1 / 23

Chapter 6

Chapter 6. Spatial Joins . Which county has most earthquakes?. County data layer Earthquake data layer No common field between layers. Spatial Joins. A spatial join is based on the location of spatial features rather than common field.

bikita
Download Presentation

Chapter 6

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. Chapter 6 Spatial Joins

  2. Which county has most earthquakes? County data layer Earthquake data layer No common field between layers

  3. Spatial Joins • A spatial join is based on the location of spatial features rather than common field • Spatial join may create new attributes, such as count or distance in the output data

  4. Spatial Join Target layer Join Layer Output Layer

  5. Spatial Join Counties showing the frequency of earthquakes

  6. Spatial Joins Spatial join can be used to find: • The closest feature to another feature. • What features in one layer are inside another feature. • What intersects a feature. Spatial join creates a new layer from two input layers by combining both sets of attributes. However, it does not combine the features to the target layer

  7. Which watershed has the highest number of septic systems? Watershed Septic System

  8. Count field shows the # of septic system in each watershed Color coded Watershed

  9. Two options • How many points are closest to it including the summary statistics of closest points 2. Closest point to the target layer including the distance Spatial Join(Point to point)

  10. Which Hospital is closest to most cities?

  11. Spatial Join(Point to point) Use Option 1 without any summary:

  12. Option 1 add only the Count field in the output layer showing the number of cities that are closest to each hospital Which hospital is the closest to most cities? No distance field in the output layer

  13. Which hospital is the nearest to most cities?

  14. Which hospital serves most people?

  15. Spatial Join(Point to point) Example: Total number of people served by each hospital In this case you have to use Summarized under Option1

  16. Spatial Join(Point to point) Example: Total number of people served by each hospital Summarized option will give summary statistics on each numeric field including the count(# of cities)

  17. This hospital serve most of the cities This hospital serve most of the people Spatial Join(Point to point) Example: Total number of people served by each hospital

  18. Which town is farthest/closest from a hospital?

  19. Use option 2 Which town is farthest/closest from a hospital?

  20. Spatial Join: Point to point-Distance Each town features gets name of closest hospital and the distance. Get the closest or farthest city by sorting the distance

  21. Example: Which counties are within a watershed Same county will fall in more than one watershed, as a result duplication will occus in count and also in summary statistics!!

  22. Spatial join Never use the unprojected data for distance calculation! You will not only get wrong distance but wrong selection as well !!

  23. ?

More Related