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2016 QUARTER 02
Knowledge Area
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Conceptual Foundations
Organizational and Institutional Aspects
Design Aspects
Data Modeling
Geospatial Data
Data Manipulation
Analytical Methods
Cartography and Visualization
Geocomputation
GIS&T and Society
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DM3-6 - Resolution
Illustrate the impact of grid cell resolution on the information that can be portrayed
Relate the concept of grid cell resolution to the more general concept of “support” and granularity
Evaluate the implications of changing grid cell resolution on the results of analytical applications by using GIS software
Evaluate the ease of measuring resolution in different types of tessellations
GC2-8 - Rule learning
Describe how a neural network may use training rules to learn from input data
GD9-3 - Sample intervals
Identify the fundamental principle of the sampling theorem for specifying a sampling rate or interval
Discuss what sampling intervals should be used to investigate some of the temporal patterns encountered in oceanography
Propose a sampling strategy considering a variable range in autocorrelation distances for a variable
GD9-1 - Sample size selection
Determine the minimum number and distribution of point samples for a given study area and a
Determine minimum homogeneous ground area for a particular application
Describe how spatial autocorrelation influences selection of sample size and sample statistics
Assess the practicality of statistically reliable sampling in a given situation
given statistical test of thematic accuracy
DN2-1 - Scale and generalization
Differentiate among the concepts of scale (as in map scale), support, scope, and resolution
Discuss the implications of tradeoff between data detail and data volume
Select a level of data detail and accuracy appropriate for a particular application (e.g., viewshed analysis, continental land cover change)
Defend or refute the statement “GIS data are scaleless”
Determine the mathematical relationships among scale, scope, and resolution, including Töpfer’s radical law
GD8-3 - Scanning and automated vectorization techniques
Outline the process of scanning and vectorizing features depicted on a printed map sheet using a given GIS software product, emphasizing issues that require manual intervention
AM8-3 - Semi-variogram modeling
List the possible sources of error in a selected and fitted model of an experimental semi-variogram
Describe the conditions under which each of the commonly used semi-variograms models would be most appropriate
Explain the necessity of defining a semi-variogram model for geographic data
Apply the method of weighted least squares and maximum likelihood to fit semi-variogram models to datasets
Describe some commonly used semi-variogram models
AM2-1 - Set theory
Describe set theory
Explain how logic theory relates to set theory
Perform a logic (set theoretic) query using GIS software
Explain how set theory relates to spatial queries
AM3-3 - Shape
Identify situations in which shape affects geometric operations
Develop a method for describing the shape of a cluster of similarly valued points by using the concept of the convex hull
Develop an algorithm to determine the skeleton of polygons
Find centroids of polygons under different definitions of a centroid and different polygon shapes
Calculate several different shape indices for a polygon dataset
Compare and contrast different shape indices, include examples of applications to which each could be applied
Explain what is meant by the convex hull and minimum enclosing rectangle of a set of point data
Exemplify situations in which the centroid of a polygon falls outside its boundary
Explain why the shape of an object might be important in analysis
GC4-4 - Simulated annealing
Outline the rationale for and usefulness of simulated annealing
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DM3-6 - Resolution