Geography 413/613 Lecturer: John Masich jamasich@gmail.com Vector Data Geography 413/613 Lecturer: John Masich jamasich@gmail.com

Agenda Questions from last week/article review Labs? Spatial Data Data Modelling Vector Data Vector Data Management Next Weeks Lecture

Questions Coordinates and Projection systems

Labs How are they going?

What makes Data Spatial Needs to be referenced to some location on the earth Latitude and Longitude Grid coordinates Place name Description Postal Code Distance and Bearing

What makes Data Spatial The world in infinitely complex Our objective with spatial data is to model the real and fictitious world. The GIS is our medium for doing so

What makes Data Spatial Characteristics Geometry – Shape Location - Place Topology - Relationship

Geometry Shapes – Boundaries/Regions/buildings Path – Streams/Roads Topography – Landscape

Location Latitude and Longitude (54°58'34“, 124°38'47“) Grid Coordinate (645345E, 7865435N) Postal Code (V2L-4P8) Lots (1904-031-200-01100-0000)

Topology Connectivity Containment Adjacency North-east of . .

Modelling Spatial Data Identify the Feature Roads Buildings Parking Lots Streams Lamp posts Manhole covers Ponds

Modelling Spatial Data Classify the feature Lamp Posts Manhole Covers Point Roads Streams Line Buildings Parking Lots Ponds Poly

Modelling Spatial Data Attribute the feature Gives intelligence/meaning to your data Allows complex queries and analysis “Validates” the data

Spatial Data Storage Vector data

Vector Data (ESRI – GIS Dictionary) A coordinate-based data model Geographic features represented as points, lines, and polygons. Point feature is represented as a single coordinate pair Line and polygon features are represented as ordered lists of vertices. Attributes are associated with each vector feature. (ESRI – GIS Dictionary)

Vector Data – Point, Line, Poly Points (0 Dimension) Display data as a single location (x/y). Has neither length or area Lines (1 Dimension) Sequence of xy coordinate pairs Displays length at any given scale Polygons (2 dimensions) Connected sequence of xy coordinate pairs Displays area at any given scale

Vector Data Coordinate Pairs Stored explicitly Cartesian coordinates

TINS (3d Vector) A vector data structure that partitions geographic space into contiguous, non-overlapping triangles. The vertices of each triangle are sample data points with x-, y-, and z-values. These sample points are connected by lines to form Delaunay triangles. TINs are used to store and display surface models. (ESRI-GIS Dictionary)

Advantages of Vector Data Structures Small amount of data Easy to update Logical data structure Attributes are combined with objects Preserves quality after interactivity (e.g. scaling) More sophisticated in spatial analysis

Disadvantages of Vector Data Structures Continuous data is not represented effectively Spatial analysis and filtering within polygons is impossible Needs a lot of manual editing to get good quality It always introduces hard boundaries Unable to model uncertainty

Vector Data Analysis Overlay/Buffer

Vector overlay much more complex compared to raster overlay Creates spurious data results Multiple features created during the process.

Basic overlay processes

Map overlay concepts Map overlay addresses the relationship of the intersection and overlap between spatial features. Map overlay combines the spatial and attribute data of two input themes. Three input feature types, overlay cover is always polygon: point-in-polygon, points are output line-in-polygon, lines are output polygon-in-polygon polygons are output

Point in Poly

Line-on Poly

Poly in Poly overlay

Examples of Vector overlay

Vector analysis Patterns - Distance Cost surface Distance to features Buffering How far is something from something else? What zone is it in? What data is within the buffer area? How long does it take to get from point a to point b?

GIS Project Management Vector Data

Remember this ... “Failing to plan is planning to fail” (Sir Winston Churchill)

Why GIS Projects fail Poor Scope Schedule No quality Standards No systems integration No executive sponsorship No staff training Failure to mange risk Unrealistic cost estimates No Internal marketing Planned obsolescence Not all of these will apply to you

$ The excuses No time Costs too much Not important Too busy I need to start now Costs for Planning Costs for Correction $ $ Before Project Starts After Project Starts

How do you manage your data? What is your plan for managing your vector data?

Managing Vector data The geodatabase

Data formats So far in your GIS courses you have used different data types (Shapes, .kml, coverages …) These are ultimately containers for your information Not always and effective way to store your data …

Why? Topological relationships not maintained in shapefiles Data is not contained … scattered Projection inconsistencies occur Attribute data formats not enforced Lets look at the geo-database

What is a Geodatabase A geodatabase is a database designed to store, query, and manipulate geographic information and spatial data.

Managing your data using a geo-database Benefits See handouts The user will ultimately decide how the data should be stored and managed.

Why ask the question Before starting your project you must have some idea of how to deal with Spatial/attribute Data integrity Error resolution Tolerances Methodology

Let take a quick look at some of the features and how Yes – the Live Demo