arc gis期末复习考点第十二章
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Chapter 12 Review Questions
1. Define a buffer zone.
A buffer zone is the area that is within the specified distance in a buffering operation.
2. Describe three variations in buffering.
The buffer distance can vary by the values of a given field. Buffering can be on either the left side or the right side of the line feature, instead of both sides. Buffer zones may remain intact so that each buffer zone is separate from others, or dissolved so that there are no overlapped areas between buffer zones.
3. Provide an application example of buffering from your discipline.
[A supermarket chain can buffer potential store locations with a buffer distance of 1 mile for demographic analysis.]
4. Describe a point-in-polygon overlay operation.
A point-in-polygon overlay operation uses a point layer as the input layer and a polygon layer as the overlay layer so that each point in the output is assigned with attributes of the polygon within which it falls.
5. A line-in-polygon operation produces a line layer, which typically has more records (features) than the input line layer. Why?
In a line-in-polygon operation, each line feature on the input layer is dissected by the polygon boundaries on the overlay layer. Therefore, the output has more records (line segments) than the input layer.
6. Provide an example of a polygon-on-polygon overlay operation from your discipline.
[An example of a polygon-on-polygon overlay operation is to overlay a land use layer on a soil layer in order to find the dominant soil type for each land use type.]
7. Describe a scenario, in which Intersect is preferred over Union for an overlay operation.
Every feature on an Intersect output will have attribute data from both of its inputs. Therefore, Intersect is preferred over Union if a project requires that attribute data be complete for each output feature.
8. Suppose the input layer shows a county and the overlay layer shows a national forest. Part of the county overlaps the national forest. We can express the output of an Intersect operation as [county] AND [national forest]. How can you express the outputs of a Union operation and an Identity operation?
Union: [county] OR [national forest]
Identity: ([county] AND [national forest]) OR [county]
9. Define slivers from an overlay operation.
Slivers are very small polygons along correlated or shared boundary lines (e.g., the study area boundary) of the input layers on an overlay output.
10. What is a minimum mapping unit? And, how can a minimum mapping unit be used to deal with the sliver problem?
A minimum mapping unit represents the smallest area unit that will be managed by a government agency or an organization. It can deal with the sliver problem by simply removing slivers that are smaller than the minimum mapping unit.
11. Although many slivers from an overlay operation represent inaccuracies in the digitized boundaries, they can also represent inaccuracies of attribute data (i.e., identification errors). Provide an example for the latter case.
[An example of identification errors is the misclassification of land use types, which can result from interpretation errors or from errors in data entry.]
12. Both nearest neighbor analysis and Moran’s I can apply to point features. How do they differ in terms of input data?
Nearest neighbor analysis uses only distances between points as inputs. Analysis of spatial autocorrelation, on the other hand, considers both the point locations and the variation of an attribute at the locations.
13. Explain spatial autocorrelation in your own words.
[Spatial autocorrelation measures the relationship among values of a variable
according to the spatial arrangement of the values. The relationship may be described as highly correlated if like values are spatially close to each other, and independent or random if no pattern is discernable from the arrangement of values.]
14. Both Moran’s I and the G-statistic have the global (general) and local versions. How do these two versions differ in terms of pattern analysis?
The global version calculates one statistic for an entire distribution, whereas the local version calculates one statistic for each feature (point or polygon).
15. The local G-statistic can be used as a tool for hot spot analysis. Why?
A cluster of high positive Z scores computed from local G-statistics suggests the presence of a cluster of high values, which is called a hot spot.
16. What does a Dissolve operation accomplish?
Dissolve aggregates features that have the same attribute value or values by removing the internal boundaries between them.
17. Suppose you have downloaded a vegetation map from the Internet. But the map is much larger than your study area. Describe the steps you will follow to get the vegetation map for your study area.
Step 1: Download or make a polygon layer of the study area.
Step 2: Perform a clip operation by using the vegetation map as the input layer and the study area map as the clip layer.
18. Suppose you need a map showing toxic waste sites in your county. You have downloaded a shapefile from the Environmental Protection Agency (EPA) website that shows toxic waste sites in every county of your state. What kind of operation will you use on the EPA map so that you can get only the county you need?
Solution 1: If the shapefile includes a field of county names, then one can run a select operation to select the county of interest.
Solution 2: Download or make a polygon layer of the county, and then perform a clip operation by using the vegetation map as the input layer and the study area map as the clip layer.
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