GIS 205 Midterm

• Descriptive vs. prescriptive
• Deterministic vs. stochastic
• Static vs. dynamic
• Deductive vs. inductive

• Map-to-map transformation
• Image-to-map transformation

D. Affine

A. True

A. Shape

C. Parallelism of lines

B. Projective

D. All of the above.

The acceptability of the 6 coefficients, as estimated from the control points, following a transformation.

• Nearest neighbor
• Bilinear interpolation
• Cubic convolution

D. Nearest neighbor

C. Bilinear interpolation

C. Cubic convolution

A. Less than 1

D. Both

B. Moran's I < E(I)

The distance between the raw score and the population mean.

Standard deviations.

Local Indicators of Spatial Association; A local version of Moran's I, this method calculates the z-score for each feature. A more negative Z means that the feature is is adjacent to dis-similar features; a more positive Z means that the feature is adjacent to similar features.

C. A cluster of high values.

Local methods apply a single mathematical function repeatedly to small subsets of the total set of observed data. Global methods apply a single mathematical function to all observed data points; this generally produces smooth surfaces.

Exact methods honor all observed points for which data are available, without smoothing or altering their values. This is most appropriate if there is a high degree of certainty attached to the measurements made at the points. Approximate methods do not have to honor all the observed data points; they can smooth the points to fit the general trend; most appropriate when there is uncertainty surrounding the measurements made at the sample points.

Deterministic methods are used when there is sufficient knowledge about the surface being modeled for its character to be described as a mathematical function; stochastic methods are used to handle uncertainty--random variation in the interpolated surface.

C. Exact vs. approximate

Kurtosis is a measure of the "peakedness" of the probability distribution of a real-valued random variable. High kurtosis means that the "bell curve" has a sharper peak and longer, thicker tails, while low kurtosis means a more rounded peak and shorter, thinner tails.

Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable. A negative skew means that the tail on the left side is longer than on the right and the bulk of the values lie to the right of the mean. A positive skew means a longer tail on the right side and the bulk of the values to the left of the mean. Zero skewness implies a more-or-less symmetrical distribution.

Central lines are the central parallel and the central meridian; toghether, they define the origin of a map projection. The standard line is the line of tangency between the map and the globe; it has no distortion and has the same scale as the reference globe.

• Origin
• Spheroid
• Separation of the spheroid and the Earth at the origin.

It serves as the reference or base for calculating the geographic coordinates of a location.

The Clarke 1866 spheroid.

GRS80

0.9996

The equator.

The normalized local scale, or the ratio of the local scale to the principal scale.

The scale of the reference globe.

D. The central lines

C. Arcs connect to each other at nodes

C. Arcs have directions and left and right polygons

A. An area is defined by a series of connected arcs

Because a shared or common boundary between 2 polygons is stored in the arc-coordinate list once, the number of data entries is reduced, and it is easier to update the polygons.

They can display more rapidly on the computer monitor than topology-based data, and they are non-proprietary.

The number of each adjacent triangle.

• Regions can have spatially joint or disjoint areas; polygons cannot.
• Regions may overlap; polygons cannot.

D. A principle used in object-oriented technology to hide the properties and methods of an object so that the object can be accessed only through the predefined interfaces

A data set that stores features of the same geometry type in a geodatabase.

A collection of feature classes in a geodatabase that share the same coordinate system and area extent.

A. True

It means that an object of a class can be created from an object of another class.

D. .mdb

B. .gdb

A digital orthophoto quad (DOQ).

A Digital Raster Graphic (a scanned image of a USGS topographic map).

B. False

A. True

A stochastic model considers the presence of some randomness in one or more of its parameters or variables, but a deterministic model does not.

• 1. Define the goals of the model.
• 2. Break the model down into elements and define each element's properties and the interactions between each element in the form of a diagram.
• 3. Implement and calibrate the model

It means the linking of a GIS to other computer programs through the transfer of data files.

• 1. Evaluate the relative importance of each criterion against other criteria.
• 2. Standardize the data for each criterion.
• 3. Calculate the index value for each unit area by summing the weighted criterion values and dividing the sum by the total of the weights.

C. Prescriptive

A common technique for displaying large raster data sets that uses resampling at different levels to produce the output raster.

In order to fill each pixel of the transformed image with a value derived from the original image.

D. Affine

Cubic convolution

Cubic convolution

Nearest neighbor

X Source and Y Source

A. True

D. 3

An overlay operation in which the same point features in the input layer are included in the output but each point is assigned the attributes of the polygon in which it falls.

Eliminate creates a new layer by removing features that meet a user-defined query expression, whereas erase removes features from the input layer.

C. Intersect

A. Union

B. Union

The spatial query

A group of cells of same values or like features.

• Union
• Intersect
• Analysis mask

Combine

B. False

• 1. Use the closest known points to the point to be estimated.
• 2. Select known points within a circle, the size of which depends on the sample size.

If spatial dependence exists in a data set, known points that are close to each other have small semivariances; points that are farther apart have larger semivariances.

The semivariance value at the distance 0 in a semivariogram.

The distance at which the semivariance starts to level off in a semivariogram.

The semivariance at which the leveling starts in a semivariogram.

The difference between the sill and the nugget in a semivariogram.

Delaunay triangulation is often used to prepare Thiessen polygons. It ensures that each known point is connected to its nearest neighbors, and that the resulting triangles are as equilateral as possible. Once this is done, Thiessen polygons can be constructed by connecting lines drawn perpendicular to the sides of each triangle at their midpoints.

Ordinary kriging assumes the absence of a drift and focuses on the spatially correlated component and uses the fitted semivariogram directly for interpolation. Universal kriging, however, assumes that the spatial variation in z values has a drift or a trend in addition to the spatial correlation between the sample points. In the first-order polynomial, M = b₁x_i + b₂y_i, M is the drift, x_i and y_i are the coordinates of the sampled point i, and b₁ and b₂ are the drift coefficients.

• Too little variation in the resdiuals for assessing uncertainty.
• More b_i coefficients, which must be estimated along with the weights, and thus a larger set of simultaneous equations to be solved.

Kriging