1. Getting the Map into the Computer Lecture 4 Introduction to GISs Geography 176A Department of Geography, UCSB Summer 06, Session B

2. Getting the Map into the Computer 4.1 Analog-to-Digital Maps 4.2 Finding Existing Map Data 4.3 Digitizing and Scanning 4.4 Field and Image Data 4.5 Data Entry 4.6 Editing and Validation

3. GIS maps are digital not analog Maps have a communications function but... A map has a storage function for spatial data Somehow, the visually “stored” data must get digital Real and Virtual maps

4. GIS Data Conversion Traditionally most of the cost of a GIS project One time cost Depends on reuse Requires maintenance

5. Finding Existing Map Data Map libraries Reference books State and local agencies Federal agencies Commercial data suppliers e.g. GeographyNetwork.com, Rand McNally, Thompson, NAVTEQ, maps.com

6. Existing Map Data Existing map data can be found through a map library, via network searches, or on media such as CD-ROM and disk. Many major data providers make their data available via the World Wide Web, a network of file servers available over the Internet. GIS vendors package data with products.

7. Commercial vendors

8. Federal Data Agencies U.S. Geological Survey (USGS) National Oceanic & Atmospheric Administration (NOAA) Census Bureau National Geospatial-Intelligence Agency (NGA) Environmental Protection Agency (EPA) many more...

9. National Spatial Data Infrastructure http://www.fgdc.gov/nsdi/nsdi.html

10. Geodata.gov

11. National Spatial Data Clearinghouse

12. USGS: National Mapping

13. National Map Viewer

14. DOQQ plus DLG streets

15. DRG plus DLG streets

16. NLCDB plus DLG streets

17. Seamless data download

18. Other components of the NSDI (Portals, standards, services, data) Geospatial Onestop Geography Network EROS Data Center FGDC: Standards Alexandria Digital Library State data centers e.g. Teale in CA MapQuest NAVTEQ, etc. Counties, municipalities, universities, tribes, etc.

19. U.S. Bureau of the Census

20. NOAA Weather and other data

21. Distributed active archive center Sioux Falls, SD Operated by USGS Eros Data Center

22. US GeoData ftp access to DEM DLG GNIS GIRAS etc.

23. GNIS Feature locations

24. GIRAS Land Use and Land Cover Data

25. GIRAS into Arc/Info (GIRASARC)

26. Terrain data DEM DLG Contours DCW Contours

27. Your Spatial Data “Rights” US Federal – FOIA – COFUR State (e.g. California, Teale Data Center) Local (e.g. Portland, OR Metro) Other countries Protection for security Steganography, watermarks, deliberate error Attributes vs. map data

29. CORONA (KH Satellites) Goleta, CA, 1967 Image

30. GIS data can be: Purchased Found from existing sources in digital form Captured from analog maps by GEOCODING

31. GEOCODING Geocoding is the conversion of spatial information into digital form Geocoding involves capturing the map, and sometimes also capturing the attributes Necessarily involves coordinates Often involves address matching

32. GEOCODING LEAVES A “STAMP” ON DATA The method of geocoding can influence the structure and error associated with the spatial information which results Example: scanning (raster), digitizing (vector)

33. Hand out the Attendance Sheet, U idiot!!

34. Geocoding methods for maps Digitizing Scanning Field data collection

35. Digitizing Captures map data by tracing lines from a map by hand Uses a cursor and an electronically-sensitive tablet Result is a string of points with (x, y) values

36. The Digitizing Tablet

37. Digitizing Stable base map Fix to tablet Set coordinate system Digitize control points Determine coordinate transformation Trace features Proof plot Edit Clean and build topology

38. Digitizing Cursor data entry Secondary tablet (menu/template) Voice command entry Point mode Stream mode (one point / time unit) Distance mode (one point / distance unit)

39. Selecting points to digitize

40. Some common digitizing errors Slivers Duplicate lines Duplicate nodes Unended lines Gaps Zingers

41. Scanning Places a map on a glass plate, and passes a light beam over it Measures the reflected light intensity Result is a grid of pixels Image size and resolution are important Features can “drop out”

42. Scanning Flat bed Drum DPI File size

43. Scanning example This section of map was scanned, resulting in a file in TIF format that was bytes in size. This was a file of color intensities between 0 and 255 for red, green, and blue in each of three layers spaced on a grid 0.25 millimeter apart. How much data would be necessary to capture the features on your map as vectors? Would it be more or less than the grid (raster) file? 15 x 15 cm (3.6 x 3.6 km) grid is 0.25 mm ground equivalent is 6 m 600 x 600 pixels one byte per color (0-255) 1.08 MB

44. On-screen digitizing

45. Isolate layer and capture

46. Resolve errors

47. Automatic Raster-to-vector

48. Rasterization problems

49. Feature vs. Text

50. Field data collection

51. GPS navigation/tracks

52. Attribute data Logically can be thought of as in a flat file Table with rows and columns Attributes by records Entries called values

53. Address Matching Most GISs contain capability Start with 123 Main St, Santa Barbara, CA 93101 End with Coordinates May need to interpolate along blocks Street number range, left and right side e.g. 101-199

54. Database Management Systems Data definition module sets constraints on the attribute values Data entry module to enter and correct values Data management system for storage and retrieval Legal data definitions can be listed as a data dictionary Database manager checks values with this dictionary, enforcing data validation

55. Database elements Type of value Range Missing data Duplicate data Key

56. The Role of Error Enforcement for map data is usually by using topology Map and attribute data errors are the data producer's responsibility, but the GIS user must understand error Accuracy and precision of map and attribute data in a GIS affect all other operations, especially when maps are compared across scales

57. Coming next …. What is where?