GIS4043 - Final Project - FPL Bobwhite_Manatee Transmission Line

Overview FPL Bobwhite-Manatee Proposed Transmission Line

Our final task was to analyze a proposed transmission line corridor from Florida Power and Light (FPL).

Our four main objectives for this analysis are to:

1. Define and quantify environmentally sensitive lands imposed by the transmission line.

We will utilized data provided by the National Wetlands Inventory to determine wetlands and uplands impacted by the corridor as well as data provided by the Florida Natural Areas Inventory.

2. Quantify homes within the proximity of the transmission line.  We will use aerial images of Manatee and Sarasota counties to digitize residences located within the corridor as well as those located within a 400 foot buffer surrounding the corridor.   We will also provide a count of the total parcels affected by the corridor and buffer in both counties.

3. Define schools and daycare centers within proximity of the transmission line corridor and 400 foot buffer zone.   School and daycare data retrieved is from the University of Florida GeoPlan Center.

4. Quantify the length of the transmission line.  (I did not choose to show the optional engineering cost associated with this transmission line).

The Bobwhite-Manatee proposed transmission line placement is acceptable and feasible based on the chosen project objectives and criteria.

It avoids large areas of environmentally sensitive lands.   No private conservation lands are impacted by the transmission line corridor. 164 Acres – Local and State Conservation Areas Impacted By Proposed Corridor

91 Acres – Heritage Ranch Conservation Easement (Local)

63 Acres – Lake Manatee State Park (State)

10 Acres – Lake Manatee Lower Watershed

914 Acres – Wetlands (National Wildlife Inventory) – 5% of wetlands in Study Area

5,652 Acres – Uplands (National Wildlife Inventory) – 5% of uplands in Study Area

It has relatively few homes in close proximity.  It is estimated that less than fifty homes would be impacted by the proposed transmission line.   Thirty-five homes in Manatee County and eleven homes in Sarasota County resided either directly in the corridor or within the 400 foot buffer surrounding the corridor.   

It avoids schools and schools sites including daycare centers.  No schools or daycare centers fall within either the corridor or the 400 foot buffer surrounding the corridor.  Sprouts Child Development Center is the closest in proximity, located less than one-fourth a mile from the 400 foot buffer zone and less than one-third of a mile from the proposed corridor.

The transmission line is approximately 25 miles in length.

GIS4043 Final Project Power Point Presentation

GIS4043 Final Project Presentation Slide Notes

GIS4043 - Week 13 - Georeferencing

MAP1: Georeferenced Buildings On And Eagle's Nest Near UWF's Campus

Difficult to believe this is our final lab assignment for GIS4043!  This week's lab was primarily focused on Georeferencing.   Georeferencing is used to align an unreferenced aerial photograph with an already referenced control layer.  In Section 1, we were provided two unreferenced aerial photographs of UWF's campus, uwf_n.jpg and uwf_s1.jpg representing the northern and southern parts of the main campus.   Our two referenced layers were a campus roads layer (UWF_roads) and a campus buildings layer (Buildings).  We then worked on referencing the North Campus layer using the Add Control Points tool to identify 10 common points on the target layer and on the already referenced control layer.  I went through this process a few times before I learned that the key was zooming and trying to select as close to the exact same spot on the unreferenced layer and the referenced layer.   Using the View Links Table we could see our Root Mean Squared (RMS) Error value which had to be less than 15.  I selected 10 common points using a 1st order transformation and a RMS Error of 6.71.   These 10 points then allowed us to "Update" georeferencing and provide a spatial reference for the North Campus layer (uwf_n.jpg).  It took me a few trials to get more proficient at adding control points with accuracy.  The second part of Section 1 of the lab had us georeference the southern part of the campus.  After we used 1st order transformation to create at least 6 common links we then changed the transformation to 2nd order.   After creating 10 common links we could change the transformation to 3rd order.  Higher transformation orders allow the raster image to "bend and warp" more.   Ideally you want to select the transformation order that presents your image most accurately.  I chose to use a 2nd order transformation and had a RMS Error of 1.70.

In Section 2 of the lab we learned how to use the Editing Tool to create new features in our map.   Using this tool and some basic editing techniques we created a new building in our Buildings layer and added a new road to our UWF_roads layer.  I am glad we learned how to use this tool as it definitely appears to be one that will come in handy.

In Section 3 we learned how to use the Multi-ring buffer tool to create two separate buffer zones around a located eagle's nest but have the buffer zones appear together as one feature.   We even learned how to add a hyperlink that displayed a photograph of the actual eagle's nest!

In Section 4 we used ArcScene to create a 3D image of the UWF Campus.   We used a DEM from Labins.org to create a "relief" for the other layers (Buildings, UWF_roads, and the aerial photographs of northern campus and southern campus) via the Base Height tab.  We used the extrude tool to extrude the campus buildings on the map.  Because the image still appeared "flat" we applied vertical exaggeration to the Scene to make it appear more three dimensional.

This lab was intensive but covered several important tools and techniques that I am sure to encounter again.

MAP2: UWF Campus Image Created In ArcScene Using a DEM

GIS4043 - Week 12 - Geocoding

Optimal Route Between Three Lake County EMS Stations

This week's lab was about Geocoding, Using Network Analyst, and Model Building.  We began by downloading data from the U.S. Census Bureau site.    Specifically, it was a Tiger Line shapefile for Lake County, FL; with this file we created a feature class for our geodatabase, Lake_Roads.   We also imported address information for Lake County EMS stations from a provided Excel table.  From our geodatabase Lake_Roads feature class we could create an Address Locator.  Finally, we could geocode the addresses for the EMS stations from the table we imported!  This was a frustrating experience but I learned how important it is to geocode!   After this process I realized how difficult it can be to correctly geocode/match addresses.  Thankfully, two-thirds of the addresses matched via our Address Locator.   Finding address matches for the remaining one-third required some zooming and hunting skills and the assistance of Google Maps and Bing Maps.  Some of the station addresses did not match due to field naming nomenclature.   A county road had the same number as a state road.   A state road was listed as a state highway.  Sometimes only one side of the street was numbered.  Even some of the rematch candidates were not good options.   I usually picked an address match from the map after a Google Maps and Bing Maps search.

With all of our station addresses correctly matched we then selected three stations to analyze with Network Analyst.  Using this tool we created an optimal route of travel between the three stations based on the amount of travel time.  U-turns were allowable anywhere but one-way and turn restrictions had to be followed.  I selected a station location in each region of Lake County to create my analysis set (Northeast-#141, Northwest-#241, and South-#341).  Using the Network Analyst Tool, Route, I was able to create a route based on travel time between the three distances.   I chose to start my route in the Northeast at Station #141 and then travel to Station #241 in the Northwestern part of the county and then finally end at Station #341 in the South.  I also tried changing the sequence of stops but the order sequence described above produced the optimal route which covers 32 miles in 43 minutes when started on a Monday at 8am.

In the final section of the lab, we were introduced to ESRI's Model Builder.  The training model was built to determine the locations of gas leak areas around schools in Fort Pierce.  The Model Builder helped me see the big picture from above the tree line of what we've been doing in some of our previous labs.  Using a model to manage geoprocessing operations makes sense.   Once a model is built you can copy or modify it for another use simply by making changes to either inputs or tools and share it.  We learned the basic elements of Model Builder; what the different shapes represented and whether they appeared filled with white (not ready to run), color (ready to run), or with a shadow (already run).

ESRI Gas Leak Model

GIS4043 - Week 10 - Vector Analysis Part 2

Potential Campsites In DeSoto National Forest, MS

In the second phase of our understanding Vector Analysis we were tasked with taking features from a provided geodatabase and creating a map of potential campsites.  We applied different analysis tools to a vector layer (Roads) and a polygon layer (Water) to create buffer zones or areas within a certain range of a feature.  The first analysis tool was the Buffer tool.   Per the lab instructions we created road buffer zones of various distances (100 meters - 300 meters).   We later used only the 300 meter road buffer zone layer to further develop our map.  In order to create these road buffer layers we used two methods, the first method used a fixed distance or linear unit to define the buffer zone.   Later we created road buffer zone layers by using Python scripts (arcpy) to create multiple processes at once.   By simply using copy/paste we could create buffer zones for the road layer of different set distances (100, 200, 250, 300).  We also used the Buffer tool to create a variable distance buffer for the Water layer.   We had two types of water features, rivers and lakes.   The lab required different buffer distances for each water type.   Rivers had a buffer distance of 500M and Lakes had a buffer distance of 150M.  This method required that we create a new field in the Water attribute table called buffdist (buffer distance) and assign the different distance values according to the water type (river, lake).

Next, we used Overlay tools to combine feature attributes of input layers to create new output layers.  Specifically, the lab used the Union tool to preserve all of the features in both input layers to create a new output layer.   Our input layers were the Water_Buffer layer we created with the varying buffer distances per water type, and the Roads_Buff300M layer which was our road buffer of 300 meters.  This union created an output layer with nine records.   From this output layer we then narrowed our selection by choosing records that only resided within our road buffer (300M) and our water buffer (150M and/or 500M).   This new Buffer_Union_Export layer became our input layer to create Possible_Sites, a layer of potential campsites.   After adding the provided conservation_areas feature class to the map, I then used the "Erase" overlay tool to exclude any conservation areas from our Buffer_Union_Export layer.   This newly created Possible_Sites layer was complete however, we could not view individual polygons (campsites) because features had been grouped together into a multipart layer.   We used the Data Management Tool, multipart to singlepart to create single polygon records, campsites.   Using this final singlepart layer I created a final map highlighting these potential campsites that met our site requirements of being located within 300 meters of a road and within our water buffer zone (150 meters of a lake and/or 500 meters of a river).  I used a World Terrain basemap underneath the feature data as well as for an inset map for reference of the location, DeSoto National Forest, Mississippi.

This assignment was a challenge for me mainly because of some ArcMap difficulties in exporting and saving files to an existing database.   I learned a work around to schema lock error messages (create shapefile and import shapefile into geodatabase).  I also had to take time to thoughtfully understand the overlay tools and the output layers they actually created from the input layer(s).   Creating a description field really helped me visually see what features were combined, excluded, etc.

GIS4043 - Week 7-8 - Data Search

Leon County, FL Map 1 - Cities, Roads, Hydrography

Leon County, FL Map 2 - Public Lands,
Invasive Plants in Elinor Klapp Phipps Park

This mid-term lab required us to find and download nine data layers to create a map or maps of our assigned Florida County.   I was tasked with presenting Leon County, Florida home of the State Capital, Tallahassee.

Using vector data layers I created my first map depicting cities, roads, and major hydrography features of Leon County.  I chose to include an inset map of the State of Florida for reference purposes.  I changed the symbol for the City of Tallahassee to represent a Capital City.

Leon County, FL Map 3 - Elevation and
Strategic Habitat Conservation Areas

In my second map I chose to display the public lands located in Leon County and then focused in on a park located in Tallahassee, Elinor Klapp Phipps Park (EKP).  I used my aerial raster layer, downloaded from Labins.org, to show a closeup view of the EKP Park.  I then added one of my environmental layers (invasive plants) on top of the aerial layer to show the various invasive plants found in the EKP Park.

For my third, and final map I chose to create two data frames.  The left frame displays the elevation of Leon County by using the raster DEM layer from the USGS.  I chose a color scheme that would enable the map audience to easily recognize the differences in elevation.

The right data frame displays my second environmental layer of strategic habitat conservation areas.   This raster layer ranks areas by priority level.  Again, I chose a color scheme that enables easy visual interpretation of the priority levels.

This lab was definitely a challenge.  Finding all of the required layers took some time and patience.  It was also helpful to view the metadata on each download site prior to downloading.  I also added all the layers to one mxd just so I could view each one and see how their data was presented visually as well as in their respective attribute tables.

Once I had my data it was hard at first to come up with my map designs/layouts.   I began with the simplest first (Map 1).  Creating Map 1 was very similar to previous lab assignments.  I started on Map 2 and began to formulate my design after looking at all of the remaining layers.  I created the left data frame of Map 2 but was unsure how and which layers to present on the rest of the map page.  I took a mental break from Map 2 and started Map 3 by adding the DEM layer.  Since I did not have too much experience with DEM and raster data layers I chose to clip this layer to the Leon County frame and display it singly.  I was worried my remaining Map 2 design would look "too busy" so I decided to display the Strategic Habitat Conservation Area layer alongside the DEM layer.   Both layers were raster data and it helped make the map appear symmetric.  I returned to Map 2 and focused in on EKP Park.  My daughters have played in travel soccer tournaments at the nearby Meadows Soccer Complex so I thought, why not.  Of course, the first aerial layer I downloaded had not been located near the park, so selected another layer.  I was right next door, but needed to move one more quad left and select my final DOQQ of q5335se.sid.  I really liked using the aerial layer as it served as a "basemap" for my invasive plants layer.  I was amazed at how many invasive plants were spotted in such a small land area; really made me think!

GIS4043 Week 6 Projections Part 2

Crude 5 Layer Map of Escambia STCM Sites

In this second phase of our Projection lesson we learned how to download data from different sources such as Labins.org and the FGDL Metadata Explorer.   We also learned how to create XY data using Excel and how to add that XY data to an ArcMap map and create a shapefile.  Part 1 and Part 2 steps enabled me to become more comfortable with understanding the different projections and where to look for them.  I also gained confidence using ArcMap tools such as Project, that enable the map creator to "reproject" layers so they match.  After proceeding through Part 1 and Part 2 of the lab, I was adequately prepared to tackle the requirements of Part 3.   After I downloaded the required data and I reprojected the layers to the same projection (NAD_1983_StatePlane_Florida_North_FIPS_0903_Feet) I created my crude map of 5 layers which inlcudes: Escambia County STCM sites, county boundaries, major roads, 4 aerial images of Perdido Bay {5160 quad of Escambia County}, and Quarter Quad Index.  I also added an imagery Basemap to ensure I had all layers aligned/projected correctly.  I changed the symbology of the Escambia STCM layer to an above ground storage tank symbol.  I also took a screen shot of the layers before and after setting Transparency on the Quarter Quad Index layer to the Area field.  Correct units in Feet are displayed in the bottom right corner.  The final screen shot shows the Data Frame Properties > Coordinate Systems Tab.

Crude 5 Layer Map of Escambia STCM Sites with Transparency

Data Frame Properties>Coordinate Systems Tab

GIS4043 - Week 5 - Projections Part 1

In this week's lab assignment we were tasked to learn about different projected coordinate systems and apply them to the same data set of Florida counties.  Using different projections we were able to see how differently the same data was displayed.    We learned how to use different Data Management Tools in the Arc Toolbox or via Search, specifically the Project Tool and the Project Raster Tool.

The Florida Counties data layer was originally projected in Albers Conical Equal Area projection.  An "Albers" layer was created in our Projection Comparison Map.  Then we used the Project Tool to create two new layers with new projection system.   The first new layer used the UTM 16N projection and the second new layer used the State Plane N (for Florida in US Feet) projection.   Each newly created layer was placed in a new data frame.   Now our Map contained three data frames with the same data set used to create three different projected layers.  Next we ordered the data displayed in each respective attribute table by County in alphabetical order.   We then added a new field and had it display the Area for each county in square miles.   From the attribute table we selected four counties specified in the lab assignment and created an additional layer for each data frame from these selected counties.   By changing the symbology of our layers our maps could now show the same four counties within the State using the three different projection systems (Albers, UTM 16N, and State Plane N).   I created a table in Excel to show the calculated Area values for each county by projection.  By comparing the values you could see which projection system was the best choice for our four county layer selection.   Because only Escambia County resided in the boundaries of all the projections it had the least variation of  area values.  Miami-Dade County had the most variation in area values because it is located furthest away from the UTM 16N projection boundary and the State Plane N boundary.  

Next, we added Raster data to two of our existing three data frames on Florida Counties map.   We learned that often raster data sets cannot carry projection information with them.   After looking at the Extent tab under the Properties of each layer and comparing the Visible an Full Extent coordinate values we could see which Projection system was used for this data (State Plane N).   We manually edited the Spatial Reference of the UWF raster data by selecting State Plane N for Florida in US Feet.   We then used the Project Raster tool to select the UTM 16N projection system for the UWF Raster data and added it to it's respective data frame.  

After reviewing the steps and results of this lab and preparing this blog and my Process Summary I understand why Albers Conical Equal Area is the best projection system to use when creating large scale maps of the United States or other countries with an east-west extent.  

I ran into a script error problem when attempting to use the Project Raster tool.   After googling my problem I decided to delete the ESRI folders in my Local and Roaming folders as it appears I had a corrupted file.   This worked and hopefully I won't run into these errors in future labs.

GIS4043 Week 4 Shared Top 10 Maps

In this week's lab our assignment was to create a Top 10 list based on locations, map our list and then share it in different formats (ArcGIS Online, ArcMap, and Google Earth).

First we learned how to search and add both internal and external data sources.  For our lab assignment we added the external sourced ESRI World Street Map.  This provided me with reliable base map data from the ArcGIS Online map service.  We also had to create a Top 10 list.   I chose to create a Top 10 list of swimming holes in Florida.   We had taken our kids and their cousins to Morrison Springs this past summer and I wanted to learn about more swimming holes.  Through a Google search I found a website with an article by Victoria Winkler on Florida swimming holes (http://www.onlyinyourstate.com/florida/swimming-holes-fl/).   I used the first 10 swimming holes listed in the article to create my Top 10 list.   I created an MS Excel file listing the rank, name, address, and an image link for each swimming hole.  In addition to having this information in an Excel file I also saved the Top 10 list as a Tab Delimited text file per the assignment instructions.  In order to use the Top 10 list to create our maps we had to convert the table list into a shapefile by geocoding the data to create a layer.  We created our first map in ArcGIS Online when we created the Top 10 layer.  

My ArcGIS Online Map

Unfortunately, from a design standpoint I could not change the symbology of this ArcGIS Online map which was shared with "everyone/public".  Once I located my created and saved layer/shapefile on my student drive, I could then add this data layer to a new blank map in ArcMap.  Now that I had the base layer World Street Map and my Top 10 list layer I needed to verify that they were using the same coordinate system (WGS 1984 Web Mercator (Auxiliary Sphere).  Next within ArcMap I optimized my scale and symbology settings to ensure better performance and appearance when my map was published to the web.  My map appeared best when the scale was set to 1:2,311,162.   I was able to see all of my locations on the screen but there was some overlapping of symbols.  If I changed the scale to 1:1,555,581 I could not see all of my locations on the same screen.  I also edited the Top 10 attribute table to only display fields that were important for the user to view.   This streamlined the data that would appear in the pop up window when a user selected the symbol for a swimming hole location.   Next I made modifications to my Map Properties and Item Description in order to make my ArcMap ready to become a Map Package.  My second map, the ArcMap was complete.   I combined the mxd file with my Top 10 text file to create a Map Package.   A Map Package enables the end user to not only see your map but also provides them the ability to explore and analyze the data  used to create the map.   Access to ArcGIS for Desktop is necessary to use the Map Package.  Finally, to create our third map we searched for and used the Layer to KML tool within ArcMap.   Our input layer was our Top 10 layer.   This tool created a compressed KML file (KMZ).  With the link to my KMZ file I could then open up and view my map in Google Earth.

This lab enabled me to understand the different methods of obtaining layers to create a map; internal and external sources as well as creating a layer from data that I created (Top 10).  After perfomring this lab, I realize the importance of having reliable data from reliable sources to create a map.  I also learned how to share my maps with end users.   Depending on the needs of the end user creating a map to be viewed in ArcGIS Online or Google Earth may be sufficient.  However, if working with an end user who needs to have access to the design and data elements of the map, providing a Map Package is the optimum way to share a map.   I also realize how important symbology selection is when preparing a map for web publishing.   The symbology settings I chose for my swimming locations appeared fine within ArcMap but the color and background didn't appear as crisp or clear in Google Earth.

I enjoyed this lab assignment.   The lab instructions guided me through this assignment.  Peforming these tasks gave me an idea on how to create a basic map of school locations in Okaloosa County.

GIS4043 - Week 3 - GIS Cartography

Maps of Mexico

The GIS Cartography lab really helped me start to feel more confident in navigating ArcMap.  In this lab we were tasked with creating three maps.  Figure 1 is a map of Mexico.  This map identifies individual Mexican states with name labels and displays the population sizes of the states by using a gradient color scheme for population ranges.  Countries bordering Mexico are also displayed and identified but are not the focus of the map.  In order to only view the individual Mexican states, we were required to create a data subset, Mexican States, and then export this subset to create a new shapefile.  Editing the population ranges displayed in the Legend was another new task to learn.  I used the data shown in the Attribute table to help determine the "rounded" ranges.  I also watched a video to help me better understand Frame lines versus Neat lines.  https://www.youtube.com/watch?v=pzscI_JhZgI

Figure 1: Map of Mexican States

With Figure 2 we take a closer look at Central Mexico.  I became more familiar with correctly using Data View and Layout View to display the features I wanted to emphasize.  We added layers to this closeup perspective (rivers, roads, and railways).  De-cluttering the map was an important assignment.  Creating layer groups within the Table of Contents also kept this map organized.  We used data information from the Attribute table to display certain subsets of the Surface Water layer and population data.  The Central Mexico map highlights urban areas with populations greater than 1 million people.  This task was performed by creating a new "class" label.  Discovering editing methods in the Symbology tab was an important element to creating this map.   There are different symbol libraries to choose unique symbol styles to display in Legends and on the map.  Instead of displaying feature labels we converted these labels to annotations, enabling us to edit these text boxes more effectively in the Data View.  An inset map was also placed on the page to provide reference/context to the location we were describing.   Using Extent Indicators I created a border indicating the location within Mexico.  I also edited the Placement of the country name label in the inset map from "horizontal" to "straight".  Working with two data frames was a new concept.   

Figure 2: Map of Urban Areas in Central Mexico

Lastly, Figure 3 presents the topography of Mexico.  A sequential color scheme was selected to highlight the ranked elevation data.   This was my first time working with raster data.  I selected a color ramp that would show a clear contrast in elevation levels.  The spectrum I chose enables the map audience to clearly see the highest elevation areas as well as valleys and coastlines.  The appearance of raster data sets can be enhanced by "stretching" or "classifying" the data.  My map used a stretched symbology scheme to modify the brightness, contrast, and gamma properties of the raster dataset.  I chose to use color symbology to indicate individual border countries but decided not to label them as the focus of this map was Mexico.  An inset map was added to provide a point of reference to the location being shown.

Figure 3: Topography Map of Mexico

I enjoyed this lab assignment but it was very time consuming for me.  Using the same original map and layers to create three different maps by applying various modifications, enabled some concepts learned in previous lab assignments to be reinforced.  I also feel more comfortable using two data frames and navigating between views in ArcMap.  I now realize there are a variety of options in regards to symbology and labeling.  Using these ArcGIS tools wisely can greatly enhance the appearance of your maps.

GIS4043 - Week 2 - Own Your Map

UWF Main Campus Location

In this week's lab assignment I felt more comfortable navigating in ArcMap.  Creating a map of UWF’s Main Campus location with an inset map of Counties of Florida was a challenge for me.   The lab guidelines helped me to explore and understand the functions of ArcGIS while creating a useful map.   I also learned about essential map elements and guidelines to follow before designing a map.  Learning how to find map information from metadata was the most difficult portion of this lab.  Metadata provided for different layers can be uniquely displayed by different metadata styles.   Knowing where to find a value or description was important in this lab.  For my UWF Main Campus Location map I chose to maintain the Portrait orientation as the instructor had because I felt Escambia County would fit better and provide me with ample map space to place essential map elements.  I chose a light green for the background color of Escambia County so there would be some contrast with important items placed on the map.  I chose to place my scale bar on the bottom right as that placement location was closest to the interstate routes on the UWF layer as well as the campus location.  I learned how and where to change the location placement of city names around the city point symbology.  Placement of the UWF logo needed to allow it to be legible and non-intrusive.  Similarly, the legend needed ample map space to make it easy to read and locate.  I chose to place the legend closest to the features shown on the map and to place the logo next to the title.  I enjoyed having some autonomy in this lab but also some guidelines and steps to follow.  I am realizing how important understanding your map audience is in the design of a map.

GIS4043 - Week1 - ArcGIS Overview

This is my first week in GIS4043.  In this week's lab assignment I was able to successfully login to ArcGIS and upload the Cities and Countries data files provided by the instructor.   Using these files I was able to follow the assignment tasks to learn about different features and settings that can be used to create, modify, and define a map.   Additionally, I learned how to find specific information about the countries in the map that I created.  Finally, we were required to use the Help Library and Search tool in order to know how and where to seek assistance regarding ArcGIS.  Since I have no prior experience using ArcGIS I found the assignment instructions very helpful.  My map is a map displaying world countries and select cities.  The individual countries are color shaded on a graduated scale to denote their country's estimated population size.