Map Projections: Part 2

This week's lab was a continuation of displaying data in the same projections. This was definitely the most challenging lab to date. I learned how to project different data files. I chose Pensacola, Florida for my aerials, created a shapefile of petroleum storage tank monitoring sites in Escambia County, and displayed the data over quad index and the counties of Florida. From the labins.org website, I learned how to navigate and searched for data files containing aerial images in Florida. From the 2004 RGB State Plane Units: FT MrSID link, I determined the file name by accessing the Geographic Profile>Quad>Dep Name and selected Pensacola, since it was a city in Escambia County, Florida. The quad number was 5258. I downloaded the file and saved to my data file. From fgdl.org, I searched Major Roads, and selected the MAJRDS_JAN18 file from the Florida Department of Transportation. I projected the data from Albers to NAD_1983_2011_StatePlane_Florida_North_FIPS_0903_Ft_US. FGDL.org is also where I obtained the quad index, and I selected the file USGS 1:24,000 Quarter-Quad Index. I also searched for county boundaries here and downloaded the cntbnd_sept15 file. I projected this file from Albers to NAD_1983_2011_StatePlane_Florida_North_FIPS_0903_Ft_US with the NAD_1983_To_Harn_Florida transformation. I accessed the EscambiaSTCM file from the R file and added two columns, the Ycoord and the Xcoord, in the excel spreadsheet. I added the XY Data on my map and transformed the data there. I did run into an issue here where the data points were thousands of miles away from Escambia county. It turned out that I needed to add a negative sign to my Y coordinates. This fixed the issue! The geographic coordinate sytem used for the shapefile created from the excel data was GCS_WGS_1984. When I had all the necessary data, shapefiles created, and projections finished, I was ready to create the map. I added the layers in this order to display so everything was viewable on the map: EscambiaSTMD_SO (excel shapefile), Major Roads, the quad file, the county layer, and the 4 aerial images. I made the quad file 40% transparent so both the quad layer and the county layer could be seen. I have included screenshots of my data and the data frame properties below. Enjoy!

Petroleum Storage Tank Monitoring Sites in Pensacola, FL

Map Projections: Part 1

Map projections are used to display 3 dimensional  areas in a 2 dimensional manner. This week we learned how to present the same dataset in three different map projections, so we could see the variation in area of each projection arranged. Different map projections vary in size and distortion. Understanding what each projection looks like and what data you are using it important in choosing which projection to use for your map. Uniformity in map projection choice is essential in making a map that is clean and represents the area and the data you are conveying. The map below shows 3 different map projections, Albers, UTM 16 N, and State Plane N, of four counties in Florida. There is a table provided with the square area in miles for each county in each projection.  According to the data in the  table referenced on the map, Miami-Dade County has the most deviation in comparison by area, followed by Polk County, Alachua County, and Escambia County. This is because the counties that are closest to the UTM 16 N and State Plane N zone display less of a difference in variation. UTM 16 N and State Plane N are limited to a smaller portion of the Florida panhandle and thusly will be more accurate showing the counties within their boundaries. Because of this, Albers, which is a global projection, is best used to signify Florida state. This week, the biggest challenge was formatting the table as neatly as possible. I chose to insert an Excel table in Microsoft Word and format it to an appropriate size and without gridlines. Then, I just copied and pasted in ArcMap. It was my favorite outcome of presenting the data, so I went with it! Projections has been the most challenging lab thus far. I hope I get comfortable with it soon, considering choosing the right ones dictates how well your map reads!

Albers, UTM, State Plane N Projections of Alachua, Escambia, Miami-Dade, and Polk Counties in Florida

Sharing GIS Maps and Data-Week 4 Lab

This week I completed a GIS project by making a map listing the Top 10 Coffee Shops in Houston, Texas.This was the first assignment where we learned how to create maps and data files that can be shared with others.  I created a public map in ArcGIS Online, created a map package to be viewed in ArcMap, and created a .kmz file to open the map in Google Earth. First, I had to gather data to prepare the maps. In ArcMap, I utilized ArcCatalog to add World Countries as a layer. In ArcGIS Online, I utilized the online database and selected the ESRI World Street Maps. I learned how to create my own data file to add to the map through excel. All that was required was to list each column by rank, name, address, state, zip, and URL, and save as a .txt document. This document was added to ArcGIS Online Map to convert the table to a shapepoint file, which is geocoding! The link provided below shows the map that was created. Next, I opened the Top 10 geocoded list in ArcGIS for Desktop.Through ArcCatalog>S:\Documents>ArcGIS>WebMaps>Top 10 Houston Coffee Shops>Features.gdb, I copied and pasted into my S:\Intro2GIS>Data working folder. After dragging the features.gdb to the layer in TOC, I exported the data and saved as a shapefile. When creating the web map, I optimized the Top 10 layer for pop-ups. In ArcMap, that information is displayed in the attribute table. This is done through the Layer Properties and Field tab, where you select what features you want displayed and rename the layers accordingly (you know, take out the underscores and such). To share the map package, I selected File>Share As>Map Package, filled in the Item Description, like tags and credits, added the .txt file in additional, analyzed, and uploaded package to my ArcGIS account online. To create a .kmz file, I opened my SharingGIS_SO.mxd file in ArcMap, used the Local Search tool to access Layer to KML (conversion) tool, saved, and then copied and pasted to my Local C drive. When I downloaded Google Earth on my Desktop, I was able to open this file easily. Personally, I feel like sharing the map package is the best way to share. The user then has access to all the data and can do any kinds of edits they so choose. I did like being able to just access the online map with a link. It was relatively simple to create and analyze all the different data files and convert the maps. I hope if you are ever in the Houston area, you go get a Crud from Boomtown Coffee! Enjoy!


http://arcg.is/11uWfS

Cartography: States of Mexico, Urban Areas of Mexico, Elevation of Mexico-Week 3 Lab

This week's lab focused on GIS Cartography. First, we learned how to explore ArcCatalog and how to organize spatial datasets. ArcCatalog catagorizes datasets through local files and geodatabases from the Web. Three deliverable maps were created and using ArcCatalog to make new .mxd files was easy and efficient. I created a new shapefile by exporting the data from Americas_Admin, using this layer’s source data as the coordinate system, and saving as S:\Cartography\Data\Mex_States.shp.  I created this layer and added to my map and removed the Americas_Admin layer and saved as GISCarto_map1.mxd. We focused on the Table of Contents and the 4 different views you can choose when working on a map. They are Order, Source, Visibility, and Selection. Map 1 displayed the Mexican States ranked by color in population groups. Map 2 displayed the Urban Areas with population greater than 1,000,000 which are located in Central Mexico. Map 3 displayed the elevation of the topography of Mexico. Producing each map was relatively simple-there was alot of time spend changing the symbology, such as font size, color, symbols, and placement properties. One thing that was a new learned outcome was how to convert labels to annotations. This is a useful tool when you are creating multiple maps and need to manipulate labels. For instance, for Map 2, I had to display the Urban Areas in Mexico with population>1,000,000. Annotations were created for these because in Map 3, the elevation map, all I had to do was delete all layers but the World Countries, add the elev_raster layer, and in Data View and while using the Selector Tool, I was able to click on each city label and delete them. As always, there was emphasis on adding the map essentials. This week we learned how to create a legend that is more complex than previous labs.  I inserted Legend and edited the Legend Properties. I unchecked “Show” in the General Tab so it would not list Legend. From Map Layers, I only added States of Mexico over to Legend Items. In the Frame tab, I chose 1.0 Border and added a Gap of 4 to X and Y. I chose a background color of white and added a Gap of 4 to X and Y on that as well. I changed the name of POP_ADMIN to Population. We also learned how to create dynamic texts to add the title, author, and date. This is done through Map Properties and typing in the information. Then, when you add each element, it automatically populates on the map. I must note that creating the annotations created a situation when making Map 3. The elevation color ramp would not populate until in Data Layout, I removed the annotations from the map, and then switched to Layout View and moved the Elevation layer to the top. This is an example of why understanding the different TOC views is important. While making Map 3, I learned the different between Classified Symbology and Stretched Symbology. Classified symbology assembles pixels together in a specific number of classes. Stretched symbology allows you to define a range of values and attaches a color ramp to display them. A stretched color ramp was chosen to accurately depict the elevation levels of Mexico. By the end of the lab, I learned how to access data files quickly and create multiple maps without doing each one step by step. The complexity of the process increases a little each week!