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
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)
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
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.
KE-26 - Incorporating GIS&T into existing job classifications