Tuesday, May 2, 2017

Final Project








       It's the final project!!  This lab was a true test of my knowledge learned over the semester.
I composed a five series map showing the Bobwhite-Manatee Project.  Each map shows the parameters of one of four main objectives and a reference basemap.  The basemap shows the study area, the preferred corridor, a 400 Ft buffer zone, and an inset map of Florida for a spatial reference.  Map 2 depicts the impacted land use of the preferred corridor.  It shows how many homes and parcels are affected by the project.  I had to digitize the homes and use the intersect tool to find land parcels impacted. Results showed 66 homes and 255 parcels are impacted.  Map 3 shows the schools and daycares impacted by the preferred corridor.  For this dataset I had to use FGDL.org to obtain two data files.  Results showed that while 5 institutions were in the study area none were directly impacted by the preferred corridor or buffer zone.  The fourth map depicts environmentally sensitive lands impacted by the preferred corridor.  For this data I also used the intersect tool on both conservation areas and wetlands to locate impacted areas.  Results revealed 3 impacted conservation areas totaling 10,452.64 acres and 26,573,417.84 acres of wetlands impacted.  My final map shows the length of the centerline in the preferred corridor.  I first had to edit the major roads layer to draw a line through the center of the preferred corridor polygon and then measure the line with the ruler tool. The centerline measured to be 42,435.54 m (139,224.21 Ft).  We also had the option to derive the cost of the project but I ran out of time.  I had many issues with this lab that still go unexplained.  Most of my problems came every time I opened a saved map; I would find my data needed to be repaired.  Once I repaired the data the image would be scattered instead of layered on top of one another.  All layers had been re-projected into the same projection, however, that did not seem to matter.  I was advised to stick with the original projection and that managed to fix that problem.  I also had problems with the editing tool when drawing the centerline.  It would not save my final product; it would only save 3/4, by this time I had to continue without resolving the issue, due to time constraints.  I also just realized while writing this blog that I put the wrong info in the data box on Map 5 (I have so much repaired data and do-overs that I didn't notice til I looked up at my pics for a reference).  I apologize, the data is correct in my blog script but not on my map pic, or the links below.  I have provided links to my power point presentation along with a slide-by-slide transcript.  I had a great semester and I feel a bit more confident in my skills now but, this final lab has shown I still have much to learn.  I hope you enjoy! 

http://students.uwf.edu/dmm16/GISLab/Wk14_16/BobManPro.pptx
http://students.uwf.edu/dmm16/GISLab/Wk14_16/FPTranscript.pdf

Friday, April 7, 2017

Week 13 Georeferencing, Editing, and ArcScene


The lab for this week focused on georeferencing, editing, and arcScene; I really enjoyed this week as it was concerned about accuracy and the small details.  We had to take the geodatabase shapefiles in ArcMap and line it up with two raster images of UWF campus using the georeferencing toolbar.  We made control points spread out the layers from the raster (unknown location) image to the buildings and roads (known locations) until the two layers matched.  We not only had to have a matching appearance but we needed the RMS Error to be below 15, plus I had to change my transformation for the South image of UWF.  We also used the editing toolbar to digitize one of the buildings and a road; I really enjoyed the drawing around the perimeter of the building and centerline of the road.  Then we had to make two buffers around the eagle nest on campus using the Multiple Ring Buffer; we even added the tool to a toolbar and chose its button design.  We also added a hyperlink to view the nest which I had some trouble on due to a glitch in the system.  The ArcScene 3D image was fun as well; I like that you can see the image from different angles with depth.  We overlayed the 3D image onto my first map and got a 3D version of the first map ( minus the nest).  My first map shows the two aeiral images of the UWF campus and the eagle's nest located to the east of the campus; I made my two digitized features into their own layer so I could highlight them in a bold color.  I also featured them in my legend to distinguish them from the intial layer.  I also added a basemap so the eagles nest would show up and the raster data would blend in.  I chose a lighter colored text to contrast the darker backdrop from the images. The inset map shows the two buffer zones around the eagles nest.  The pink zone is a 330 ft easement for conservation of the nest and habitat surrounding; the neon green zone is a 660 ft no development zone.  My second map is the 3D assessment of the two aeirial raster images, in which I also chose to highlight my digitized features.  I did feel a bit rushed in this lab, but I feel good about my results and much better than last week.  I am heading into the final project with confidence.

Monday, April 3, 2017

Week 12 Geocoding

Week 12 lab was about Geocoding and Network Analysis.  We were introduced to Tiger/Line shapefiles as well as Model Builder.  The Tiger/Line shapefiles had to be imported from a table so we could get all the addresses for the EMS stations in Lake County, Florida.  Once the table was imported we used Bing maps to match addresses that had no candidates.  The Bing map and Lake County EMS site provided a reference for the station number and streets; I had to find street names that matched or cross roads to get specific addresses.  Another method to matching the addresses was a select by attribute query.  After the attribute table was geocoded we had to make new layers with the data from the completed table.  We then used the layers to create a route between three of the stations.  This week we also learned about Model Builder which allows you to set up a series of tool commands that can run simulaneously.  This process gives a visual aid to how geocoding works as well as makes sharing the process and data with others easier.  My map this week has two data frames.  The main data frame shows Lake County, Florida including all the streets, EMS stations labeled with their addresses, and an extent indicator for the next data frame; I also provided a base map of world topography for a reference.  The second data frame shows the optimal route between my three selected EMS stations as well as the streets layer from the Lake County map.  This week proved to be very trying; I had to repeat many of the steps and never really understood what I was doing wrong.  As usual I enjoyed designing my map, but all the computer lingo is still confusing to me.  Fingers crossed for next week.

Friday, March 31, 2017

Week 10: Vector 2

Week 10 in lab was a continuation of Vector Analysis with the addition of Buffers, ArcPython and Overlays.  Buffers were created around roads and waterways at 100 m, 200 m, 250 m, 300 m, and 500 m using the ArcToolbox at first and then ArcPython.  ArcPython seemed simple but I ended up having to retype the code over 10 times and never truly understood what I did wrong; I put in the output filepath wrong several times, and once that was fixed  I continued to have run time errors, and my layers could not be opened.  The Overlays were fun but I tried a few different ones like Union, Intersect, Erase, and Update.  My map shows possible camping sites in DeSoto National Forest in Mississippi; the campsites are shown in green and follow specific guidelines that were defined using the buffers and overlays.  Campsites had to be within 150 m of a lake, within 500 m of a river, within 300 m of a road, and could not be inside a conservation area.  I enjoyed seeing how you could combine or erase different parts of layers to achieve a desired location.  While I was confused with ArcPython it did make sense to use it so that many actions could be done at once, which seemed to help ArcMap draw layers faster.  The repetition this week was frustrating and I am nervous about the next lab.

Friday, March 10, 2017

Data Search Mid-Term



      This lab was our Mid-Term and was more or less a do it yourself assignment with basic set parameters.  Our guidelines were to locate and download 9 data layers (5 Vector, 2 Environmental, and 2 Raster), put all data in the same projection and clip it to fit our assigned county, then to use this data to make 1-3 maps showing all the data in a visually appealing and readable way.  I obtained all my vector (county boundary, cities,public land, major roads, and hydrology) and environmental data (invasive plants, and wetlands) from a FDGL search.  My raster data came from two different locations; the aerial image was obtained from Labins, while the DEM (elevation) data came from USGS (TNM Download).  I originally used my aerial image to make my projection choice (NAD_1983_2011_StatePlane_Florida_West_FIPS_0902_Ft_US) but while putting all data into ArcMap I realized changing the DEM projection was not working and had to re-project all data to match the DEM (GCS_North_American_1983).  Clipping the data was more simple than I expected; I only had two hic-ups, one with the DEM; I fixed the issue by choosing not to use the raster data clipping tool and using the data frame clipping option instead.  The second struggle was try to clip vector data to fit my raster aerial image, again I had to clip it in the data frame tab in order for it to work.  I was assigned Citrus county, Florida as my AOI (Area of Interest); I chose to do a series of three maps.  My first map was a general map of Citrus county showing the shape of the county, cities within, major roads, bodies of water, and an inlet map of the state of Florida giving a spatial reference of the county within the state.  Citrus County, FL Series map 2 focused on the environmental layers and my aerial image; I zoomed in on my aerial image of the SW quadrant of Crystal River and clipped the environmental data on top of the image.  I also provided a small inlet map of entire county's wetlands and invasive plants.  The final map of my series showed the public conserved land and elevation of Citrus county.  I used the same font, symbology, and color scheme throughout all three maps giving the entire series a connective theme besides the title and location.  Weeks 7 and 8 were daunting; I was sick for most of week 7 so I only had half the time to complete this lab.  I downloaded extra data in hopes I would have time to play with more layers and different images but my time constraint proved to be too much.  I did enjoy finding my data even though the descriptions of what I was downloading were deceiving, and I found myself having to choose different data because some were far to large, or completely blacked out the entire county.  I feel confident about my knowledge of how to obtain data and how to manipulate the data to show my desired outcome; all in all this was a great mid-term that forced me to use the skills I have obtained throughout this class.  On a side note I was assigned this county at random, I randomly choose Crystal River and the SW quadrant image; come to find out I have been to that exact location to swim with manatees ten years ago (I always thought it was in Homosassa Springs but apparently not).  NIFTY!!!

Friday, March 3, 2017

Projections Part 2


Week 6 we continued our focus on Projections with an emphasis on data retrieval.  We learned where/how to find publically accessible data, how to make the data readable by ArcMap, how to change the projections to match other data, and put it all together on one map.  We used a few different data search sites such as FGDL, and Labins to find aerial images as well as base map layers for state and county.  In addition to the downloaded data we used an Excel spreadsheet with x/y coordinates that we needed to convert degrees to decimals to plot the points on our map.  Once all layers were downloaded we had to make sure all projections matched; most had to be re-projected, but the Exel file had to be defined.  I did have a few issues whenever I would come back to my map, some of my layers data was no longer present; I found myself having to re-download the data and re-add the layer.  My map shows eight layers including, a quad index, county boundaries, and major roads for the state of Florida, four aeiral images making up Perdido Bay quadrant, and the oil tanks located within Escambia county Florida.  I really enjoyed all the data retreival and, as I have said before, the spreadsheets, especially learning the new formula.  I also like adding the layers and watching them line up.  However, I did find it cruel and unusual punishment that after doing the eagle nest data map I had to start all over and do the oil tank map; I did practice a lot of saving and folder making which I feel will help later on.  Week 6 was an extended week for me, a slight hiccup but I'm headed back on tract now.

Thursday, February 16, 2017

Projection Part 1

This week, Lab 5's focus was on georeferencing and projection; my map shows three different projections of the counties of Florida, highlighting four counties from all across the state.  The first map was projected with Albers which is a global projection system and distorted the shape of the counties and state.  Both the UTM 16 and State Plane projections focus mainly on the panhandle of Florida; with the smaller reference frame the  shape distortion is minimized.  I also included a table showing the different calculaltions for area in the four select counties; the table shows the distortion between projections as a calculation distortion.  You can see numerically that Escambia county shows the least distortion among the projections, and then Alachua, Polk, and Miami-Dade respectively.  The last element added was a picture of the UWF main campus provided with rasta data.  This week was confusing going back and forth between projections but I did enjoy seeing the different perspectives; hopefully part 2 will show me some clarity.