1. CE 250 - Introduction to Surveying and Geographic Information Systems Donald J. Leone, Ph.D., P.E. eLearning Version Lecture 3

2. Introduction What are databases and database management systems (DBMS)? What is a relational data base model? How are databases linked with GIS? How do we get paper maps into the computer? How can we edit and convert data?

3. Databases Spatial Data – “Where things are” Attribute Data – “What things are” Attribute Data – Stored in databases Def: Database – “A set of structured data – usually in table form”, or “ A Collection of related data”

4. Traditional Database Example

5. Traditional Databases Some Problems Duplication of Data High Maintenance Costs Data Sharing Difficulties Lack of Security and Standards

6. Computer Based Databases Different data access methods will be available. Are independent of application. Unnecessary duplication of data – minimized. Access controlled and centralized. Maintaining and Updating relatively easy. Can ask questions - “query”

7. Database Approach Data Application Database Management System Database DBMS Hotel Booking Travel Arrangements Ski School Booking

8. Database Management Systems Functions File Handling/management Adding/deleting/updating records Extraction of data (sorting, querying) Maintenance (security, backup) Application building

9. Data Base Table PINOwnerAddress Sale Date Acres Zone Code Zoning P101Wang 101 Oak St. 1-10-98 1.0 1Res. P101Chang 200 Maple St. 1-10-98 1.0 1 Res. P102Smith 300 Spruce Rd. 10-6-68 3.0 2 Com. P102Jones 100 Ash St. 10-6-68 3.0 2 Com. P103Costello 206 Elm St. 3-7-97 2.5 2 Com. P104Smith 300 Spruce St. 7-30-78 1.0 1 Res.

10. Separate Data Tables – A Relational Database PIN Owner name Zone Code

11. Creating a New Table JOIN Key Field

12. Joined Table PINOwnerAddress P101Wang 101 Oak St. P101Chang 200 Maple St. P102Smith 300 Spruce Rd. P102Jones 100 Ash St. P103Costello 206 Elm St. P104Smith 300 Spruce St.

13. Creating New Tables – “The Query” Standard Query Language – SQL Generate New tables Advantages: Completeness, Simplicity Style, Wide Application Disadvantages: Slow, Difficult to implement Can’t Handle geographic concepts, i.e. “near to”

14. Parcel Table PIN Sale Date Acres Zone Code P101 1-10-98 1.0 1 P102 10-6-68 3.0 2 P103 3-7-97 2.5 2 P104 7-30-78 1.0 1 “Which Parcels (PINS) have 2 or more acres?”

15. Create a New Table Using SQL Query: “Acres” =>2.0 Result: PIN Sale Date Acres Zone Code P102 10-6-68 3.0 2 P103 3-7-97 2.5 2

16. Creating a Database 1. Data Investigation – Fact finding. Define Tables. 2. Data Modeling – Relationships between entities and attributes – Define Tables. 3. Database Design – Fit data modeling to software at hand. 4. Database Implementation – Filling in the actual data.

17. Data Modeling Entity Attribute Modeling (EAM) 1. Identification of Entities 2. Identification of the Relationship between entities (1:1, 1:M, M:1, M:N) 3. Identification of the Attributes of the entities 4. Development of the Tables

18. EAM for Ski Resort 1. Entitles – Hotels, Travel Companies, Ski Schools, Visitors 2. Relationships a) Many visitors stay at One hotel (M:1) b) One Travel Co, organizes for Many visitors (1:M) c) One Ski School teaches Many visitors (1:M) d) Different Travel Co.s may use Different Ski Schools (M:N)

19. EAM Diagram N a) Many visitors stay at One hotel (M:1) b) One Travel Co, organizes for Many visitors (1:M) c) One Ski School teaches Many visitors (1:M) d) Different Travel Co.s may use Different Ski Schools (M:N) a c d b

20. Attributes of the Entities HOTEL (Hotel ID, Name, Other Attributes) TRAVEL CO. (Travel Co. ID, Travel Co. Name, Other Attributes) SKI SCHOOL (Ski School ID, Ski School Name, Other Attributes) VISITOR (Visitor ID, Visitor Name, Hotel ID, Travel Co. ID, Ski School ID, Other Attributes) LINK (Travel Co. ID, Ski School ID)

21. Ski Resort Tables

22. Linking Spatial and Attribute Data

23. Database Applications Single User/PC Large Corporate Databases Large Computers Control Access Manage Data Security Different Sites Simple Software

24. Little Grey Cells Quiz SQL stands for standard question link. T or F One of the functions of a DBMS is to allow several applications access to the data. T or F Give one advantage of a computer database over a “traditional” database.

25. Break!

26. Getting the Data Into The Computer Data Input (Encoding) and Editing ANALOG DIGITAL What is data encoding? How are paper maps digitized? How are paper maps scanned? Methods of Data Editing and Conversion

27. Data Capture Editing/Cleaning Re-Projection Generalization Edge Matching and Rubber Sheeting Layering Maps Satellite Data Digital Data Tabular Data Soft Ideas Digitizing Scanning Data TransferKey Coding Integrated GIS Database Data Editing Data Encoding Methods

28. Data Encoding Methods Digitizing Tracing over a map with a cursor. Mechanical Device with a Human Operator. Most errors operator induced. Produces A Vector Map.

29. Data Encoding Methods Scanning Some problems with scanning (automatic digitizing) Distortion. Automatic scanning of unwanted images. Produces a raster image- can be vectorized with some problems. Amount of editing required to produce suitable spatial data.

30. UT Hall HJG Center Sports Center University of Hartford Aerial Photo Ground Truthing Points

31. Scanning Original Paper Map Scanned Image

32. Data Encoding Methods Electronic Data Transfer What data exist? How much they cost? What format will it be in? Pay off – Considerable time and effort saved !

33. Data Editing Methods Detecting and Correcting Errors Missing or Duplicate Features Mislocated Features Missing or Duplicated Labels Unwanted Results of Digitizing or Scanning Noise

34. Errors in Vector Data

35. Errors in Raster Data Noise Original “noisy” data 3 x 3 Mean Filter 9 x 9 Mean Filter

36. Producing a Common Reference Re-Projection Transformation Generalization

37. Producing a Common Reference Re-Projection All data needs to be referenced to the same projection.

38. Trying to Overlay Different Projections Cylindrical Conic

39. Producing a Common Reference Re-Projection All data needs to be referenced to the same projection. Transformation All data needs to have the same origin.

40. Producing a Common Reference Re-Projection All data needs to be referenced to the same projection. Transformation All data needs to have the same origin. Generalization All data needs to be set to the same scale.

41. Remaining Problems After Re-Projection, Transformation, and Generalization Edge Matching

42. Remaining Problems After Re-Projection, Transformation, and Generalization Rubber Sheeting

43. An Integrated Database Ski Resort Example Layer NameSourceData Model InfrastructureScanned – 1:5000 Raster HotelsSurvey DataVector Ski SchoolsSurvey DataVector Weather StationsGPS DataVector

44. An Integrated Database Ski Valley Example Layer NameSourceData Model RoadsDigitized 1:25000Vector Ski TrailsDigitized Aerial Photos Vector Ski Resort Boundary Digitized 1:25000Vector TopographyFile Transfer 1:25000 DTM Vector/Raster Land UseSatellite ImageRaster

45. Summary What are databases and data base management systems (DBMS)? What is a relational data base model? How are databases linked with GIS? How do we get paper maps into the computer? How can we edit and convert data?

46. What’s Next Up to now – Data Formation Data Analysis – Decision Making