Zoom in on the map (below left), and turn off county_roads_sp in order to observe county_roads (below right, projected to NJ SP NAD 1983 “on the fly”) directly underneath.
It is encouraging to see that the projected county_roads_sp shapefile directly overlies the original that was projected “on the fly”.
Repeat the Project (8b) steps above for county_boundary_sp
File > Save your project.
File > Exit ArcMap.
Part II - Geocoding Discussion: In Exr01, you learned how to download and import existing, vector-based (point, line, polygon) data and create new vector data within the GIS. In Exr02, you have learned how to collect, correct, and export Trimble GPS data to a GIS map, as well as how to change projections. Now you will learn how to use geocoding to convert alphanumeric street address data into point shapefiles.
Overview: Geocoding enables the user to transform tables of street addresses into actual points on a map. Those of you who have used Mapquest have seen geocoding in action: you type in an address, and a location is pinpointed on a map. Geocoding is used in many disciplines, including business, health science, criminal justice, nursing, and transportation.
GIS takes a table of input address data (e.g., names and addresses of local businesses) and “compares” those addresses to a “reference table” (aka address locator, usually a TIGER Line features-roads shapefile). The TIGER shapefiles are collections of line segments (usually equivalent to city blocks) defined by addresses at the endpoints of the line segments. For example, to locate 125 Main Street, the GIS finds the line segment whose address endpoints “bracket” 125 Main Street, and then estimates where 125 Main is located on that segment:
est. location, 125 Main