Geographic Information Systems : Data Types, Sources and the ArcView Program

1. Geographic Information Systems :Data Types, Sources and the ArcView Program

2. Overview • Lecture (50 min) • Review • Spatial Data • Shapefiles, Images, Grids, TINs • Relational Databases • Links and Joins • What is ArcView • Scale and Resolution • Break (15 min) • ArcView Intro Lab (75 minutes) • Homework Assignment

3. GIS: Simplified (Review) • A computer-based tool for mapping and analyzing things. • Geospatial Database: a set of compatible data layers or themes

4. Digital Hydrologic / Hydraulic Processing (Review) HEC-RAS Water surface profiles HEC-HMS Flow discharge HEC-GeoHMS HEC-GeoRAS ArcView Digital Elevation Model ArcView Flood plain maps Digital Map Database

5. GIS: Analysis (Review) • Why should spatial data be stored in a GIS? • Want to use the power of the computer to ask queries of the spatial data • Analyze data and produce new information • Convey technical data non-technically

6. GIS Data Types Discrete Space: Vector Data -- Shapefiles Continuous Space: Raster Data -- Grids -- TINs (Triangulated Irregular Networks) -- Images

7. Vector Data: Types Vector data are defined spatially as either: (x1,y1) Point - a pair of x and y coordinates vertex Line - a sequence of points Node Polygon - a closed set of lines

8. Sample Point Shapfile: Water Right Locations A “point” shapefile Each data point has a specific x,y coordinate pair

9. Sample Line Shapefile: River Reaches Each “line” consists of two nodes and a series of vertices

10. Sample Polygon Shapefile: River Basins A closed set of lines illustrating the watershed or drainage area for a corresponding river reach

11. Types Combined

12. Cell size Number of rows NODATA cell (X,Y) Number of Columns Spatial Data: Grid (Raster)format Raster data are described by a cell grid, one value per cell:

13. NEXRAD Rainfall Intensity Image October 18, 1994 @ 3:00 AM (CST)

14. NEXRAD Rainfall Intensity Image October 18, 1994 @ 4:00 AM (CST)

15. DEM Close Up

16. Raster – Vector Model

17. Raster and Vector Data Vector Raster Point Line Zone of cells Polygon

18. Points as Cells

19. Line as a Sequence of Cells

20. Polygon as a Zone of Cells

21. Image Data and Vector Overlays • Image data is nothing more than a properly placed picture. Actually made of pixels of a certain cell size much like raster data. • Smaller the cell size – the more refined the resolution – the sharper the picture • Vector representations are often traced from a “base” image map Reservoir and Highway

22. Image Data and Raster Overlays • Samples attributes at fixed intervals • List of numbers, one number per cell Reservoir and Highway

23. Triangulated Irregular Network(TIN) Outside Channel: Raster DEM Inside Channel: Vector cross-sections Triangular mesh of (x,y,z) points Triangles as elements Result: TIN of channel and landscape

24. Three-Dimensional View of a TIN (Clear Creek and Cowarts Creek Confluence)

25. Hydrologic Cycle Atmospheric water Surface water Subsurface water Connecting processes in the hydrologic cycle involves linking spatial features of various kinds

26. Section Summary • Four types of GIS data: • Shapefiles (point, line, polygon) • Grids • TINs • Images • A real-world region can be considered spatially discrete or spatially continuous • Discrete space is represented by features in vector data(shapefiles) and continuous space by elements or cells inraster data (grids) • Both vector and raster data are required to represent the real-world in the digital GIS world  Raster-Vector model

27. Overview • Lecture (45 min) • Review • Spatial Data • Shapefiles, Images, Grids, TINs • Relational Databases • Links and Joins • What is ArcView • Scale and Resolution • Break (15 min) • ArcView Intro Lab (75 minutes) • Homework Assignment

28. GIS: Data Entry and Storage • Store data in a logical way • Maps and data are stored in digital form • Digital layers with attributes attached • Layers are stored together in a relational database using a database management system (DBMS).

29. Attributes • GIS stores more than just maps • Relationship between map features and attributes within a GIS • Dynamic interactive maps

30. DBMS Database Management System • Inside the DBMS, spatial data is stored as digital layers with their associated attributes

31. Levels of Analysis:Relational Database Relational Linkages Spatial Attributes Water Right Locations Descriptive Attributes

32. Feature Attribute Table (Vectors) Fields Records

33. Value Attribute Table (Grids) Attributes of grid zones

34. Linked Tables

35. Query Builder - find all countries with pop > 1 million people

36. Edit Join Link Tables: Edit, Join and Link

37. Relationships in Linking and Joining Tables Source Table (new information to be added) Destination Table (existing information) Many to one relation Primary Key field (each record must have a unique value) Relate field (can have one or many records for each value)

38. Concept Summary • All GIS data files have descriptive attributes in a data table associated with each file • Feature attributes (associated with vector files) form the basis for data analysis of these files • Value attributes (associated with grid files) form the basis for continuous representation of data across a surface (precipitation, elevation, etc) • Attribute tables can be linked or joined to related tables using a key field

39. What is ArcView? • Desktop geographic information system (GIS) from ESRI • Uses scripting language called Avenue • Customize GUI • April 20, 2002 – ArcGIS released

41. Geographic Features

42. Feature Attributes

43. Feature Attributes

44. Feature Attributes

45. Overview • Lecture (45 min) • Review • Spatial Data • Shapefiles, Images, Grids, TINs • Relational Databases • Links and Joins • What is ArcView • Scale and Resolution • Break (15 min) • ArcView Intro Lab (75 minutes) • Homework Assignment

46. Soil Map of TNRCC Management Segment 841 Lower West Fork Trinity River

47. 30 m DEM of Lower West Fork, Trinity River Both regions and features can be represented using elements