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UNIT 3 – MODULE 2: Spatial Data. DATA Sources of data can be categorized as primary (first-hand observation or secondary (collected by someone other than.

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Presentation on theme: "UNIT 3 – MODULE 2: Spatial Data. DATA Sources of data can be categorized as primary (first-hand observation or secondary (collected by someone other than."— Presentation transcript:

1 UNIT 3 – MODULE 2: Spatial Data

2 DATA Sources of data can be categorized as primary (first-hand observation or secondary (collected by someone other than the user). All data sources have three modes or dimensions: – Temporal – Thematic – Spatial Credit: CSU - Chico

3 MODES & DIMENSIONS Temporal – Records when data was collected. Example: 02:30 hours, 4 March, 1996. Thematic – Describes characteristics of the data being referenced. Example: dry slab avalanche caused by three skiers. Spatial – Coveys information about a location or feature. Example: Snow Valley, north- facing slope.

4 MAPS How we traditionally store, analyze and present spatial data. Can take different forms. Thematic maps – shows data or information about a specific topic or theme. Maps are generated with a purpose or goal. Credit: EIA Credit: University of Delaware

5 SCALE Maps are always smaller than what’s being presented. Scale allows us to get a real- world sense of features on a map by comparing actual size to a represented size. We express scale in three different ways: – Ratio Scale – Verbal Scale – Graphical Scale Credit: www.lewishistoricalsociety.com

6 POINTS Represents features that are too small to be represented as with the map scale being used. Example: tree, lamp post, mailbox, etc. Data from a point should include location, height and feature details. Credit: www.bostonography.com

7 LINES Represents linear features (e.g. rivers, roads, power lines, geologic fault lines). Credit: ArcGIS

8 AREAS Represented by lines that enclose a portion of the map (e.g. buildings, lakes, fields, parks). Can also represent features that do not exist (e.g. school zone). Areas are commonly referred to as polygons. Credit: GIS Consortium

9 GENERALIZATION All spatial data is a generalization of real- world features. Simplifying real-world features is necessary for map clarity. Amount of detail will be determined by the map scale. Credit: Ordnance Survey

10 GENERALIZATION EXAMPLE Example: Bloodvein River Small Scale Representation – Bends & Turns Smoothed – Simplified & Easy To Read Large Scale Representation – More Details – Nearby Features Highlighted – Complex Credit: www.chrs.ca

11 SPATIAL REFERENCING Referencing system needed for locating features on Earth’s surface. There are several spatial referencing categories: – Geographic Coordinate Systems – Rectangular Coordinate Systems – Non-Coordinate Systems (e.g. Zip Codes) Geographic coordinates (latitude & longitude) are the most common. Credit: ArcGIS

12 DATA SOURCES Spatial Data – Census & Survey Data (Population Census, Employment Data, Marketing Data, etc.) – Aerial Photographs – Satellite Images Field Data – used when data does not exist. – Surveying – GPS Some data sources may be more accurate than others. Which do you think is more accurate: census data or satellite images?


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