/GG3019

Data Models Lecture 2 Objectives Representing the ‘Real World’ Examine Vector Data Model Examine Raster Data Model

Real World

Real World

Representation

Vector Data Model Points Lines and Areas (Polygons) Represent ‘real world’ / ‘spatial’ features X,Y co-ordinates Point (zero dimension) Line (1D) Area (2D) Nodes, vertex / line, link / area, polygon

Vector Data Model Point: x,y Line: x1,y1: x2,y2 Area/Polygon: x1,y1:x2,y2:x3,y3:x4,y4:x1,y1 x,y……… northings and eastings

Vector Data Model

Vector Data Model Line features can intersect (network) Line features can join Area features can be linked Area features can be connected Area features can have ‘holes’ Representation depends on ‘scale’

Topology Non-Topological Data Structures Do not always require topology CAD - DXF Shapefiles No files to describe topology! X,Y co-ordinates only Topology can be built ‘on-the-fly’ Needed for spatial analysis

Topology Topology Relationships between objects Based on Graph Theory (study of geometric objects and relationships) 3 basic relationships Connectivity (arcs connected at nodes) Area Definition (arc connections define area) Contiguity (left and right direction) Data Structures - Topological

Topology

Topology Connectivity: Arcs are connected to others (at nodes). This identifies possible routes and networks, such as rivers and roads, via the lists of arcs and nodes in the database. Containment: An enclosed polygon has a measurable area; lists of arcs define boundaries and closed areas. Contiguity: The adjacency of polygons can be determined by shared arcs. These are fundamental to GIS analysis and queries, for example: a. From point A, how can I get to point B using the city road system? b. What is the area of the combined areas of all residential housing? c. Which residential areas are next to city parks?

TIN ALSO: Vector data structure for terrain mapping and analysis Triangulated Irregular Network (TIN) Approximate surface with a set of non-overlapping triangles Constructed using Delaunay Triangulation X,Y, Z values and edges

TIN

Raster Data Model Grids / Rasters / Tessellations Raster Map / Surface Cover Square cells Rows and Columns (address of each cell) Cell contains a value / digital number (DN) Point, Line, Area Features represented by ‘overlay’ of grid

Raster Data Model Raster / Grid / Tessellation (regular) 1,1 32 3,3 Columns (j) Image: number (0-255) or 8-bit GIS: number (code) 1,1 Addressing can be used to manipulate data store in each cell e.g. digital image processing 32 Row, column or x,y numbers provide an address for each cell e.g. 1,1; 3,3 etc… (similarity of spreadsheet) 3,3 Rows (i) e.g. mat (2,2) = 32 Multiple matrices e.g. bands of data/imagery; raster maps; digital images

Raster Data Model Airborne & Satellite Imagery Scanned aerial photographs Scanned images, maps, graphics Often used as backdrops for digitising, context May be geocorrected (image fitted or warped to a map (geometrically or planimetrically correct)

Raster Data Model Digital Elevation Models (DEM) Grid of cells comprising heights (z-value) Uniformly spaced Create ‘surfaces’ X Y Z

Raster Data Model Data Structures for Raster files Cell values written - cell-by-cell encoding Also: Run Length Encoding (homogenous areas) Also: Chain Codes, Block Codes, Quadtrees (2D features)

Raster Data Model Data Compression Techniques Standard file encoding for remotely sensed images not always efficient Use more advanced techniques Lossy (JPEG) and Lossless (TIF and GIF) compression Mr.SID / ECW Differential compression based on detail in image

Vector and Raster Conversion Vector to Raster Raster to Vector Vectorisation Rasterisation Integration ArcView / Idrisi

Vector and Raster Advantages & Disadvantages Vector: compact Raster: bulky (large file sizes) Vector: network analysis Raster: cell-based modelling etc…….. Choice dependent on purpose!

Using GIS – What you need to know! Software and Hardware Mathematics (arithmetic, geometry, co-ordinate systems) Statistics (univariate and multivariate) Data Formats Map Projections Datums

Introducing ArcView 3.X Views, Themes/Layers, Legends, Tables, Layouts and Project Files Data Files (.shp, .dbf, .shx etc..) ArcView Extensions and Scripts Maps Map Projections and Datums Basic GIS Functionality

Homework Topology: Map Projections and Datums: Crime Mapping Exercise: http://www.esri.com/news/arcuser/0401/topo.html Map Projections and Datums: http://www.colorado.edu/geography/gcraft/notes/mapproj/mapproj_f.html Crime Mapping Exercise: On GG3019 Website (instructions, three documents, website links, and map files for use in ArcView GIS) Summary of Introduction to ArcView