## 2021 QUARTER 02

##### DM-09 - The hexagonal model
• Illustrate the hexagonal model
• Explain the limitations of the grid model compared to the hexagonal model
• Exemplify the uses (past and potential) of the hexagonal model
##### GS-01 - The legal regime
• Discuss ways in which the geospatial profession is regulated under the U.S. legal regime
• Compare and contrast the relationship of the geospatial profession and the U.S. legal regime with similar relationships in other countries
##### DM-15 - The network model
• Define the following terms pertaining to a network: Loops, multiple edges, the degree of a vertex, walk, trail, path, cycle, fundamental cycle
• List definitions of networks that apply to specific applications or industries
• Create an adjacency table from a sample network
• Explain how a graph can be written as an adjacency matrix and how this can be used to calculate topological shortest paths in the graph
• Create an incidence matrix from a sample network
• Explain how a graph (network) may be directed or undirected
• Demonstrate how attributes of networks can be used to represent cost, time, distance, or many other measures
• Demonstrate how the star (or forward star) data structure, which is often employed when digitally storing network information, violates relational normal form, but allows for much faster search and retrieval in network databases
• Discuss some of the difficulties of applying the standard process-pattern concept to lines and networks
• Demonstrate how a network is a connected set of edges and vertices
##### FC-20 - The power of maps
• Describe how maps such as topographic maps are produced within certain relations of power and knowledge
• Discuss how the choices used in the design of a road map will influence the experience visitors may have of the area
• Explain how legal issues impact the design and content of such special purpose maps as subdivision plans, nautical charts, and cadastral maps
• Exemplify maps that illustrate the provocative, propagandistic, political, and persuasive nature of maps and geospatial data
• Demonstrate how different methods of data classification for a single dataset can produce maps that will be interpreted very differently by the user
• Deconstruct the silences (feature omissions) on a map of a personally well known area
• Construct two maps about a conflict or war producing one supportive of each side’s viewpoint
##### KE-01 - The process of GIS&T design
• Describe the major approaches to the design of geospatial systems
• Analyze past cases to identify best practices of design and implementation
• Compare and contrast the relative merits of the use-case driven and architecture-centric design processes
##### DM-07 - The Raster Data Model

The raster data model is a widely used method of storing geographic data. The model most commonly takes the form of a grid-like structure that holds values at regularly spaced intervals over the extent of the raster. Rasters are especially well suited for storing continuous data such as temperature and elevation values, but can hold discrete and categorical data such as land use as well.  The resolution of a raster is given in linear units (e.g., meters) or angular units (e.g., one arc second) and defines the extent along one side of the grid cell. High (or fine) resolution rasters have comparatively closer spacing and more grid cells than low (or coarse) resolution rasters, and require relatively more memory to store. Active research in the domain is oriented toward improving compression schemes and implementation for alternative cell shapes (such as hexagons), and better supporting multi-resolution raster storage and analysis functions.

##### DM-13 - The topological model
• Define terms related to topology (e.g., adjacency, connectivity, overlap, intersect, logical consistency)
• Describe the integrity constraints of integrated topological models (e.g., POLYVRT)
• Discuss the historical roots of the Census Bureau’s creation of GBF/DIME as the foundation for the development of topological data structures
• Explain why integrated topological models have lost favor in commercial GIS software
• Evaluate the positive and negative impacts of the shift from integrated topological models
• Discuss the role of graph theory in topological structures
• Exemplify the concept of planar enforcement (e.g., TIN triangles)
• Demonstrate how a topological structure can be represented in a relational database structure
• Explain the advantages and disadvantages of topological data models
• Illustrate a topological relation
##### DM-10 - The Triangulated Irregular Network (TIN) model
• Describe how to generate a unique TIN solution using Delaunay triangulation
• Describe the architecture of the TIN model
• Construct a TIN manually from a set of spot elevations
• Delineate a set of break lines that improve the accuracy of a TIN
• Describe the conditions under which a TIN might be more practical than GRID
• Demonstrate the use of the TIN model for different statistical surfaces (e.g., terrain elevation, population density, disease incidence) in a GIS software application
##### FC-27 - Thematic Accuracy Assessment

Geographic Information System (GIS) applications often involve various analytical techniques and geographic data to produce thematic maps for gaining a better understanding of geospatial situations to support spatial decisions. Accuracy assessment of a thematic map is necessary for evaluating the quality of the research results and ensuring appropriate use of the geographic data. Thematic accuracy deals with evaluating the accuracy of the attributes or labels of mapped features by comparing them to a reference that is assumed to be true. The fundamental practice presents the remote sensing approach to thematic accuracy assessment as a good guidance. For instance, the accuracy of a remote sensing image can be represented as an error matrix when the map and reference classification are conducted based on categories. This entry introduces basic concepts and techniques used in conducting thematic accuracy with an emphasis on land cover classification based on remote sensing images. The entry first introduces concepts of spatial uncertainty and spatial data quality standards and further gives an example of how spatial data quality affects thematic accuracy. Additionally, the entry illustrates the techniques that can be used to access thematic accuracy as well as using spatial autocorrelation in thematic accuracy sampling design.

##### AM-86 - Theory of error propagation
• Describe stochastic error models
• Exemplify stochastic error models used in GIScience