2016 QUARTER 02

A B C D E F G H I K L M N O P R S T U V W

List the conditions that make point pattern analysis a suitable process
Identify the various ways point patterns may be described
Identify various types of K-function analysis
Describe how Independent Random Process/Chi-Squared Result (IRP/CSR) may be used to make statistical statements about point patterns
Outline measures of pattern based on first and second order properties such as the mean center and standard distance, quadrat counts, nearest neighbor distance, and the more modern G, F, and K functions
Outline the basis of classic critiques of spatial statistical analysis in the context of point pattern analysis
Explain how distance-based methods of point pattern measurement can be derived from a distance matrix
Explain how proximity polygons (e.g., Thiessen polygons) may be used to describe point patterns
Explain how the K function provides a scale-dependent measure of dispersion
Compute measures of overall dispersion and clustering of point datasets using nearest neighbor distance statistics

Recognize the constraints that political forces place on geospatial applications in public and private sectors
Evaluate the influences of political ideologies (e.g., Marxism, Capitalism, conservative/liberal) on the understanding of geographic information
Evaluate the influences of political actions, especially the allocation of territory, on human perceptions of space and place

Calculate, in terms of ground area, the uncertainty associated with decimal coordinates specified to three, four, and five decimal places
Explain, in general terms, the difference between single and double precision and impacts on error propagation
Explain the concept of error propagation

Explain the distinction between primary and secondary data sources in terms of census data, cartographic data, and remotely sensed data
Describe a scenario in which data from a secondary source may pose obstacles to effective and efficient use

Describe the relationship between the semi-variogram and kriging
Explain why it is important to have a good model of the semi-variogram in kriging
Explain the concept of the kriging variance, and describe some of its shortcomings
Explain how block-kriging and its variants can be used to combine data sets with different spatial resolution (support)
Compare and contrast block-kriging with areal interpolation using proportional area weighting and dasymetric mapping
Outline the basic kriging equations in their matrix formulation
Conduct a spatial interpolation process using kriging from data description to final error map
Explain why kriging is more suitable as an interpolation method in some applications than others

Identify and define the parameters of a semi-variogram (range, sill, nugget)
Demonstrate how semi-variograms react to spatial nonstationarity
Construct a semi-variogram and illustrate with a semi-variogram cloud
Describe the relationships between semi-variograms and correlograms, and Moran’s indices of spatial association

Explain how spatial dependence and spatial heterogeneity violate the Gauss-Markov assumptions of regression used in traditional econometrics
Demonstrate how the spatial weights matrix is fundamental in spatial econometrics models
Demonstrate why spatial autocorrelation among regression residuals can be an indication that spatial variables have been omitted from the models
Demonstrate how spatially lagged, trend surface, or dummy spatial variables can be used to create the spatial component variables missing in a standard regression analysis
Describe the general types of spatial econometric models

Discuss the status of the concept of privacy in the U.S. legal regime
Explain how conversion of land records data from analog to digital form increases risk to personal privacy
Compare and contrast geographic information technologies that are privacy-invasive, privacy-enhancing, and privacy-sympathetic
Explain the argument that human tracking systems enable “geoslavery”
Explain how data aggregation is used to protect personal privacy in data produced by the U.S. Census Bureau

Identify some of the key commercial activities that provided an impetus for the development of GIS&T
Differentiate the dominant industries using geospatial technologies during the 1980s, 1990s, and 2000s
Describe the contributions of McHarg and other practitioners in developing geographic analysis methods later incorporated into GIS
Evaluate the correspondence between advances in hardware and operating system technology and changes in GIS software
Describe the influence of evolving computer hardware and of private sector hardware firms such as IBM on the emerging GIS software industry
Discuss the emergence of the GIS software industry in terms of technology evolution and markets served by firms such as ESRI, Intergraph, and ERDAS

Recognize the challenges of implementing and using geospatial technologies
Create a charter or hypothesis that defines and justifies the mission of a GIS to solve existing problems
Define an enterprise GIS in terms of institutional missions and goals
Identify geographic tasks for which particular geospatial technologies are not adequate or sufficient
Identify what is typically needed to garner support among managers for designing and/or creating a GIS

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