Angelique's GIS Portfolio

The purpose of this lab was to create a map and tour in Google Earth using layers from a previous ArcGIS Pro lab, the Module 10 Dot Density lab. In order to convert the ArcGIS pro layers from the previous lab into usable files for Google Earth, I used the Layer to KML tool. I converted 3 different feature layers - Counties, Surface Water, and Population - to KML. These layers were then added to Google Earth and placed in a separate file folder for the lab. In order to finalize the dot density map to share with others, I added a legend. To add the legend I created for this project in ArcGIS Pro, I captured the image using the Snipping tool and saved it as a PNG file. I then zoomed into the area I wanted it in Google Earth and used the Image Overlay option under the Add drop down menu. I then scaled and oriented the image as needed. In order to change the order of the layers, I right-clicked the layer and under properties, and changed the Altitude. In order to save the whole map to s

The purpose of this lab was to georeference unknown raster images of the UWF campus to known vector data, digitize new line and polygon features, create multiple ring buffers and overlay data in a 3D environment. To create the first map, I georeferenced two unknown rasters using the Control Points tool. For each raster, I created 10 control points, keepings the RMS error low. For the second raster, I used a 2nd order polynomial transformation for a better map appearance. I then digitized a new line feature for the new campus road and a new polygon feature for the new gym. Finally, I used the Multiple Ring Buffer tool to create a conservation buffer around the eagle's nest that corresponded to FWC requirements of 330 ft and 660 ft. The second map is a 3D overlay of the first map (without the eagle's nest). In order to create the 3D effect I used lidar data from USGS National Map Viewer. To convert the lidar to a DEM, I used the LAS Dataset to Raster tool. I then used the DE

The purpose of this lab was to explore and visualize data in 3D scenes and maps. 3D maps and scenes can be helpful for visualizing the real world. They also allow us to ask and analyze different questions, such as the effect of date and time of date on illumination and shade in an area. Sometimes investigating a certain set of data in 3D allows us to have a different perspective or gain different and new insights that cannot be answered in a 2D setting. Applications for 3D maps are endless, including showing the impact of a new building in an area, realistically displaying a transportation route through a city, over a country or even globally, or even visualizing subsurface features such as wells, pipelines or fault lines. Although 3D maps have wide ranging applications and they suffer from the same pitfalls as 2D maps, navigating them can be initially cumbersome or difficult and sometimes they can be more difficult to interpret initially, depending on the data being displayed.

The objective of this lab was to geocode by address matching and complete a route analysis for EMS station locations in Lake County, FL. For the lab, I downloaded a 2017 US Census Bureau Tiger Line shapefile for Lake County, FL from their web interface. This data was projected to NAD 1983 Harn State Plane Florida East FIPS 0901 Feet using the Project tool. I then created an address locator using the Create Address Locator tool from the Geocoding toolbox. Using this address locator, I mapped or geocoded known EMA station locations from address and zip code. Thirteen of the addresses were matched but there were still 8 unmatched results. Two of the unmatched addresses had possible matches. In order to match the address, I added the street maps basemap and zoomed to the layer to check the matches against the street names and addresses. In order to match the remaining locations, I looked up the addresses in Google maps, found the largest nearby street, used Select by Attributes to locate