Chapter 13.
Geographic Query and Analysis
- What
is spatial analysis?
- How
did spatial analysis help John Snow identify the source of cholera?
- How
did Openshaw identify clusters of disease?
- What
is an inductive spatial analysis approach?
- What
is the deductive approach to spatial analysis?
- What
is the normative approach to spatial analysis?
- Briefly
define queries, spatial analytical measurements, spatial analytical
transformations, descriptive spatial summaries, optimization techniques,
and spatial analytical hypothesis testing?
- What
are local, focal, global, and zonal operations?
- Interrogating
a GIS database sometimes involves the use of a catalog view such as ArcCatalog. What ways does this type of query
system allow you to interrogate a database?
- What
types of information can you query in a map view such as ArcMap?
- What
types of information can you query in the table view?
- What
is exploratory spatial data analysis?
- What
does SQL have to do with querying a spatial database?
- What
is an algorithm?
- What
is a metric and what is the most common method?
- What
is a great circle equation?
- Why
are the lengths of polylines usually shorter
than the objects they represent?
- Are
measured areas also underestimates of the geographic objects they
represent? Why or why not?
- Is
there a difference between the length of a path on the Earth's surface and
a planar projection? Why or why not?
- What
algorithm can you use to measure the compactness of a polygon? What are
its parameters?
- What
are slope and aspect and what dataset would you usually use to create
them?
- The
spatial resolution used to calculate slope and aspect should always be
specified. Why?
- Slope
can be calculated three different ways including as an angle ranging from
0 to 90 degrees, rise over run (run defined as the horizontal distance
between two points, and rise over run (run defined as the hypotenuse of
the right-angled triangle). What are the implications of this?
- When
a GIS calculates slope and aspect, it does so by estimating slope at each
of the data points by comparing the elevation at that point to the
elevations of surrounding points. However, the number of surrounding
points used in the calculation varies, as do the weights given to each of
the surrounding points in the calculation. What are the implications
of this?
- What
is a buffer?
- Give
an example of why you might use a buffer transformation on a line.
- Raster
buffers can be based on attributes of cells rather than simple Euclidean
distances as with the vector model. Explain.
- What
is a point in polygon operation? Give an example of what it might be used
for.
- Using
discrete object polygon overlay can lead to large numbers of
polygons. Explain.
- In
two vector datasets of the same area there will almost certainly be
instances where lines in each dataset represent the same feature on the
ground. When overlaying them it leads to spurious polygons or
slivers. What are they and how can you avoid them by using a
tolerance value?
- Raster
overlay is simpler, but it produces a fundamentally different kind of
result. What is the basic concept behind raster overlay?
- What
is spatial interpolation and what does it have to do with Tobler's Law?
- What
is IDW and how do you calculate it?
- Explain
the weights scheme in IDW.
- IDW
interpolation may produce counterintuitive results in the areas of peaks
and pits, and outside the area covered by the data points. Why?
- Explain
the general idea behind Kriging.
- What
is a variogram?
- What
is an isotropic variogram as opposed to an
anisotropic variogram?
- Why
is Kriging better than IDW?
- Interpolation
and density measurements both begin with points and end with rasters. However, transforms sample measurements
from a field and the other transforms locations of discrete objects.
Which is which? Explain.
- There
is no such thing as population density only population density at a
spatial resolution. Density estimation with a kernel allows the
spatial resolution population density to be made explicit. Explain.