All Topics

CV-14 - Terrain Representation

Terrain representation is the manner by which elevation data are visualized. Data are typically stored as 2.5D grid representations, including digital elevation models (DEMs) in raster format and triangulated irregular networks (TINs). These models facilitate terrain representations such as contours, shaded relief, spot heights, and hypsometric tints, as well as automate calculations of surface derivatives such as slope, aspect, and curvature. 3D effects have viewing directions perpendicular (plan), parallel (profile), or panoramic (oblique view) to the elevation’s vertical datum plane. Recent research has focused on automating, stylizing, and enhancing terrain representations. From the user’s perspective, representations of elevation are measurable or provide a 3D visual effect, with much overlap between the two. The ones a user can measure or derive include contours, hypsometric tinting, slope, aspect, and curvature. Other representations focus on 3D effect and may include aesthetic considerations, such as hachures, relief shading, physiographic maps, block diagrams, rock drawings, and scree patterns. Relief shading creates the 3D effect using the surface normal and illumination vectors with the Lambertian assumption. Non-plan profile or panoramic views are often enhanced by vertical exaggeration. Cartographers combine techniques to mimic or create mapping styles, such as the Swiss-style.

DM-49 - Tessellated referencing systems
  • Explain the concept “quadtree”
  • Describe the octahedral quarternary triangulated mesh georeferencing system proposed by Dutton
  • Discuss the advantages of hierarchical coordinates relative to geographic and plane coordinate systems
AM-42 - The Classic Transportation Problem

The classic transportation problem concerns minimizing the cost of transporting a product from sources/supplies to destinations/demands. It is a network-flow problem that arises in industrial logistics and is often solved by linear programming (LP). The three inputs of the model are total units produced at each source, total units needed at each destination, and the cost to transport one unit from each source to each destination. And the objective is to minimize the total cost of transporting all units produced at sources to meet the demands at destinations. The problem solution includes three basic steps: 1) finding an initial basic feasible solution, 2) checking if the current solution is optimal (with the lowest costs), and improving the current solution through iteration. Solving such a problem relies strongly on the network data models, least-cost path algorithms, other functionalities in GIS. And an integrated framework is often adopted to utilize both GIS and non-GIS linear programming solvers to search for the optimal solution.

AM-21 - The Evolution of Geospatial Reasoning, Analytics, and Modeling

The field of geospatial analytics and modeling has a long history coinciding with the physical and cultural evolution of humans. This history is analyzed relative to the four scientific paradigms: (1) empirical analysis through description, (2) theoretical explorations using models and generalizations, (3) simulating complex phenomena and (4) data exploration. Correlations among developments in general science and those of the geospatial sciences are explored. Trends identify areas ripe for growth and improvement in the fourth and current paradigm that has been spawned by the big data explosion, such as exposing the ‘black box’ of GeoAI training and generating big geospatial training datasets. Future research should focus on integrating both theory- and data-driven knowledge discovery.

AM-34 - The Geographically Weighted Regression Framework

Local multivariate statistical models are increasingly encountered in geographical research to estimate spatially varying relationships between a response variable and its associated predictor variables. In geography and many other disciplines, such models have been largely embedded within the framework of regression and can reveal significantly more information about the determinants of observed spatial distribution of the dependent variable than their global regression model counterparts. This section introduces one type of local statistical modeling framework: Geographically Weighted Regression (GWR). Models within this framework estimate location-specific parameter estimates for each covariate, local diagnostic statistics, and bandwidth parameters as indicators of the spatial scales at which the modeled processes operate. These models provide an effective means to estimate how the same factors may evoke different responses across locations and by so doing, bring to the fore the role of geographical context on human preferences and behavior.

KE-29 - The geospatial community
  • Describe possible benefits to an organization by participating in a given society that is related to GIS&T
  • Discuss the value or effect of participation in societies, conferences, and informal communities to entities managing enterprise GIS
  • Identify conferences that are related to GIS&T
KE-30 - The geospatial industry
  • Assess the involvement of non-GIS companies (e.g., Microsoft, Google) in the geospatial industry
  • Describe three applications of geospatial technology for different workforce domains (e.g., first responders, forestry, water resource management, facilities management)
  • Explain why software products sold by U.S. companies may predominate in foreign markets, including Europe and Australia
  • Describe the U.S. geospatial industry including vendors, software, hardware and data
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