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...

The objective of this week's lab was to explore the concept of dot mapping in which each dot represents a certain amount of some phenomenon. The resulting map shows the 2010 population in South Florida. To create this map, I used ArcGIS Pro and data provided by UWF. I joined an Excel table of 2010 US census population data to a feature class of the South Florida counties and applied Dot Density Symbology. In order to exclude surface water areas from the dot density map, I applied a masking effect using a surface water feature class. To more accurately display the dot density in the areas outside the surface water, I clipped the county population with an urban land feature class. I included and labeled 4 major cities to provide geographic reference to the map. In addition, I uniquely symbolized the surface water by type. I then adjusted the dot size and dot value to find suitable values where the densest areas are just beginning to coalesce. In order to create the visual legend, ...

The purpose of this week's lab was to explore the most common modeling tools in ArcGIS - buffer and overlay - and create a script in ArcPy for the buffer tool to combine or exclude multiple vector features. The resulting map includes final possible campsite areas, after applying the overlay tools.   First, I used the Buffer tool to create a feature class with a fixed distance. The resulting feature class included areas within 300 meters of roads, dissolving all buffer borders so that areas of overlap were merged.  Next, I created a feature class with a variable distance from the water features (150 m for lakes and 500 m for rivers). To do this, I added a field to the attribute table of the water feature that included the desired buffer distance for each feature type, and then I used the Buffer tool with these fields as the buffer distance and dissolve type. I also used ArcPy to create a script to use the Buffer tool to create feature classes with variab...

The purpose of this lab was to explore the design concepts involved with flowline mapping. For this lab, I used Adobe Illustrator to create a flowline map of immigration to the U.S. using data from the U.S. Department of Homeland Security.  I chose to create my flow map where the choropleth map of immigration per U.S. state is overlaid on the world map.  I chose this option because it saved space on the map layout. In addition, I preferred keeping the continents in place to more accurately show the layout of the world and its relation to immigration to the U.S. (although the map does not aim to show the actual paths of immigration, just the percent from each region). I also chose this option because shows where the U.S. is located in relation to the other regions. Even though this option made it slightly more difficult to see the choropleth map, enlarging the whole map made the choropleth map easier to see. I then created proportional flowlines from each region t...