Tuesday, May 2, 2017

GIS 4043 Final Project

Hi GIS partners,

For this project, I was required to conduct a GIS study on a real-life event that had GIS connotations: the construction of the Bobwhite-Manatee Power Transmission Line. I was required to use already provided data, search and collect data, conduct spatial analysis, prepare maps, and assess whether the construction of the transmission line was feasible and acceptable based on certain criteria.

This project provided me with the opportunity to review and use GIS tools and processes such as: Projection, Transformation, Union, Buffer, Intersect, Select by Attributes, Select by Location, Erase, Calculate Geometry, and the creation of shapefiles and geodatabases. This project served to reinforce the GIS skills I learned during the course. I have included links to the project's presentation and transcript.

This is my first experience taking a college-level online course and I highly recommend it. I thank the professor and instructors for sharing their expertise and assisting me with any obstacles I encountered. The course itself was intensive, yet interesting and enjoyable. I also want to thank my classmates for their continued support throughout the course.


    Jeffra Montañez Sánchez

Tuesday, April 4, 2017

Georeferencing, Editing & ArcScene Lab

Hi GIS partners,

      This week's lab was about georeferencing, editing and ArcScene; I have included the two maps that I prepared. For the first map, I georeferenced two aerial images (uwf_n.jpg and uwf_s.jpg) covering The University of West Florida Campus North and South. I georeferenced the images as accurately as possible using the Root Mean Error parameter and a distinct type of Transformation for each image. This process was a little bit rigorous and time consuming as I had to delete the links with the highest residual and replace them with more accurate links. After that, I used editing sessions to digitize the UWF Campus Gym and an arterial of the "Campus Dr". Finally, I used the Multi Ring Buffer tool to create 330 and 600 feet buffers mandated by the FWC and UWF to protect an Eagles Nest located within the Campus, and added an imagery basemap. For the second map, I opened an ArcScene project and used a DEM to create relief on the aerials and vector layers from the previous map. Lastly, I exported an image of the resulting scene and used it to prepare the map in ArcMap.

Geocoding and Network Analysis Lab

Hi GIS partners,

      This lab was about learning how to transform a description of a location to a location on earth, a process better known as geocoding, and how to perform a Network Analysis. Using a Map Locator, the reference layer "LakeRoads", and the ArcGIS Geocoder, I geocoded the addresses of the Emergency Medical Services Stations (EMS) in Lake County, Florida that had been previously compiled in a xls file table. It took me a bit of practice and time to complete the geocoding as I had to use the Interactive Rematch - Geocoding Result window to manually rematch one by one some addresses that could not be automatically geocoded. After that, I selected three of the geocoded EMS and performed a Network Analysis to find the best route to travel among them. This is the map that I prepared:

Thursday, March 30, 2017

Vector2 Lab

Hi GIS partners,

      The purpose of this week's lab was to determine and display the possible campsites in De Soto National Forest in Brooklyn, Mississippi following certain criteria. The possible campsites should be located at a certain distance from lakes, rivers and roads in the area to facilitate easy access to them. Also, the campsites should not be located within a conservation area. In preparing the map I used the Analysis Tool to create fixed and variable distance buffers for the Road and Lake/river layers, respectively. At this point, I took the time to practice how to run multiple buffers at once to save time using ArcPython. For some reason, I could not run the buffers at once but I was able to copy and paste the original script, modify it and run it for each subsequent buffer one at a time, by which I ended up saving some time. Finally, I used "Select by Attribute", SQL Query, and the "Union" and "Erase" Tools to overlay the buffers and identify the possible campsites. Alternatively, I ran an "Intersect" and obtained exactly the same results as before.

Thursday, March 9, 2017

GIS Data Search Lab

Hi again GIS partners,

    The GIS Data Search Lab was very intensive for me because of all the research and retrieval of spatial data from several web-based data repositories prior to the preparation of the maps, but at the same time it was very rewarding because of what I learned through the whole process. I downloaded my spatial data from the Florida Geographic Data Library (FGDL), LABINS.org, and the United States Geological Survey (USGS) website. The projection of my digital orthographic quarter-quad is NAD_1983_State Plane_Florida_West_FIPS_0902_Feet; all the vector layers and remaining rasters were reprojected accordingly. I isolated and/or clipped these layers to determine their extent for displaying purposes. Some of the tools or methods that I used to prepared the maps are the Project, Project Raster, and Analysis Clip Tools, and the Data Frame Clipping Method. The following are the three maps that I prepared.

    This first map provides an overview of Polk County. It includes major cities, an interstate, major rivers, major waterbodies (lakes), and an elevation layer of the county (with hill-shade effect). It also includes an enlarged digital image of the Bartow City area and associated elevation data.

    For this second map, I adjusted the symbology of the strategic habitat layer to show strategic habitats by richness level instead of strategic habitats by species. I did this because I was mainly focus on displaying the location and importance of these areas. One of the things that calls my attention in this map is that interestingly the strategic habitat areas not necessarily match the conservation lands.  

    Finally, this third map basically shows vegetated areas in Polk County. I adjusted the symbology using unique values and a color ramp that shows very clearly the distinct types of vegetation.

Sunday, February 26, 2017

Projections Part 2 Lab


 Hi GIS partners,

      The purpose of this week's lab map was to display the petroleum tank contamination sites within a specific area of interest in Escambia County in Florida.  The vector data for the Florida's county boundaries, major roads and Quad Index was dowloaded from the FGDL website and reprojected. The coordinates from Escambia County Storage Tank Contamination Monitoring tabular data were converted from DMS to decimal degree. After that, the tabular data was exported as a shapefile, its spatial reference was defined, and the layer was projected. Finally, the raster data was dowloaded from Labings.org, defined and projected. I chose Molino in Escambia County as my area of interest. All layers were projected or reprojected to NAD_1983_2011_StatePlane_Florida_North_FIPS_0903_Ft_US.

     I had some obstacles throughout this lab to include problems with the transferring of files from local to S drives. However, following instructor guidelines I started using eDesktop for GIS for all my file transfers, which proved to be the best option for me. As a result of this lab, I feel confident dowloading spatial data from web-based data repositories, converting coordinates and creating shapefiles from tabular data, defining a spatial reference, and projecting data.  

Thursday, February 16, 2017

Projections Part 1

As part of this lab, I had to create a map showing how the calculated area of select counties in Florida varies whenever the data is represented in different map projections. Using the Project Tool from the Tool Box I re-projected the “cntbnd” shapefile from the Albers Conic Equal Area to the UTM Zone 16N projection. In this case, I had to perform a Geographic Transformation to ensure that the UTM Zone 16N was in the same geographic coordinate system as the Albers. After that, I re-projected the original “cntbnd” shapefile to the State Plane North projection. This time I did not have to perform a Geographic Transformation because both projections were in the same coordinate system. I created three data frames to compare the calculated area data for the selected counties in the three different projections. For this Summary Template, I created a comparative table where I captured this data. However, for my map, I decided to use the legend to display the same data. To do that I created shapefiles of the county selections in each projection and symbolized these shapefiles to color-code the selected counties and to display their calculated areas in the Table of Contents and in the Legend.

Below is the map that I created. Of the three projections shown in the map, the Albers more accurately represents area across the globe. Because the UTM Zone 16N and State Plane North only cover different extents of the northwestern region or “panhandle” of Florida, the calculated area of counties within the intended area of coverage of these projections will be more accurate than the calculated area of outlier counties. Moreover, the calculated area of counties that are farther away from the UTM Zone 16N and the State Plane North (e.g. Miami-Dade) will diverge significantly between these two projections.

This lab helped me understand the rationale behind projections and performing geographic transformations. I’m confident that I can apply this knowledge in future GIS projects.