1 / 21

Attribute Data

CampusID. Name. Type. Floors. Footprint. 6. Murphy. Academic. 2. 2001. 9. Hopkins. Support. 2. 946. 12. Maintenance. Support. 1. 1848. 15. Hickey. Support. 2. 2367. 17. Shay-Loughlen. Dorm. 3. 1298. Attribute Data. Why Databases?.

Télécharger la présentation

Attribute Data

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. CampusID Name Type Floors Footprint 6 Murphy Academic 2 2001 9 Hopkins Support 2 946 12 Maintenance Support 1 1848 15 Hickey Support 2 2367 17 Shay-Loughlen Dorm 3 1298 Attribute Data CS 128/ES 228 - Lecture 6a

  2. Why Databases? • One of the advantages of vector-based data is that each datum corresponds to a (portion) of a “real” object. • BUT… Objects are more than geographic locations CS 128/ES 228 - Lecture 6a

  3. CampusID Name Type Floors Footprint 6 Murphy Academic 2 2001 9 Hopkins Support 2 946 12 Maintenance Support 1 1848 15 Hickey Support 2 2367 17 Shay-Loughlen Dorm 3 1298 Database “Review” • Databases consist of tables • Each table holds records • Records are in rows • Each record consists of fields, i.e. individual data items • Fields are in columns • Fields that have unique values within a table are called “keys” CS 128/ES 228 - Lecture 6a

  4. Sequential Databases Once upon a time, computer scientists tried to put all the data for an application in one table It didn’t work CS 128/ES 228 - Lecture 6a

  5. Flaws of Sequential Databases • Not all data is homogeneous • Monolithic structure leads to contention problems • Separation of data into “sub” databases leads to duplication (and inconsistencies) CS 128/ES 228 - Lecture 6a

  6. Relational databases • Use many (related) tables of data, with minimal duplication • Tables are “linked” through common values in particular fields • “Queries” permit rich “data mining” CS 128/ES 228 - Lecture 6a

  7. What Color Hair Does Student 234 Have? This is an example of a JOIN operation CS 128/ES 228 - Lecture 6a

  8. Relational Databases in GIS • One table traditionally holds geographic information • Other tables hold data about other attributes • Tables are linked through “Object Ids” • (Object Ids should be independent of the software) CS 128/ES 228 - Lecture 6a

  9. Relational Databases in GIS • Consider a “Buildings” layer • “GIS” data includes location (including coordinate system), symbology, internal bookkeeping • “External” data includes name of building, date built, purpose, etc. CS 128/ES 228 - Lecture 6a

  10. Sometimes they are mixed CS 128/ES 228 - Lecture 6a

  11. Queries • Information is gained by linking tables through “joins” • Queries can involve computed quantities, etc. CS 128/ES 228 - Lecture 6a

  12. Storing Topology • Shapefiles contain no topological information • But topology is important SOLUTION • Store the topology elsewhere CS 128/ES 228 - Lecture 6a

  13. Practicality • GIS must maintain topology (to be useful) • GIS can’t store topology (in shapefiles) • SO, GIS must compute topology CS 128/ES 228 - Lecture 6a

  14. 2 1 B 4 A 10 3 5 9 C 8 D 6 7 Data Structure for Topology Select Boundary Where Zone1=A Ans: 4,5 CS 128/ES 228 - Lecture 6a

  15. C A B Topological Operations • Merge two regions into one …and change the appropriate table CS 128/ES 228 - Lecture 6a

  16. B A C Topological Operations • Split one region into two …and change the appropriate table CS 128/ES 228 - Lecture 6a

  17. Other Topological Operations • Clip an image CS 128/ES 228 - Lecture 6a

  18. Topological Operations • Erase an image CS 128/ES 228 - Lecture 6a

  19. Other operations • Union • Intersect • “Snaps” CS 128/ES 228 - Lecture 6a

  20. How this is used • Find nearest neighbor • Find largest “empty” region CS 128/ES 228 - Lecture 6a

  21. What distinguishes (some) GIS’s • The types of these operations that they can perform. Both Database and Topological CS 128/ES 228 - Lecture 6a

More Related