1. Unit 2. Understanding Geospatial Data Student Learning Outcomes: Students will investigate and understand types of data such as discrete and continuous, and data models such as raster and vector, used to store and analyze this data in a Geographic Information System. Students will add and view data in a GIS application. Students can identify the major software applications used and their uses as well as installation requirements.

2. Understanding Geospatial Data Models

3. Geospatial Data Models Formal means of representing spatially-referenced information Simplified view of physical entities A conceptualization of reality

4. Geospatial Data Models Composed of two parts Object Attributes Reality

7. Types of Spatial Phenomenon Two types of spatial phenomenon Discrete Continuous

8. Discrete Spatial Phenomenon Discrete Individually distinguishable Does not exist between observations Examples: streams and lakes, roads

9. Continuous Spatial Phenomenon Continuous Exist between observations Represent data of a continuous nature Examples: temperature, elevation

11. Spatial Phenomenon typically organized into thematic layers Geospatial Data Models

14. Attributes

15. Attribute Data Record non-spatial characteristics that describe spatial entity Arranged in tables Row = 1 entity Column = 1 attribute Stored in a computer in a flat-file format or a Database Management System (DBMS) ROW COLUMN

16. Position Color Service Date Flow Attributes

17. Attribute Categories Nominal Attributes Provide descriptive information Ex: color, city name, plant type No implied order, size, or other quantitative info May also be images, movies, sounds

18. Attribute Categories Ordinal Attributes Imply a ranking or order by their values Use descriptive or numerical attributes Ex: High/Medium/Low or 100/50/1 Specifies rank only, does not specify scale Ex: High/50 is ordered higher than Low/1, but we do not know by how much

19. Attribute Categories Interval Rank order and magnitude is implied. Does not have a natural zero. Uses an arbitrary zero point instead. Use numerical attributes. Ex: 50°F is 10°F more than 40°F Addition and subtraction make sense, but not multiplication since values are relative from an arbitrary zero.

20. Attribute Categories Ratio Rank order and magnitude is implied. Has a natural zero. Use numerical attributes. Ex: 50MPH is twice as fast and greater than 25MPH Addition, subtraction, multiplication, and division make sense, as the values are absolute from a natural zero.

21. Identify Columns as: Nominal Ordinal Interval/Ratio Identify Columns as: Nominal Ordinal Interval/Ratio IDHeight(ft)TypeClass 115PineMedium 220PineMedium 38MesquiteSmall 430OakTall 1 2 3 4

22. Attribute Data Types Attributes are stored in computer memory. The data type of the attribute needs to be specified for efficient use of memory and determination of operation applicability. There are four typical data types Integer Float/Real Text/String Date

23. Attribute Data Types Integer E.g. whole number Can be used for mathematical calculations However, any resulting fraction of a whole number will be rounded Examples: 1 2458 -54

24. Attribute Data Types Float/Real E.g. decimal number Can be used for mathematical calculations Examples: 1.452 254783.1 -845.157

25. Attribute Data Types Text/String E.g. characters Cannot be used for mathematical calculations Strings can be manipulated, however. e.x. Extract substring Examples: “a” “GIS” “125 Main St.” “9”

26. Attribute Data Types Date Holds date information Cannot be used for mathematical calculations Lengths of time can be calculated, however Examples: 12/10/2010 10/12/10 December 10 2010

27. Spatial Data Models

28. Three common spatial data models Vector Raster Triangulated Irregular Network (TIN)

29. Vector Data Model Defines discrete objects Ex: Fire hydrants, roads, ponds, cadastre 3 basic types of vector data Point Line Polygon Composed of coordinates and attributes

30. Point Uses a single coordinate pair to define location Considered to have no dimension (They may have actual real-world dimensions, but for the purposes of a GIS, no dimension is assumed) Attribute information is attached to the point Ex: Light poles, manhole covers, crime location

32. Line Use an ordered set of coordinates to define location Each line (and curve) is made up of multiple line segments Occasionally, curved lines are represented mathematically Starting point of a line is a node. Intermediate point of a line is a vertex. Attributes may be attached to whole line, or node, or vertex Ex: Road, pipeline, object outlines, powerline

34. Polygon Formed by a set of connected lines Polygons must close. The start and end point must have the same coordinate, or the polygon must close to an adjacent feature Polygons have an interior region Attribute information is attached to the polygon Ex: Lake, city, tree stand, political boundary

36. Spatial Data Models

37. Three common spatial data models Vector Raster Triangulated Irregular Network (TIN)

38. Raster Data Model Represents continuous objects Represents continuous objects Ex: temperature, elevationEx: temperature, elevation Regular set of cells in a grid (matrix) pattern Regular set of cells in a grid (matrix) pattern Real-world objects are represented by value in the grid cell Real-world objects are represented by value in the grid cell Cell dimension Coordinates of cell y x

40. Raster Resolution The cell size is the resolution There is a trade-off between resolution and raster file size The cell coordinate is the center point of the cell The coordinate applies to the entire cell area

41. Raster Resolution (continued) Each raster cell represents a given area and the value assigned applies to the entire cell The raster cell value represents the average, central, most common, or only value covered by the cell

44. GGGGGRGG GGGGRRGG WGGGRGGG GWGRGGGG GWWRGGGG GGWWGGGG GRGGWGGG RGGGWWGG G = Grass R = Road W = Water

46. Spatial Data Models

47. Three common spatial data models Vector Raster Triangulated Irregular Network (TIN)

48. Triangulated Irregular Networks (TIN) A network of triangles connected together to create a 3D surface Triangles do not cross More complex than rasters more efficient space-wise Easily accommodates differing sample density TIN preserves each measurement point

49. Point Edge Face Anatomy of a TIN

52. Document Version: 2012-06-20 In this lab, students will explore and manage geospatial data using a program called ArcCatalog. ArcCatalog is part of the ArcGIS Desktop 10.1 program suite created by Esri. ArcCatalog is similar to Windows Explorer for your geospatial data. ArcCatalog can view data, set properties of that data, manage the metadata for the data, and much more. This lab will contain quite a bit of handholding to help students get started with the ArcGIS Desktop software. It is important that students learn the concepts in this lab as future labs will require the skills covered in this lab. This lab includes the following tasks: Task 1 – Open ArcCatalog and Organize the Workspace Task 2 – Become Familiar with Geospatial Datasets and Data Models Complete lab instructions are included in the following PDF document: Module 2 Lab-1.pdf Access to the Virtual Lab Server is linked here: Del Mar College Virtual Server How to Install Desktop ArcGIS 10.1 Student Edition Module 2 Lab-1.pdfDel Mar College Virtual ServerModule 2 Lab-1.pdfDel Mar College Virtual Server https://delmar.instructure.com/images/play_overlay.png