Spatial Join Counties showing the frequency of earthquakes
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
Which watershed has the highest number of septic systems? Watershed Septic System
Color coded Watershed Count field shows the # of septic system in each watershed
Spatial Join (Point to point) 2. Closest point to the target layer including the distance Two options 1.How many points are closest to it including the summary statistics of closest points
Which Hospital is closest to most cities?
Spatial Join (Point to point) Use Option 1 without any summary:
Which hospital is the closest to most cities? No distance field in the output layer 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 nearest to most cities?
Which hospital serves most people?
Spatial Join (Point to point) Example: Total number of people served by each hospital In this case you have to use Summarized under Option1
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)
Spatial Join (Point to point) Example: Total number of people served by each hospital This hospital serve most of the cities This hospital serve most of the people
Which town is farthest/closest from a hospital?
Use option 2
Each town features gets name of closest hospital and the distance. Spatial Join: Point to point-Distance Get the closest or farthest city by sorting the distance
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!!
Spatial join Never use the unprojected data for distance calculation! You will not only get wrong distance but wrong selection as well !!