## 2016 QUARTER 03

##### DC-18 - Algorithms and processing
• Differentiate supervised classification from unsupervised classification
• Describe the sequence of tasks involved in the geometric correction of the Advanced Very High Resolution Radiometer (AVHRR) Global Land Dataset
• Compare pixel-based image classification methods with segmentation techniques
• Explain how to enhance contrast of reflectance values clustered within a narrow band of wavelengths
• Describe an application of hyperspectral image data
• Produce pseudocode for common unsupervised classification algorithms, including chain method, ISODATA method, and clustering
• Calculate a set of filtered reflectance values for a given array of reflectance values and a digital image filtering algorithm
• Describe a situation in which filtered data are more useful than the original unfiltered data
• Perform a manual unsupervised classification given a two-dimensional array of reflectance values and ranges of reflectance values associated with a given number of land cover categories
##### AM-02 - Analytical approaches
• Compare and contrast spatial statistical analysis, spatial data analysis, and spatial modeling
• Compare and contrast the methods of analyzing aggregate data as opposed to methods of analyzing a set of individual observations
• Define the terms spatial analysis, spatial modeling, geostatistics, spatial econometrics, spatial statistics, qualitative analysis, map algebra, and network analysis
• Differentiate between geostatistics and spatial statistics
• Discuss situations when it is desirable to adopt a spatial approach to the analysis of data
• Explain what is added to spatial analysis to make it spatio-temporal analysis
• Explain what is special (i.e., difficult) about geospatial data analysis and why some traditional statistical analysis techniques are not suited to geographic problems
• Outline the sequence of tasks required to complete the analytical process for a given spatial problem
• Compare and contrast spatial statistics and map algebra as two very different kinds of data analysis
##### AM-11 - Analyzing multidimensional attributes
• Relate plots of multidimensional attribute data to geography by equating similarity in data space with proximity in geographical space
• Conduct a simple hierarchical cluster analysis to classify area objects into statistically similar regions
• Perform multidimensional scaling (MDS) and principal components analysis (PCA) to reduce the number of coordinates, or dimensionality, of a problem
• Produce plots in several data dimensions using a data matrix of attributes
• Assemble a data matrix of attributes
##### KE-04 - Application user assessment
• Identify current and potential users of geospatial technology in an enterprise
• Identify new geographic tasks or information that align with institutional missions and goals
• Educate potential users on the value of geospatial technology
• Classify potential users as casual or professional, early adopters or reluctant users
• Recognize geographic tasks and geographic information that already exist in an enterprise
• Evaluate the potential for using geospatial technology to improve the efficiency and/or effectiveness of existing activities
• Differentiate the concepts of efficiency and effectiveness in application requirements
##### DA-02 - Applications and settings
• Describe how sea surface temperatures are mapped
• Explain how sea surface temperature maps are used to predict El Niño events
• Outline a plausible workflow used by MDA Federal (formerly EarthSat) to create the high-resolution GEOCOVER global imagery and GEOCOVER-LC global land cover datasets.
• Outline a plausible workflow for habitat mapping, such as the benthic habitat mapping in the main Hawaiian Islands as part of the NOAA Biogeography program
##### DA-07 - Applications in federal government
• List and describe the types of data maintained by federal governments
• Explain how geospatial information might be used in a taking of private property through a government’s claim of its right of eminent domain
• Describe how geospatial data are used and maintained for land use planning, property value assessment, maintenance of public works, and other applications
• Explain the concept of a “spatial decision support system”
##### DA-05 - Applications in local government
• List and describe the types of data maintained by local governments
• Explain how geospatial information might be used in a taking of private property through a government’s claim of its right of eminent domain
• Describe how geospatial data are used and maintained for land use planning, property value assessment, maintenance of public works, and other applications
• Explain the concept of a “spatial decision support system”
##### DA-06 - Applications in state government
• List and describe the types of data maintained by state governments
• Explain how geospatial information might be used in a taking of private property through a government’s claim of its right of eminent domain
• Describe how geospatial data are used and maintained for land use planning, property value assessment, maintenance of public works, and other applications
• Explain the concept of a “spatial decision support system”
##### AM-62 - Approaches to point, line, and area generalization
• Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)
• Explain why areal generalization is more difficult than line simplification
• Explain the logic of the Douglas-Poiker line simplification algorithm
• Explain the pitfalls of using data generalized for small scale display in a large scale application
• Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals
• Evaluate various line simplification algorithms by their usefulness in different applications
• Discuss the possible effects on topological integrity of generalizing data sets
##### DM-44 - Approximating the Earth's shape with geoids
• Explain why gravity varies over the Earth’s surface
• Explain how geoids are modeled
• Explain the role that the U.S. National Geodetic Survey plays in maintaining and developing geoid models
• Explain the concept of an equipotential gravity surface (i.e., a geoid)