CE 250 - Introduction to Surveying and G eographic I nformation S ystems

1. CE 250 - Introduction to SurveyingandGeographic Information Systems eLearning Version Donald J. Leone, Ph.D., P.E. Lecture 2

2. Introduction • Spatial Data – How is it described? • Spatial Data – Main sources. • More on Rasters and Vectors • Spatial Data Models • Two new Spatial Data Entities • Numerical Characteristics of Attributes.

3. Definition • Spatial Data: Information about the geographic position of features • Geographic Position – Usually an x,y coordinate pair in two dimensional space

4. GIS Model Building • Model – “Simplified “ view of the “real” world. • Computer generated representation. • Constructed using spatial data.

5. Nature of Spatial Data • Data vs. Information - Metadata • Primary data – first hand knowledge • Secondary data – collected by someone else • Spatial data types • Temporal – when, where, etc. (Metadata) • Thematic – describes real world feature (Attributes) • Spatial – location of feature (x,y)

6. Traditional Maps Influence how we characterize spatial data. • Purpose • Scale • Select features • Adopt a map projection • Select a spatial reverencing system • Annotate

7. Scale • Definition – Indicates how much smaller than reality a map is. • Ratio – Distance on a map to the distance on the ground. • 1:5000 – 1 cm on map = 5000 cm on ground or 50 m • Graphical 1 cm 0m 100m 150m 50m

8. Scale – Continued • Large ratio’s – 1:2,000,000 • “small scale maps” • Cover large areas • Small ratio’s – 1:25,000 • “large scale maps” • Cover small areas

9. Scale Related Generalization The level of detail shown is directly related to scale

10. Map Projections • Transfer spherical earth to flat surface. • Many types of projections used world-wide. • There will always be some distortion generated in the projection process.

11. Projection TechniquesCylindrical Projection

12. Projection TechniquesAzimuthal Projection

13. Projection TechniquesConic Projection

15. Spatial Referencing • Geographic Coordinate Systems (3D) • Rectangular Coordinate Systems (2D) • Non Coordinate Systems, i.e. zip codes

16. Geographic Coordinate SystemLatitude and Longitude Parallels - Meridians

17. Geographic Coordinate SystemLatitude and Longitude Angles Prime Meridian 00Longitude Latitude – North Longitude - West Equator 00Latitude

18. Latitude – Longitude Calculation

19. Little Grey Cells Quiz • Large scale maps cover large areas. T or F • Why are projections needed? • Why do you think the prime meridian goes through Greenwich, England?

20. Rectangular Coordinates (2D)

21. Universal Transverse Mercator (UTM)

22. The State Plane Coordinate System - SPCS • Used primarily for engineering applications • Arbitrary origin - An arbitrary number of feet south and west of the most southwesterly point on the map. • Eastings (x) and northings (y) all come out positive. • Advantage: Accuracy • Disadvantage: Lack of universality, as each state has it’s own coordinate system.

23. Break!

24. Other Sources of Spatial Data • Census Data – TIGER Files Topolocally Integrated Geographic Encoding Referencing

25. Other Sources of Spatial Data Aerial Photographs Increased Altitude Produces smaller scale maps Distortion toward the edges

26. University of Hartford Aerial Photo Sports Center HJG Center UT Hall

27. Other Sources of Spatial Data LANDSAT Image Morro Bay, CA • Satellite Images

28. Other Sources of Spatial Data • Surveying • The Global Position System – GPS www.trimble.com

29. Spatial Data Modeling Real World Spatial data – Map, etc. Spatial Data Model Raster Vector GIS Software Spatial Data Structure Computer

30. Raster Data Structure Cell Values File Structure Feature Model

31. Vector Data Structure Line or Arc Number Node or Point Number

32. Vector Data Structure - TOPOLGY • Topology- “The property that describes adjacency and connectivity of features” • Newer structure for Vector data - Topological Arcs File - added to previous data. • Used to build polygons that touch each other exactly.

33. Vector Data Structure - TOPOLGY

34. Two New Spatial Entities • “Old” three – Points, Lines, Polygons • Add two more – • Surfaces • Networks

35. Surfaces Snowdonia National Park, Wales

36. Surfaces Snowdonia National Park, Wales

37. Raster Digital Terrain Models – DTM Digital Elevation Model (DEM) - Njolomole, Malawi

38. Vector DTM’s Triangular Irregular Network - TIN

39. TINS - Surface Significant Points • Eliminate points that are close together and similar – Cuts down on storage requirements. • Those points that cannot be interpolated from their neighbors – Surface Significant. • Surface Significant points are used as vertices in the TIN

41. Modeling Networks Network – “A set of interconnected line features through which material, goods and people are transported. or Along which communication of information is achieved.”

42. Networks Impedance – The cost associated with traversing a network link, making a turn, or stopping.

43. Raster and Vector Data Models

44. Raster and Vector Data Models

45. Thematic Characteristics of Spatial Data aka - Attributes • Gives information about the feature. • Allow certain GIS operations – like “Query”. • Scale of measurement of the attributes is important.

46. Scales of Measurement of the Attributes • Nominal: Assign a label or class to a feature, e.g. 1 is a well, 2 is a catch basin. • Ordinal: Have a rank assigned to them e.g. 1 is light, 2 moderate, 3 heavy. • Interval: Values measured on relativescale e.g. elevations measured from some datum. • Ratio:Values measured on an absolutescalee.g. coordinates or total precipitation.

47. How to Construct a Spatial Data Model • Purpose • Scale • Select features • Adopt a map projection • Select a spatial reverencing system • Annotate

48. What’s Next • Attribute Data Management. • Data Input and Editing.