Part I1. Points and lines do not represent the same level of abstraction, because a point represents one specific region or place, while a line does not represent a region, but a demarcation orsomething which connects or divides two certain points. Cities are represented by a pointbecause they can be defined by one area, whereas a road is represented by a line because it is compromised of many points one after the other. A point could not only represent a city, but a landmark, a home, or a school for example. Lines could also represent boundaries of provinces, states, or coastlines.2. Using the identify tool allows you to identify a certain part or region of the data. The option to change the layers of identification is very useful because it allows you to furtherexamine certain attributes within that region which has been initially identified.3. With field definition, you should differentiate between text and numeric data types because different types of data are represented by different types of things. For example, the name of a state would represent text data, whereas temperature would represent numeric data. Field width should also be specified because you need the correct boundaries so that your data will be best viewed.4. After joining, the data from the weather table was inserted into the data in the states attribute table.5. The original states attribute table is distinguished from the weather data which was joinedin that all the other information from the fifty states remains in tact, with only the weatherdescriptions inserted into the ten states chosen being the difference, along with the new fields created.6. If we tried to do the reverse, and join the states table into the weather table, there would probably be an error, because the weather table could not support the information from the states attribute table.7.The record selected is the state of Utah.8.New fields from weather table at the far rightPART II1. The reclassification in Step 1 gives new values for the distances to be classified as. Distances were now assigned to five different categories of length.2. At the end of step 3, the map uses various colors to show the suitability of the land. The higher numbers represent better suitability for building, while the lower numbers represent low suitability.3. Step 4 is the culmination of all the reclassifications we have done, meaning it is the best map to use for determining suitability for building structures.4. To the developer,My analysis of the Chapel Hill area has concluded that there are a few places where building your office building would be viable. I have done several reclassifications of data from Chapel Hill, including data on roads and streams/rivers. Ihave put these reclassifications together to for the best suitability index for building. It is this index, which includes roads, that translates into the areas I feel you should build.Looking at the final map, there are four major areas with the best suitability. Because you wanted to building next to major roads, I would recommend you choose either of the two areas on the right hand side of the map (the areas with a mixture of colors indicating better suitability values) because they are adjacent to highway 15-501. Iwould also recommend the large area on the mid-left hand side of the map, as it is closer to UNC Chapel
View Full Document
Unlocking...