Module 7--Google Earth

Google Earth Map of South Florida Showing Hydrology and Population Density

This was the final lab of this course. Google Earth was much easier to use than in the last course. The overall operations of the lab were very easy and straightforward. Once I created a new map in ArcGIS Pro and added a feature class, I exported the layer to a .kmz file using the "Layer to KML" tool in ArcGIS Pro. The only issue I had was that because I use the virtual desktop, I had to package the .kmz files into a zip folder and then send them to my desktop.

I then ensured all layers were exported to Google Earth Pro in accordance with the lab instructions. In order to add the files to Google Earth, I used File>Open>click on .kmz file. This placed the file in a temporary folder, which I moved to a new folder in My Places.  I was able to drag each feature to change the order, but this did not change the drawing order. In order to change the drawing order so that the dots were the highest (lab requirement), I right clicked the feature, chose Properties, and then adjusted altitude. I used absolute and adjusted the dots to be higher than the county boundaries (which I placed above ground level so they wouldn't blend in so much). The hydrology features did not have the altitude option, of course.

To create the legend, I imported a .png file by using the Add menu and selected Image Overlay. In order to properly size and position the legend, I had to move several bright green marks, which I complete through trial and error. I then saved the .kmz file onto my desktop.

The second part of the lab was to create a Google Earth recorded tour of specific areas in South Florida. This took some practice in order to smoothly move from one location to another at a specific location and perspective.

The first step was to add place marks by clicking on the yellow push pin icon above the map, I then renamed it and moved it while the properties window was open. You cannot move the place mark when the properties window is closed. 

Once all the place marks were positioned and the view was the way I wanted it, I pressed the record icon (looks like video camera at top of map), clicked the red button and moved from place to place until I visited all my place marks. Again, it took numerous trials to make the tour flow smoothly and correctly. Once I was complete, I saved the recording (icon in popup), moved the recording to an appropriate place with the rest of its layers, and then saved the entire group by right click the group, Save Places As, and then named it and ensured it was saved on my desktop.

This was a very fun lab to complete and gave me more confidence with Google Earth. 

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).

Google Earth

After collecting the data in Collector, the lab required me to share the data as a Google Earth file and an ESRI map package. I created two .kml files (.kmz if in zip format)--one from ArcGIS Pro and one from ArcGIS Online. This was very easy, but the files were much different in size and in the way the data was portrayed.

I imported both .kml files to Google Earth Pro (online). I was unable to display the files simultaneously, but I could toggle between both files. As with all Google Earth applications, the output was beautiful and I could pin the data for others to see.

I also created a map package to share a map with someone not connected to the network. This operation was very easy, to include the synchronization between ArcGIS Pro and ArcGIS Online. This is a very powerful tool in the event that someone does not have access to these programs, which are very expensive.

All in all, I really enjoyed this lab and look forward to building my knowledge base further.