1. 3D Analyst

3. 3D Scenes

4. Triangulated Irregular Network Triangulated Irregular Network (TIN) Structure Defined by two elements: a set of input points with x,y, and z values, and a series of edges connecting these points to form triangles. Each input point becomes the node of a triangle in the TIN structure, and the output is a continuous faceted surface of triangles.

5. Resultant TIN

6. TIN Zoomed

7. Drape Features to TIN

8. Extrude 3D Features 3D buildings includes 3D heights

9. Buildings draped to TIN and extruded

10. Observer and Target Locations Target

11. Observer and Target Locations Observer

12. Navigate a Scene Navigate button

13. Flythrough a Scene Choose Fly button and slowly move mouse Left mouse: increases speed Right mouse: decreases speed ESC: stops flight

14. 3D Symbols Start with 2D point symbols (street trees)

15. 3D Symbols Add layer and display (drape) in ArcScene

16. 3D Symbols Swap with 3D Symbol

17. 3D Symbols Resultant layer with 3D symbols

18. Line of Sight Analysis Lines showing visibility (green) and obstruction (red)

19. ArcGlobe

20. Other 3D Examples Steepest-path analysis Flow of liquid from a certain point

21. Elevated Blood Level Example

22. Other 3D Examples 3D Representation of Land Value Totals by Tax Map Grid, Concord, North Carolina, USA

23. Other 3D Examples North Macadam Development Concept—Floor Area Ratio Massing Study, City of Portland Bureau of Planning.

24. Spatial Analyst

25. Poverty Risk Model

26. Model for Risk Index Poverty study looking at multiple criteria Population below poverty income line Female headed household with children Population with less than HS education Workforce who are unemployed Improper linear model for poverty Calculate Z-score values - Data selected by subtracting the mean and dividing by the standard deviation for above variables, then averaging them

27. Risk Model Base Layers Block Groups NoHighSch2 (ho high school degree) Male16Unem (males in workforce who are unemployed) Poverty (population below poverty income) Blocks FHH (female headed households with children)

28. Why Spatial Analyst? Study needs a large scale analysis - block level Pittsburgh has 7,466 blocks - Difficult to use vectors at different scales - Best to use block centroids Need a different type of map - raster map - deals with continually changing variables

29. Spatial Analyst Primary Features Data analysis Allows rapid generation of maps that are based on complex statistics Surface modeling Creates predicted surface (grid maps) from unmeasured points based on statistical analysis of measured points

30. Raster Maps Rectangular arrays of very small, uniform squares analogous to pixels in an image file - Cells are uniform and not dependent on original vector size (e.g. tracts, block groups, blocks) Value in a cell (e.g. population, other census variables)

31. Kernel Density Smoothing Point shapefiles of census block centroids Produces a smoothed, mean surface for the designated values Two parameters - Based on map scale and detail level - Cell Size - Search radius

32. Risk Model Base Layers Difficult to represent using vectors

33. Kernel Density Layers Create kernel density layer for first input FHH by blocks

34. Poverty Index Model Poverty Index Model with one layer

35. Kernel Density Results

36. Kernel Density Layers Create kernel density layer for second input NoHighSch by block group

37. Kernel Density Results

38. Other Layers

39. Calculate Statistics Improper or Unweighted Linear Model Robyn Dawes, “The robust beauty of improper linear models in decision making,” American Physcologist, Vol 34, pp 571-582 Calculating Z-score values Data is scaled by subtracting the mean and dividing by the standard deviation) for the above-mentioned variables and averaging them.

40. Map Algebra

41. Model with all variables

42. Resulting Poverty Map

43. FOOD BANK Student Project

44. Non-profit organization, Duquesne, PA Collects and distributes 18 million pounds of food per year to over 350 member organizations - Soup kitchens - Food pantries - Shelters - After school programs - Senior high rises, etc. Greater Pittsburgh Community Food Bank

45. Food Bank Research Question Are our distribution locations in areas of need? Advanced GIS spatial analyst tools used 8 U.S. Census variables - Combined to form the single, composite indicator layer - Scale based on the combination of un-weighted Z-scores (mean and standard deviation) of each factor

46. High Risk Poverty “Hot Spots” Low Risk Medium Risk High Risk

47. “Hot Spots” and Distribution Centers Low Risk Medium Risk High Risk 1,500’ Buffer Zone

48. Extract Raster Value Points Extraction Toolset Extracts raster value (high/low risk) to points (distribution locations)

49. Member Agencies Serving High Risk Areas

50. Member Agencies Serving High Low Areas

51. Other examples Presidential Election Maps -Compares variables of likely voters Heart Attack Prediction Model -Actual heart attacks (data from 911) -Likely candidates (census data) Others?

52. Network Analyst

53. Solves a variety of problems based on geographic networks including: Routing - Most efficient travel routes Service Areas - Territories based on travel time Closest Facilities - Closest vehicle or service facility to an incident Driving Directions

54. Routing

55. Shortest vs. Fastest Paths

56. Service Areas / Closest Facilities

57. Areas within a Distance 10 minute walking distance of different bus stops (service area and network) and which bus routes (find best route) are serviced by the stops.

58. Other GIS Tools

59. Advanced Visualization Tools - Helps view, project, analyze, and understand potential alternatives and impacts via visual exploration and alternative scenarios - Experiments with hypothetical scenarios, challenge assumptions on the fly - Encourages participation and collaboration by engaging users and public audiences via visualization and interactive participation.

60. Community VIZ Community VIZ http://www.communityviz.comhttp://www.communityviz.com

61. Criterion Planners INDEX http://www.crit.comhttp://www.crit.com

62. TerraSim, Inc. CMU Spin-off TerraTools 3D GIS Visualization Software http://www.terrasim.com/ Transforms raw cartographic and GIS data into complex 3D visualizations suitable for real-time driving or flight simulation. Easy-to-use interface for its powerful terrain and feature generation tools, enabling users to rapidly construct complex geospecific virtual worlds without tedious manual modeling.

63. Defense Modeling and Simulation

64. Intelligence Preparation

65. Civil Engineering

66. Schenley Park

67. Parametric Bridge Models

68. CMU Campus

69. Extension Review GIS Extension Overview Free Add On Applications Analysis based extensions - 3D Analyst - Spatial Analyst - Network Analyst Other GIS Tools