2018 QUARTER 02

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

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 the positions necessary to design and implement a GIS
Discuss the advantages and disadvantages of outsourcing elements of the implementation of a geospatial system, such as data entry
Evaluate the labor needed in past cases to build a new geospatial enterprise
Create a budget of expected labor costs, including salaries, benefits, training, and other expenses

Distinguish between GIS, LIS, and CAD/CAM in the context of land records management
Evaluate the difference in accuracy requirements for deeds systems versus registration systems
Exemplify and compare deed descriptions in terms of how accurately they convey the geometry of a parcel
Distinguish between topological fidelity and geometric accuracy in the context of a plat map

Explain how knowledge of the history of the development of enterprise GIS can aid in an implementation process
Evaluate case studies of past GISs to identify factors leading to success and failure
Discuss the evolution of isolated GIS projects to enterprise GIS

Describe contracts, licenses, and other mechanisms for sharing geospatial data
Outline the terms of a licensing agreement with a local engineering consulting firm that a manager of a county government GIS office would employ if charged to recoup revenue through sale and licensure of county data

Describe the nature of tort law generally and nuisance law specifically
Describe strategies for managing liability risk, including disclaimers and data quality standards
Describe cases of liability claims associated with misuse of geospatial information, erroneous information, and loss of proprietary interests
Differentiate among contract liability, tort liability, and statutory liability

Discuss dynamic segmentation as a process for transforming between linear and planar coordinate systems
Construct a data structure to contain point or linear geometry for database record events that are referenced by their position along a linear feature
Explain how linear referencing allows attributes to be displayed and analyzed that do not correspond precisely with the underlying segmentation of the network features
Describe how linear referencing can eliminate unnecessary segmentation of the underlying network features due to attribute value changes over time
Demonstrate how linear referenced locations are often much more intuitive and easy to find in the real world than geographic coordinates

Describe an application in which a linear referencing system is particularly useful
Explain how the datum associated with a linear referencing system differs from a horizontal or vertical datum
Identify several different linear referencing methods (e.g., mileposts, reference posts, link and node) and compare them to planar grid systems
Identify the characteristics that all linear referencing systems have in common Unit GD4 Datums (core unit) “Horizontal” datums define the geometric relationship between a coordinate system grid and the Earth’s surface, where the Earth’s surface is approximated by an ellipsoid or other figure. “Vertical” datums are elevation reference surfaces, such as mean sea level.
Explain how a network can be used as the basis for reference as opposed to the more common rectangular coordinate systems
Discuss the magnitude and cause of error generated in the transformation from linear to planar coordinate systems

Describe the effect of non-stationarity on local indices of spatial association
Decompose Moran’s I and Geary’s c into local measures of spatial association
Compute the Gi and Gi* statistics
Explain how geographically weighted regression provides a local measure of spatial association
Explain how a weights matrix can be used to convert any classical statistic into a local measure of spatial association
Compare and contrast global and local statistics and their uses

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