2019 QUARTER 02

A B C D E F G H I K L M N O P R S T U V W
KE-26 - Incorporating GIS&T into existing job classifications
  • Select two effective methods of overcoming resistance to change
  • Illustrate how methods for overcoming resistance to change can aid implementation of a GIS
  • Explain how resistance to change and the need to standardize operations when trying to incorporate GIS&T can promote inclusion into existing job classifications
PD-02 - Integer programming
  • Explain why integer programs are harder to solve than linear programs
  • Differentiate between a linear program and an integer program
AM-16 - Interpolation methods
  • Identify the spatial concepts that are assumed in different interpolation algorithms
  • Compare and contrast interpolation by inverse distance weighting, bi-cubic spline fitting, and kriging
  • Differentiate between trend surface analysis and deterministic spatial interpolation
  • Explain why different interpolation algorithms produce different results and suggest ways by which these can be evaluated in the context of a specific problem
  • Design an algorithm that interpolates irregular point elevation data onto a regular grid
  • Outline algorithms to produce repeatable contour-type lines from point datasets using proximity polygons, spatial averages, or inverse distance weighting
  • Implement a trend surface analysis using either the supplied function in a GIS or a regression function from any standard statistical package
  • Describe how surfaces can be interpolated using splines
  • Explain how the elevation values in a digital elevation model (DEM) are derived by interpolation from irregular arrays of spot elevations
  • Discuss the pitfalls of using secondary data that has been generated using interpolations (e.g., Level 1 USGS DEMs)
  • Estimate a value between two known values using linear interpolation (e.g., spot elevations, population between census years)
AM-17 - Intervisibility
  • Define “intervisibility”
  • Outline an algorithm to determine the viewshed (area visible) from specific locations on surfaces specified by DEMs
  • Perform siting analyses using specified visibility, slope, and other surface related constraints
  • Explain the sources and impact of errors that affect intervisibility analyses
AM-08 - Kernels and density estimation
  • Describe the relationships between kernels and classical spatial interaction approaches, such as surfaces of potential
  • Outline the likely effects on analysis results of variations in the kernel function used and the bandwidth adopted
  • Explain why and how density estimation transforms point data into a field representation
  • Explain why, in some cases, an adaptive bandwidth might be employed
  • Create density maps from point datasets using kernels and density estimation techniques using standard software
  • Differentiate between kernel density estimation and spatial interpolation
AM-37 - Knowledge discovery
  • Explain how spatial data mining techniques can be used for knowledge discovery
  • Explain how a Bayesian framework can incorporate expert knowledge in order to retrieve all relevant datasets given an initial user query
  • Explain how visual data exploration can be combined with data mining techniques as a means of discovering research hypotheses in large spatial datasets
AM-29 - Kriging methods
  • 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
KE-09 - Labor and management
  • 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
DC-02 - Land records
  • 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
AM-54 - Landscape Metrics

Landscape metrics are algorithms that quantify the spatial structure of patterns – primarily composition and configuration - within a geographic area. The term "landscape metrics" has historically referred to indices for categorical land cover maps, but with emerging datasets, tools, and software programs, the field is growing to include other types of landscape pattern analyses such as graph-based metrics, surface metrics, and three-dimensional metrics. The choice of which metrics to use requires careful consideration by the analyst, taking into account the data and application. Selecting the best metric for the problem at hand is not a trivial task given the large numbers of metrics that have been developed and software programs to implement them.

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