Criteria 3--Schools and Registered Daycare Centers

For Criteria 3, I had to define and quantify schools and registered daycare centers in proximity to the preferred corridor. I downloaded the U.S. Census Bureau's TIGER edge files for both counties and used imagery for my basemap. As with every map, I ensured that the GCS and projection were consistent.

I got a little over zealous on determining the schools and daycare centers. I prepared two separate Excel spreadsheets to input my data. Unfortunately, I input ALL schools and daycare centers in both counties from information on the school districts' webpages and a childcare center locator.

After I cleaned the spreadsheets, I save them in .csv format and then created my address locator. When I geocoded the schools, more than half were unmatched and would take an inordinate time to match them using Google Earth and school webpages. As a result, I located the zip codes that were impacted by the corridor and removed all schools (and later daycare centers) that were not in these zip codes. I then geocoded the result and matched any schools that were not matched. I did the same with the registered daycare centers.

Just as in the homes and parcels analysis, there were many schools and daycare centers that were new, had moved, or shut down. I had to use my best judgment when determining their status. In the end, only two private schools were within one mile of the corridor midline and no daycare centers were close. Therefore, no schools or daycare centers met the criteria to be impacted.

Schools and Registered Daycare Centers in Proximity of the Corridor.
The colors are consistent with previous maps. No schools or daycare centers
are impacted by the corridor.

Geocoding

This week's lab taught me quite a bit. Though I am still weening myself from Power Point habits, I was excited to learn some Excel techniques. I wish I had known about these time-saving tools several years ago.

The lab started by converting latitude/longitude (DMS format) into decimal format via Excel. Once I set up my headings in the spreadsheet, I used the extract function to remove specific characters (by Left or Mid, place number, and number of characters) from one cell to another. As with all Excel functions, I was then able to drag the formula down the column, saving time. Once the D-M-S (use a comma for degrees) were extracted, I then converted the numbers into X and Y coordinates (decimal form). Once I added the data to a new project, the eagle nest locations were displayed.

Eagle Nests. Hybrid imagery of Santa Clara County, FL. Green point features are eagle's nests obtained by converting lat/long to X/Y decimal coordinates. The XY Point Data was then added to the layer group to display the locations.

The second part of the lab taught geocoding. To accomplish this, I downloaded census data (TIGER) and addresses from Brevard County Schools. Once the data was placed into Excel, I converted the addresses for input into the address locator function. Using Excel extraction functions and offset functions, I stripped specific data from a cell and moved it to another. Following each operation, I copy/pasted the values only into another spreadsheet (tab at bottom). To remove excess cells (many of the input data took up multiple cells), I used the filter function, which allowed me to select/de-select data within columns and then perform a function (such as delete).

Brevard County Schools. This is a hybrid imagery map of Brevard County, Florida. In this map, yellow outlines are roads and boundaries. The purple school point symbols are Brevard County schools. The data was obtained by downloading standard mailing addresses and transforming the data into a usable format to be geocoded in the address locator. After matching and re-matching the output, the schools were displayed with the school house symbol.

When the addresses were formatted properly (saved in an .xls and .csv format), shapefiles were added (roads and county boundaries) and the projection was changed. I imported the .csv table and created an address locator, which allowed me to geocode. By geocoding, each address was matched to a specific map location. Those unmatched schools were rematched using Google Earth and sometimes visiting the school website. From this analysis, I located the school location, I chose its site on my map. For ease of viewing, I changed my school icons and saved my data.

The link to the above web map is http://arcg.is/ai1vP

All in all, it was a fun lab. I always enjoy learning, especially when I can leverage the new knowledge into future projects (such as the new Excel tools I learned).