The first map we created was a map showing the variable buffer zones around lakes in Hugo, Washington County.
The buffer zones are defined as
Large Lake 500 meters
Medium Lake 150 meters
Small lake 50 meters
This gave us practice on creating buffers to move onto the next phase of maps
In this map we were to find suitable public and private land in Hugo, Washington County for Recreation areas and to calculate the total of Hectares for the suitable areas The suitable areas are depicted in lime green.
For the final map we did a buffer selecting private areas within the buffer zones of the lakes and within the buffer of the roads so a campground can have the features of access to the lakes and access to drive-in sites. From doing a Union of these two criteria I came up with the following map which shows only a few acceptable sites for the new proposed campground.
This lab basically got us to understand the concepts of buffers and created experience using the arc catalog analysis tools and was an easy lab to follow. It demonstrates the power of arc map to create selections using the buffer, union and erase tools.
This lab was a crash test for learning attribute tables and how to pull specific data out of a table using the query builder and selection by location and attribute. We also got to experience how to add new fields to an attribute table, reclassify large amounts of data to easier to view condensed classes, and insert text into fields and work with different values in the attribute table to get the desired results above. The hill shade demonstration in this lab I found very useful for creating visually stimulating maps. Overall this lab flowed well and beyond paying close attention to your query building was easy to follow
Map Showing number of People in the US in 2000
Map showing percent population change from 1990 to 2000
Population Difference between 1990 to 2000
Map of Population Density of People per Square Mile in the US
This lab was interesting in that it shows a definite shift of people moving from more rural areas to more urban areas of the country. It seems the southwest in particular also has a large shift in population density. Working with the census data can be useful in gaining understanding of demographics and how it affects issues at the county level as far as government resources and land development planning. Working with Census data can also be frustrating. There is such a huge amount of data available and just downloading and finding the data is just the first step in trying to get the data to work for you. For the second part of the lab I had to delete excess headings and trying to find null values in the data was an exercise in frustration too. I did attempt the join a few different ways for the race step and at first noticed the null values when opening the attribute table. After a few attempts to find the null value I gave up and got this map which only showed a few counties with a larger population of one race.
The area of interest I chose to display is Lower Glidden Lake in Idaho. This is an alpine lake that is accessible by car and stocked with rainbow trout. A great fishing day trip can be had at this lake.
Spatial Reference GCS_North American_1983
Datum North_Amercian_Datum _1983
Distance between Washington DC to Kabul found to be 8,818 miles
Distance between Washington DC to Kabul found to be 7,166 miles
Distance between Washington DC to Kabul found to be 10,157 miles
Cylindrical Equal Area
Distance between Washington DC to Kabul found to be 10,117 miles
The total Map Layout
Map projections are fascinating in that they can create very different results depending on the particular map project and what the creator intends to show. Each projection has its place and use and can produce wildly different distances and distortions. In the Equidistant projection the distances are accurate along the center of the projection but tends to distort away from the parallels. Conformal Projection maintains accuracy along smaller areas but distorts a great deal as you get to the poles. Equal area projections maintain accurate relative sizes of shapes. Overall every map projection has its distortions so it is up the creator to use the projection that best used for each application.
The distance exercise was interesting in that it forced you to see the distortions and in some cases double check your numbers that were quite different than other projections. So distance on a projection that doesn’t quite fit what you are trying to show can be inaccurate. The types of measurement in Arc map planar, Geodisic, Loxodrone and Great Eliptic showed even much variation depending on the measurement tool. In the Conformal and Equal Area projections the Geodisic and Great Eliptic tended to have similar measurements but when you switched to Equidistant projections these measurements seemed to have a bigger gap. In conclusion the map creator must pay attention to the projection and familiarize himself with the use of the map and whether area accuracy is more important or navigational/measurement use when choosing a projection.
My Maps Project for Alpine Lake Fishing