1. Lecture 4 Geodatabases

2. Geodatabases Outline  Data types  Geodatabases  Data table joins  Spatial joins  Field calculator  Calculate geometry  ArcCatalog functions 2 INF385T(28437) – Spring 2013 – Lecture 4

3. DATA TYPES Lecture 4 3 INF385T(28437) – Spring 2013 – Lecture 4

4. Directly loadable data types  dBase (.dbf)  Text with comma (.csv) or tab-separated values (.txt)  Microsoft Access (.mdb)  Microsoft Excel (.xls) 4 INF385T(28437) – Spring 2013 – Lecture 4

5. Data table formats  First row must have attribute names with self-documenting labels  (e.g. Pop5To17, Area)  Usual naming convention  first character is a letter  remaining characters be any letters, digits, or the underscore character  All additional rows of a data table contain attribute values  None of the rows can be sums, averages, or other statistics of raw data rows 5 INF385T(28437) – Spring 2013 – Lecture 4

6. Data table formats  dBase field names  Maximum 10 characters 6 INF385T(28437) – Spring 2013 – Lecture 4

7. GEODATABASES Lecture 4 7 INF385T(28437) – Spring 2013 – Lecture 4

8. Geodatabase types Manages features and tables inside a database management system  File geodatabase  stores datasets in a folder of files  each dataset file up to 1 TB in size  can be used across platforms  can be compressed and encrypted for read-only, secure use 8 INF385T(28437) – Spring 2013 – Lecture 4

9. Geodatabase types  Personal geodatabase  stores datasets in a Microsoft Access.mdb file  storage sizes between 250 and 500 MB  limited to 2GB  only supported on Windows  ArcSDE geodatabase  stores datasets in a number of optional DBMSs:  IBM DB2, IBM Informix, Microsoft SQL Server, Oracle, or PostgreSQL  unlimited size and users 9 INF385T(28437) – Spring 2013 – Lecture 4

10. New file geodatabase ArcCatalog 10 INF385T(28437) – Spring 2013 – Lecture 4

11. Import into geodatabase 11 INF385T(28437) – Spring 2013 – Lecture 4 Shapefile features

12. Import into geodatabase  Tables 12 INF385T(28437) – Spring 2013 – Lecture 4

13. Export from geodatabase 13 INF385T(28437) – Spring 2013 – Lecture 4

14. View geodatabases  Cannot identify names in Windows Explorer  Must use ArcCatalog 14 INF385T(28437) – Spring 2013 – Lecture 4

15. Compact geodatabases  File and personal geodatabases  Reduces size and improves performance  Compact personal geodatabases > 250 MB.  Geodatabases with frequent data entry, deletion, or general editing  Open geodatabases in ArcMap cannot be compacted  remove any layers with a source table or feature class in that database from the TOC 15 INF385T(28437) – Spring 2013 – Lecture 4

16. Compress geodatabases  File geodatabases  Once compressed, a feature class or table is read-only and cannot be edited  Compression is ideally suited to mature datasets that do not require further editing  Compressed dataset can be uncompressed to return it to its original, read-write format 16 INF385T(28437) – Spring 2013 – Lecture 4

17. DATA TABLE JOINS Lecture 4 17 INF385T(28437) – Spring 2013 – Lecture 4

18. Data table joins  Putting two tables together to make one table  Join two tables one-to-one by row  Must have the same values and data types 18 INF385T(28437) – Spring 2013 – Lecture 4

19. Join example  Housing heating fuel study for U.S. Counties  Source: U.S. Census  Data table: Census SF3 table for heating fuel by county  Map Features: County polygons 19 INF385T(28437) – Spring 2013 – Lecture 4

20. Data table  Heating fuel table (Excel spreadsheet) 20 INF385T(28437) – Spring 2013 – Lecture 4

21. Data table  Heating fuel table data dictionary  H040001: Occupied housing units: House heating fuel; TOTAL Units  H040002: Occupied housing units: House heating fuel; Utility gas  H040003: Occupied housing units: House heating fuel; Bottled; tank; or LP gas  H040004: Occupied housing units: House heating fuel; Electricity  H040005: Occupied housing units: House heating fuel; Fuel oil; kerosene; etc.  H040006: Occupied housing units: House heating fuel; Coal or coke  H040007: Occupied housing units: House heating fuel; Wood  H040008: Occupied housing units: House heating fuel; Solar energy  H040009: Occupied housing units: House heating fuel; Other fuel  H040010: Occupied housing units: House heating fuel; No fuel used 21 INF385T(28437) – Spring 2013 – Lecture 4

22. Feature class  County polygons 22 INF385T(28437) – Spring 2013 – Lecture 4

23. Add data and features to map 23 INF385T(28437) – Spring 2013 – Lecture 4

24. Open attribute tables  Find common attribute to join 24 INF385T(28437) – Spring 2013 – Lecture 4

25. Data problem  FIPS has leading zero and is a TEXT field.  GEO_ID2 is a NUMBER field with no leading zeros. 25 INF385T(28437) – Spring 2013 – Lecture 4 FIPS 01001 01003 01005 01007 GEO_ID2 1001 1003 1005 1007

26. Data solution  Make a new NUMBER field in Counties attribute table and use field calculator to populate new field from old 26 INF385T(28437) – Spring 2013 – Lecture 4

27. Data solution  New FIPS_NUM is same as GEO_ID2 and ready to join 27 INF385T(28437) – Spring 2013 – Lecture 4

28. Join tables 28 INF385T(28437) – Spring 2013 – Lecture 4

29. Join result  Heating fuel data is now listed for every county in the USCounties feature attribute table 29 INF385T(28437) – Spring 2013 – Lecture 4

30. Permanent joins  Joins are temporary and can be removed  Export data to make joins permanent 30 INF385T(28437) – Spring 2013 – Lecture 4

31. Choropleth map result 31 INF385T(28437) – Spring 2013 – Lecture 4

32. SPATIAL JOINS Lecture 4 32 INF385T(28437) – Spring 2013 – Lecture 4

33. Spatial join example  You have census block group centroids with housing fuel data  You want to know housing fuel data by neighborhoods  No attributes in common  Spatial join needed 33 INF385T(28437) – Spring 2013 – Lecture 4

34. Spatial joins  Points to polygons  Spatially joins points (block centroids) within polygons (neighborhoods)  Joins using “shape” (not attribute field) 34 INF385T(28437) – Spring 2013 – Lecture 4

35. Spatial joins  Right click polygon layer (neighborhoods) 35 INF385T(28437) – Spring 2013 – Lecture 4

36. Join result  New polygon feature 36 INF385T(28437) – Spring 2013 – Lecture 4

37. Join result  Counts and sums 37 INF385T(28437) – Spring 2013 – Lecture 4

38. Count result  Number of points in each polygon 38 INF385T(28437) – Spring 2013 – Lecture 4

39. Sum result  Every block group centroid has associated data  (e.g. H040004, heating electricity shown in labels) 39 INF385T(28437) – Spring 2013 – Lecture 4

40. Sum result 40 INF385T(28437) – Spring 2013 – Lecture 4  One neighborhood example  Central business district  4 block groups  Housing units with electricity fuel (80 + 299 + 128 + 292 )  Sum = 799

41. Choropleth map result (sum) 41 INF385T(28437) – Spring 2013 – Lecture 4

42. Choropleth map result (sum) 42 INF385T(28437) – Spring 2013 – Lecture 4

43. Other spatial joins  Polygons to points  Example: ATM robberies (points) need neighborhood name 43 INF385T(28437) – Spring 2013 – Lecture 4

44. Polygon to point join result  Neighborhood name shows on each point 44 INF385T(28437) – Spring 2013 – Lecture 4

45. Other spatial joins  Points to points  Example: What is the distance of a burglary to the nearest commercial property? 45 INF385T(28437) – Spring 2013 – Lecture 4

46. Point to point join result  Distance to nearest commercial property shows on each burglary point 46 INF385T(28437) – Spring 2013 – Lecture 4

47. FIELD CALCULATOR Lecture 4 47 INF385T(28437) – Spring 2013 – Lecture 4 (as in “Feature-Attribute” Calculator)

48. Sample functions  Performs numeric calculations  Populates field  Concatenates text data 48 INF385T(28437) – Spring 2013 – Lecture 4

49. Field calculator functions  Calculate acres to square miles 49 INF385T(28437) – Spring 2013 – Lecture 4

50. Field calculator functions  Populate field with county name INF385T(28437) – Spring 2013 – Lecture 4 50

51. Field calculator functions  Concatenate house number and street fields INF385T(28437) – Spring 2013 – Lecture 4 51

52. CALCULATE GEOMETRY Lecture 4 52 INF385T(28437) – Spring 2013 – Lecture 4

53. Polygon/point centroids  Advanced calculations for finding a polygon’s point centroid 53 INF385T(28437) – Spring 2013 – Lecture 4

54. Calculate XY fields  Add new X and Y fields in the attribute table INF385T(28437) – Spring 2013 – Lecture 4 54

55. Calculate XY fields  Calculate geometry for X field, repeat for Y INF385T(28437) – Spring 2013 – Lecture 4 55

56. XY field results  Results are X and Y values based on map properties (e.g. Long/Lat or XY feet) 56 INF385T(28437) – Spring 2013 – Lecture 4

57. Export XY coordinates 57 INF385T(28437) – Spring 2013 – Lecture 4

58. Add XY data table 58 INF385T(28437) – Spring 2013 – Lecture 4

59. Export as shapefile  XY events should be exported as permanent shapefile or feature class 59 INF385T(28437) – Spring 2013 – Lecture 4

60. Calculate area  Add area field and calculate geometry INF385T(28437) – Spring 2013 – Lecture 4 60

61. Calculate perimeter  Add perimeter field and calculate script 61 INF385T(28437) – Spring 2013 – Lecture 4

62. Calculate length  Add length field and calculate script 62 INF385T(28437) – Spring 2013 – Lecture 4

63. ARCCATALOG FUNCTIONS Lecture 4 63 INF385T(28437) – Spring 2013 – Lecture 4

64. Basic functions  Copy, paste, rename, etc. 64 INF385T(28437) – Spring 2013 – Lecture 4

65. View and edit properties  Projections, fields, etc. 65 INF385T(28437) – Spring 2013 – Lecture 4

66. View metadata 66 INF385T(28437) – Spring 2013 – Lecture 4

67. Edit metadata 67 INF385T(28437) – Spring 2013 – Lecture 4

68. Create new files  Geodatabases, tables, features, etc. 68 INF385T(28437) – Spring 2013 – Lecture 4

69. Summary  Data types  Geodatabases  Data table joins  Spatial joins  Field calculator  Calculate geometry  ArcCatalog functions 69 INF385T(28437) – Spring 2013 – Lecture 4