GIS 1 Lab 4

Goals and Background: The goal of this lab was to assess my working knowledge of both spatial and attribute queries. In order to display my knowledge I used these two types of queries to find features that fit certain criteria, then used and displayed my understanding of cartography in ArcMap by creating maps to display the counties fitting the specific criteria. I also had to answer specific questions about statistics on the features that met the criteria which took knowledge of navigating and manipulating attribute table data.

Methods:

Part 1 - County Attribute Queries of the US

I found data from the USA geodatabase from my textbook cited below and set my geoprocessing workspace and scratch space to appropriate folders first for each map.

Map 1: For this map I was asked to write a multiple criteria query that will return counties with population between 3000 and 4000 people in 2010 and also all counties in 2010 that had a population density of at least 1000 persons per square mile. In order to do this made a new map document, and imported my counties shapefile from my geodatabase. I then opened the select by attributes window from the selection drop-down menu and used the following SQL expression:

This returned a selection of counties meeting the criteria. I right clicked on the counties layer in the table of contents, then clicked selection, create new layer from selection. This layer I named "Counties Meeting Criteria". gave a contrasting color by clicking the color box under the layer label. I then found a scale for the map that looked good in layout view and used the Insert drop-down menu to create a title, legend, my name, a north arrow, and a scale bar, then used the layout view to Place and size everything in a neat fashion. In order to answer statistical questions about the states queried I chose the statistics option after right clicking on the intended heading in the attribute table. 

Map 2: For this map I was asked to write a multiple criteria query that will return records for counties in Wisconsin, Texas, New York, Minnesota, and California where male population is greater than female population and also the number of seniors (age 65 and above) is over 6500. After clearing my previous selection, I used this query in the select by attributes window:

I was then asked how many counties met this criteria, which I answered using the selection count in the list by selection view of the table of contents. Other questions I was able to answer using visual inspection of the attribute window. In order to map these selected counties I right clicked on the counties layer and created another layer from the selection, now renaming the selection from my first map selection 1, and naming my new layer "Counties Meeting Criteria". I then mapped these counties using the same techniques as in making map 1.

Map 3: For map 3 I was required to build a query to add more states to the the last selection and also not include counties where there were less than 30,000 housing units. I used the following query:

(STATE_NAME = 'Wisconsin' OR STATE_NAME = 'Texas' OR STATE_NAME = 'New York' OR STATE_NAME = 'Minnesota' OR STATE_NAME = 'California' OR STATE_NAME = 'Washington' OR STATE_NAME = 'Maryland' OR STATE_NAME = 'Illinois' OR STATE_NAME = 'Nebraska' OR STATE_NAME = 'District of Columbia' OR STATE_NAME = 'Michigan') AND HSE_UNITS > 30000 AND AGE_65_UP > 6500 AND MALES > FEMALES

I then created a map of these counties manipulating layer names and creating a pleasing map with the same steps as map 1 and 2.

 

Part 2 - Mixed Queries of Wisconsin 

Map 4: For this map I downloaded data supplied by my professor which included Wisconsin specific data of rivers, roads, counties, lakes, and cities. I was asked to develop a query that will return cities in Wisconsin with 2007 population between 15,000 and 20,000 people, an area of the city being at least 5 square miles in land area, a female population that is greater than males, and also the cities had to be within 2 miles of a lake. For this task I started with an attribute query of the cities layer:

After this query selected these specific cities which met all criteria except that of being within 2 miles of a lake, I got to the spatial query to find the cities close to lakes. I clicked on selection, then select by location, then clicked on select from the currently selected features in in the selection method, targeting the cities layer, then setting all other settings as seen below:

The resulting selection I made a new layer from and created a pleasing map with the same tools used in above maps. I answered questions about statistics by using the statistics function after right clicking on the population field in the attribute table while having the cities selected.

Map 5: For this map I was required to select all segments of the rivers mentioned: CHIPPEWA R, EAU CLAIRE R, 'EMBARRASS R, FISHER R, HUNTING R, KINNICKINNIC R, MAUNESHA R, MILWAUKEE R, MOOSE R, NAMEKAGON R, PELICAN R, PLATTE R, and POTATO R. For this selection I used the following attribute query:

      "PNAME" = 'CHIPPEWA R' OR "PNAME" = 'EAU CLAIRE R' OR "PNAME" = 'EMBARRASS R' OR "PNAME" = 'FISHER R' OR "PNAME" = 'HUNTING R' OR "PNAME" = 'KINNICKINNIC R' OR "PNAME" = 'MAUNESHA R' OR "PNAME" = 'MILWAUKEE R' OR "PNAME" = 'MOOSE R' OR "PNAME" = 'NAMEKAGON R' OR "PNAME" = 'PELICAN R' OR "PNAME" = 'PLATTE R' OR "PNAME" = 'POTATO R'

This returned a selection of 80 segments of the named rivers, which I found the total length of all added by finding the sum in the statistics of the length field in the attribute table. I then changed the symbology of these selected rivers after making them a different layer and deleted the original rivers layer to remove clutter. Then I added roads, lakes, and county shapefiles and changed the symbology for them too in order to make a better looking map. I added other features to the map similar to the maps above, and changed the layout to portrait in order to make a pleasing map.

Results: These are the resulting maps of my work. 

Map 1

Map 2

Map 3

Map 4

Map 5

GIS 1 Lab 3

Goals and Background: The goal of this lab was to build good maps both dynamic and static, and learn how to work with external online data in the process. I went through the process of downloading, converting, and joining data tables with state and county boarder shapefiles to be able to map the data.

Methods: 

Part 1-Static Mapping

I first went to the U.S. Census Bureau website and used the advanced search tools on the left hand side to refine my search to 2010 SF1 100% data for all counties of Wisconsin. I next located and downloaded the P1 - Total Population 2010 Census Summary File in the .csv format. This file I opened in Microsoft Excel, saving the file again as a MS Excel workbook file, and converting all number data columns to the number format by right clicking the column once it was highlighted and clicking Format Cells. I next downloaded the Wisconsin counties shapefile by selecting the shapefile format and download, after clicking on geographies then map, after I had selected all counties in Wisconsin and the 2010 SF1 100% data dataset. 

I then opened ArcMap, and after setting my appropriate workspaces under Geoprocessing - Environments, imported my Wisconsin counties shapefile and my edited MS Excel table. Observing that both the stand alone table and the attribute table for my Wisconsin counties had GEO id fields, which matched states, I right clicked my shapefile in the table of contents, and clicked Join and Relates and then Join, then joined the tables using the GEO_ID and GEO#id fields as keys, selecting 'Keep all records". After checking that all my data was properly joined in the attribute table, I right clicked on this shapefile in the table of contents and clicked data, then export data. I saved this as a new shapefile, which included the old shapefile's data and my joined data. I next deleted the old shapefile and the old stand alone table after double checking that my exported data had all of the data that I needed.

I next mapped this new shapefile. I right clicked on the shapefile in the table of contents, selecting properties, then clicking on the symbology tab. On the symbology tab I choose the correct value field (D001), the graduated colors method under Quantities, then classified the data with Jenks Natural Breaks with six classes and an easy to understand color ramp. Under the coordinate system tab of the data frame properties I then chose an appropriate projection, the central Wisconsin state plane projection. I then worked in the layout view to craft a cartographically pleasing map, including scale, a neatline, a legend, and north arrow, and appropriate title and reference data. These were included using the buttons on the insert drop down menu. To clean up my map further, I turned of the map's boarder and tinkered with it and the other elements' scales. My map of population in Wisconsin counties is shown in Figure 1.

Figure 1

I next choose the average age data set  to map Wisconsin counties with. I found this data on the same Census Bureau website, under the same geography and dataset search criteria. I then edited this data the same in Excel, and imported it into ArcMap, as well as the same shapefile used for the population data, joining the two using the same key and exporting the new joined data as a shapefile all the same. After removing the old data from the data frame, and dragging in my new shapefile with all of my data, I symbolized this average age data with graduated colors and the same easy to understand color ramp. I did, however, change the classification system. This time I chose the equal interval classification with 5 classes due to the more normal but relatively flat distribution. I then also projected this data frame to the central Wisconsin state plane projection and edited the map for viewing under the layout view. This map of average data is shown in Figure 2.

Figure 2

Part 2-Dynamic Mapping

I logged into my ESRI account by clicking file, login, then signed in using my UWEC enterprise account. I then clicked file, share as, then service... In the wizard I clicked publish a service, chose my school's connection, then named my service (without spaces). I next turned on Feature Access and turned off Tiled Mapping, which would have taken up a lot of my schools credits in ESRI's online service interface. I then entered in descriptors under the Item Description tab, and shared my service with my school's geography department under the sharing tab. Clicking on the Analyze check mark in the upper right hand corner, I encountered no errors and published my service. I then went to My Content on ESRI's website in my browser after logging in, and clicked the down arrow, then add layer to map on the feature layer I had just published. I now clicked on the more options ... symbol in my data under Contents, and clicked Configure Pop-up in order to correctly configure pop up data for my map which can be seen on my map below (Figure 3).

Figure 3

Results: My resulting maps are shown in figures one, two, and three. 

Sources:

  Price, M. H. (2016). Mastering ArcGIS (7th ed.). Dubuque, IA: McGraw-Hill.

  

  Median Age by Sex (2010) [Downloaded File]. United States Census BureauURL: http://factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=DEC_10_SF1_P13&prodType=table

  Total Population (2010) [Downloaded File]. United States Census Bureau URL: http:/factfinder.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=DEC_10_SF1_P1&prodType=table