Morgan Taylor

Morgan Taylor

Part 1

1. Do the points and lines represent the data with the same level of abstraction? Discuss in terms of their representation of the two data layers (cities, roads) that we have added so far, and in terms of other types of data that they might represent.

In computer science, abstraction is the act of reducing and factoring out details as to focus on just a few concepts at a time. Points and lines do not represent data with the same level of abstraction;points represent discrete data whereas lines represent more of continuous data. In the terms of the data layers used in Part 1 of this lab, cities represented by points displayed exact locations on the map, where as the roads represented by lines were continuous and represented more of an area that a city was located near. Other types of data are similar, for example using a map of a park where water fountains are represented by points and the sidewalks are represented by lines. The sidewalks are continues data that is related to the points of the water fountains.

2. What happens when you use the identify tool? Is the option to change the layer(s) beingidentified useful?

When you use the identify tool, you have the ability to identify an area of the map that you click on. By identify, the button will provide with information identifying the selected data. The identify button also has the ability to specify the exact data to identify by changing the “Identify From” menu to include just the top most layer, visible layer, selectable layers, or all layers. This option is very useful because one can identify the data they are most interested in efficiently, combining any layers they wish to learn more about.

3. Why do you think the Field Definition requires that you differentiate between text and numeric

data types? Why do you need to specify the field width?

The Field Definition requires that you differentiate between text and numeric data types because there are seven field types in ArcMap and by differentiating, the data will be stored within the table as nominal data. You need to specify the field width because the field type is based on precision and nominal data would not have to be expressed more precisely than just a few characters.

4. What has changed in the table after joining?

After joining, the attribute table for States has an added column of weather pertaining to the specific states that we chose to define in this lab.

5. How is the original attribute data from the States layer distinguished from the Weather data thatyou joined?

The original attribute data is still available in the attribute table, the weather was just added along to the end as the information that was defined for the certain states.

6. What would happen if you tried to join the attributes from the States layer to the Weather data

(rather than joining the Weather data to the States data as you just did)?

If you tried to join the attributes from the States layer into the Weather data, the states data would only be provided for those that we identified the weather for. We only specified data for 11 states, which would not join the entire States layer into the weather data.

7. Print screen of selected record

8. Print screen of new attribute table

Part 2

9. What does the reclassification step in Step 1 accomplish?

The reclassification step allows us to classify the “classes” that are graphed of distances from major roads. We choose to classify the distance scores to be graphed as:

0 - 60 = 10

60.001 - 200 = 8

200.001 - 1000 = 4

1000.001 - 3000 = 2

3000.001 - 4768.773 = 1

10. Please include a JPEG of roadscore (end of Step 1). This should be a completed map (i.e.

ready for display), exported into your student folder, and inserted as a picture into lab report.

11. Please include a JPEG of hydroscore (end of Step 2). This should be a completed map (i.e.

ready for display), exported into your student folder, and inserted as a picture into lab report.

12. At the end of Step 3, what does the map tell you in terms of the developer’s office building

project? What do the highest scores represent? What do the lowest scores represent?

At the end of Step 3, the map tells you that the high scores represent the least suitable places to build the office building and the lower scores represent the most suitable places to build the office building.

13. What does Step 4 accomplish towards producing the final suitability data layer?

Step 4 factors in zoning codes to generate a data layer including final suitability scores. The zoning codes specify where the project is allowed to be built in accordance to where the optimum areas are identified.

14. Please include a JPEG of final suitability layer (end of Step 4). This should be a completed map(i.e. ready for display), exported into your student folder, and inserted as a picture into labreport.

15. Prepare a brief executive summary (~2 paragraphs) to the developer, summarizing your results.Include a short description of the analysis you performed and indicate the locations you thinkwould be the best choices for her office project.

The results of the search to find the most suitable location for the office project would found by mapping the location of major roads and the available land in close proximity in order to ease transportation. Also, locations of streams and their proximity to building sites was mapped in order to avoid less desirable areas that have to possibility of confronting flooding issues. When the two maps were overlaid and areas that were located within Chapel Hill's Office/Institutional (O/I) or Mixed-Use and Office/Institutional (MU-OI) zoning districts were identified.

The perfect areas for the office building project would be in an area in southeast Chapel Hill and a few identified in northwestern Chapel Hill. The areas are specifically found around the borders of Chapel Hill towards Carrboro.