FPL and Bobwhite-Manatee Transmission Line Project

Hello avid GIS'ers,
      This post is all about the culminating exercise of the this Semester in Intro to GIS. The final project for the class had me acting as a budding GIS analyst for the UWF GIS Group, recently hired by Florida Power and Light to conduct analysis on a newly proposed power transmission line corridor. Now this corridor was actually erected and put into service years ago. But it provided an excellent backdrop for skills learned throughout the course to be honed and demonstrated. This project utilized three phases, a Background or information gathering phase, an Analysis phase whereby the background data was used to derive various conclusions about the transmission line and surrounding area, and a Presentation phase. This post comes at the end of that presentation phase. My finalized Power Point (Yay death by PP...its not that bad...) presentation and my Slide by Slide commentary are both linked below detailing the project.
This post is kept relatively short as most of the other posts go into specific maps and a brief synopsis of them. However all of that is contained within the links here. Would you like to know more...? Simply click:
Project Presentation (Power Point has been transformed to PDF for space saving)
Slide by Slide Breakdown
Overall most of the processes for each objective discussed in the presentation seem relatively easy (even if sometimes time consuming) looking back on them. This is most likely attributed to the excellent process of guiding students through this program. Kudos goes to the UWF Instructor for the foundation of GIS knowledge imparted. Thank you Mrs Bloechle. And of course where would an instructor be without an Aid, thank you Ms Krolikowski.
Further it is amazing to look back on the beginning weeks and how little I knew about GIS, and how little fashion sense I had toward it. I probably still don't have much, but its an improvement. Thank you for joining and continue to find my work as the program continues.



v/r



Brandon

A Triple Threat: Georeferencing, Editing, and Arc Scene

Hello all,
      This weeks post for my Intro to GIS class is all about what my title has alluded to; Georeferencing, Editing, and Arc Scene. The data for the lab was provided by UWF, featuring UWF through two aerial images, a building footprint layer, roads layer,a local eagle nest, and a Digital Elevation Model for the Arc Scene work. The maps below were both compiled in ArcMAP, however the 3D map was originated in Arc Scene. There were many overall objectives for this week as each of these topics can easily be given its own Lab Week and beyond. However a rundown of some of the bigger objectives is below.

• Georeference data using Control Points and proper distribution
• Georeference an unknown raster image of the campus to known vector data (i.e. buildings & roads)
• Interpret Residual and Root Mean Square errors
• Digitize new building and road features
• Edit data features and attributes
• Create hyperlinks in ArcGIS to data stored on a personal drive
• Create Multiple Ring Buffers
• Practice overlaying data in a 3D environment

Of the above the newest term should be Georeferencing. This is the registration of an image without a known reference to a dataset or group of features with known coordinate system etc. So below I took two un-referenced images of UWF and using the buildings and roads feature layers was able to add reference information by matching up location in the road and buildings layer to locations on the imagery. This is done through a set of linked control points. Essentially im telling the image, this spot on the image correlates to this point on this building or road layer. After enough of these points the image is able "referenced" because it now knows where it spatially belongs.

Above is my Georeferenced Raster map. You can see that its divided into three parts. The main component being the georeferenced rasters whereby the aerial images were matched up to the building and road feature location. Additionally the UWF Gym was edited onto the building layer, and Campus Drive was edited onto the road layer. The inset map in the bottom right shows the location of a nearby eagle nest relative to the main campus, and also depicts the mandated conservation easement area around the nest. 

The next portion of this lab involved taking the newly georeferenced rasters and the associated feature layers and adding them to Arc Scene. There, the layers were all floated on top of a digital elevation model. The building layer was extruded relative to the height of each building Then the entire image was given a vertical exaggeration of 5x, which only changes the visual appearance of the map, not any of the actual data values associated, but gives you a better visual interpretation of where height variation occurs.

This map which was created as specified above needed to be exported from Arc Scene and imported into Arc Map to do some of the finishing touches, such as applying the legend features and information. The image maintains a largely North up appearance, however due to the change of 2D into 3D and other exaggeration you can no longer dedicate a scale bar or North arrow given the ability to freely change the vantage point in Arc Scene.

I hope you have enjoyed these maps, they were definitely entertaining to create. It is neat to know how to create and edit your own layers and present them in different views, both 2D and 3D.

Cartography and Google Earth

Hello All
      Let us continue what we started a couple weeks ago with an introduction to 3D mapping with this post specifically dedicated to Google Earth. This weeks assignment was two fold. Import a map built in ArcMAP into Google Earth, and build a tour of the surrounding region also using Google Earth. The main objectives of this assignment were to do as mentioned above, convert ArcMAP to KML, and to create and share a KML map and tour utilizing Google Earth. The data for this conversion was two fold, my Module 10 data and map, found in the previous Dot Map post, as well as another version of the same provided by the instructor. This lab was completed using a combination of the aforementioned programs.
What enables it all? Well, ArcGIS has tools to convert its data to the KML format that is view able in Google Earth. We've discussed raster and vector data before, and Google Earth takes these and then gives you different functionality for them. Raster data is faster to process and eats less space. Vector data allows for more variation of individual items rather than entire layers. A combination of both was used in this assignment. So lets look at that.

You've seen this map before if you've seen the Dot Map post. However this one is a little more realistic as it is overlayed on top of Google Earth imagery. The same basic features apply, population density data across southern Florida with a few key cities highlighted for reference.

The next big portion of this assignment was to build a tour visiting various areas in the populated regions. Unfortunately the tour itself is not included. However it was relatively simple to create. It involves setting particular views of whatever areas you desire to show and then recording as you move between them. This movement between locations can either be done free hand with the cursor or via set place markers which can have default views associated with them. I have taken two of the more interesting views I found while building my map for your viewing pleasure below.

Here is one of the scenes in my tour, Essentially the camera is parked on top of one of the highrise buildings in downtown Tampa looking west. You can make out a lot of detail here in the 3D mapped area of Tampa. One of the places that I found to particularly highlight the amount of detail you can find in this city is below.

The focus of this scene is just south west of the last image, but looking to the North West instead of straight west. The features that really caught my eye was the multi-story penthouse in the center of this Hilton hotel with the rooftop pool. The specific feature which peaked my interest most was that the detail is so good in this area of the picture that you can see the swimming pools reflected off the glass of the high rise portions of the hotel. Areas with extensive data and imagery overlay can create amazing digital scenery in Google Earth. This was one of the points with this lab. Discover what is possible, and continuing to evolve with mapping. Thank you.

Intro to Geocoding and Model Builder

Good afternoon all,
       This post follows up on this weeks Intro to GIS assignment which was broken down into two main topics: geocoding and Model Builder, both associated with ArcGIS. The majority of the lab was involved with geocoding, broken down into three sections: Building an address locator based on reference data, geocoding addresses with the locator and background road layers, and then network analysis with the road layer based on a created route.  The model builder portion took an existing model and dissected its individual components and functionality via ESRI.com online training. The objectives for this week all supported an enhanced understanding of these topics. Data was provided by both UWF and the ESRI.com virtual training course. Lets look at each of the above concepts before getting to the map below.

What is Geocoding?
Geocoding is the process of finding a geographic location using an address, coordinate pair, or name of a place. Most of us have reaped the benefit of this type of system anytime we tell TomTom, Google Maps, or your phone to find you an address from where ever you happen to be.

What is Network Analysis?
To understand this we must first look at what a network is. A network is a set of interconnected lines and intersections. In this context we refer to the lines as edges, and intersections as junctions. As such a network is a representation of possible routes from one point to another along these interconnected edges, via the intersections.
Network analysis then is what we do to derive certain information about the network, whether it be as simple as finding the shortest route from point A to B, or understanding based on the network the next best place to put a Starbucks is not across the street from a Starbucks. 

Lets look at the map creation for this week before we get further into Model Builder. 

This map is a combination of Emergency Medical Service sites for Lake County Fl, and an example optimum route both created in ArcMAP. You can see that the big key I want you to pay attention to for this map is the Point location and address for the EMS site. These addresses were geocoded using an Address Locator that I specified, and then located on the street feature class. The Route demo was also built from the Network Analyst utility in ArcMAP and placed as an inset for further clarification and enhancement. Also, the basic features presented here dont really need the lake data... but what is Lake County without lakes? Just county? So i added them in for an understanding of why its called what it is. 

On to Model Builder.
This is a handy application for when you want to  do the following according to ESRI's virtual training on the subject

• To see a visual representation of analysis and geoprocessing operations.
• To automate and manage geoprocessing workflows.
• To run a complex succession of processes as one tool.
• To plug in additional tools and parameters as needed.
•  To be able to share geoprocessing workflows with other users by sending them the model you’ve created in Modelbuilder. 

So how does model builder do the above? It takes a set of user specified input data, tool selections and output data the user connects them based on the applications with the associated tools. Once complete the entire process should be much faster than if you were to perform each step individually.

Here is an example of the model used this week and the final output. 

As you can see this is a screen shot of ArcMAP, with this weeks Model in the lower portion of the shot. The blue ovals indicate input data elements, the yellow rounded rectangles are individual tools being applied at various stages, and the green ovals are data created as a result of a tool or process. 

The fact that these items are all drop shadowed indicates that those elements have been ran. The overall very specific result is displayed above the model. An entire background area was reduced to identifying these few areas as the result of the model. Kudos to you model builder.

Thank you for your time.