All Topics

A B C D E F G H I K L M N O P R S T U V W
AM-77 - Genetic algorithms and global solutions
  • Describe the difficulty of finding globally optimal solutions for problems with many local optima
  • Explain how evolutionary algorithms may be used to search for solutions
  • Explain the important advantage that GA methods may offer to find diverse near-optimal solutions
  • Explain how a GA searches for solutions by using selection proportional to fitness, crossover, and (very low levels of) mutation to fitness criteria and crossover mutation to search for a globally optimal solution to a problem
  • Compare and contrast the effectiveness of multiple search criteria for finding the optimal solution with a simple greedy hill climbing approach
DM-47 - Geographic coordinate system
  • Distinguish between various latitude definitions (e.g., geocentric, geodetic, astronomic latitudes)
  • Explain the angular measurements represented by latitude and longitude coordinates
  • Calculate the latitude and longitude coordinates of a given location on the map using the coordinate grid ticks in the collar of a topographic map and the appropriate interpolation formula
  • Mathematically express the relationship between Cartesian coordinates and polar coordinates
  • Calculate the uncertainty of a ground position defined by latitude and longitude coordinates specified in decimal degrees to a given number of decimal places
  • Use GIS software and base data encoded as geographic coordinates to geocode a list of address-referenced locations
  • Locate on a globe the positions represented by latitude and longitude coordinates
  • Write an algorithm that converts geographic coordinates from decimal degrees (DD) to degrees, minutes, seconds (DMS) format
FC-22 - Geometric primitives
  • Identify the three fundamental dimensionalities used to represent points, lines, and areas
  • Describe the data models used to encode coordinates as points, lines, or polygons
  • Critique the assumptions that are made in representing the world as points, lines, and polygons
  • Evaluate the correspondence between geographic phenomena and the shapes used to represent them
DM-56 - Georegistration
  • Differentiate rectification and orthorectification
  • Identify and explain an equation used to perform image-to-map registration
  • Identify and explain an equation used to perform image-to-image registration
  • Use GIS software to transform a given dataset to a specified coordinate system, projection, and datum
  • Explain the role and selection criteria for “ground control points” (GCPs) in the georegistration of aerial imagery
DA-25 - Geospatial Intelligence and National Security

GIS&T exists within the national security enterprise as a multidisciplinary field that is now commonly referred to as Geospatial Intelligence (GEOINT).  U.S. GEOINT operations are principally managed by the National Geospatial-Intelligence Agency (NGA). GEOINT is one among several types of intelligence produced in support of national security, along with Human Intelligence (HUMINT), Signals Intelligence (SIGINT), Measurement and Signatures Intelligence (MASINT), and Open Source Intelligence (OSINT). Primary technical GEOINT skill areas include remote sensing, GIS, data management, and data visualization. The intelligence tradecraft is historically characterized as a process involving tasking, collection, processing, exploitation, and dissemination (TCPED), and supports decision-making for military, defense, and intelligence operations. The GEOINT enterprise utilizes every type of data collection platform, sensor, and imagery to develop intelligence reports. GEOINT products are used to support situational awareness, safety of navigation, arms control treaty monitoring, natural disaster response, and humanitarian relief operations. Geospatial analysts employed in government positions by NGA or serving in the U.S. armed forces are required to qualify in NGA’s GEOINT Professional Certification (GPC) program, and industry contractors have the option of qualifying under the United States Geospatial Intelligence Foundation (USGIF) Certified GEOINT Professional (CGP) program.

CV-36 - Geovisual Analytics

Geovisual analytics refers to the science of analytical reasoning with spatial information as facilitated by interactive visual interfaces. It is distinguished by its focus on novel approaches to analysis rather than novel approaches to visualization or computational methods alone. As a result, geovisual analytics is usually grounded in real-world problem solving contexts. Research in geovisual analytics may focus on the development of new computational approaches to identify or predict patterns, new visual interfaces to geographic data, or new insights into the cognitive and perceptual processes that users apply to solve complex analytical problems. Systems for geovisual analytics typically feature a high-degree of user-driven interactivity and multiple visual representation types for spatial data. Geovisual analytics tools have been developed for a variety of problem scenarios, such as crisis management and disease epidemiology. Looking ahead, the emergence of new spatial data sources and display formats is expected to spur an expanding set of research and application needs for the foreseeable future. 

CV-35 - Geovisualization

Geovisualization is primarily understood as the process of interactively visualizing geographic information in any of the steps in spatial analyses, even though it can also refer to the visual output (e.g., plots, maps, combinations of these), or the associated techniques. Rooted in cartography, geovisualization emerged as a research thrust with the leadership of Alan MacEachren (Pennsylvania State University) and colleagues when interactive maps and digitally-enabled exploratory data analysis led to a paradigm shift in 1980s and 1990s. A core argument for geovisualization is that visual thinking using maps is integral to the scientific process and hypothesis generation, and the role of maps grew beyond communicating the end results of an analysis or documentation process. As such, geovisualization interacts with a number of disciplines including cartography, visual analytics, information visualization, scientific visualization, statistics, computer science, art-and-design, and cognitive science; borrowing from and contributing to each. In this entry, we provide a definition and a brief history of geovisualization including its fundamental concepts, elaborate on its relationship to other disciplines, and briefly review the skills/tools that are relevant in working with geovisualization environments. We finish the entry with a list of learning objectives, instructional questions, and additional resources.

GS-14 - GIS and Critical Ethics

This entry discusses and defines ethical critiques and GIS. It complements other GIS&T Body of Knowledge entries on Professional and Practical Ethics and Codes of Ethics for GIS Professionals. Critical ethics is presented as the attempt to provide a better understanding of data politics. Knowledge is never abstract or non-material. Spatial data, as a form of knowledge, may mask, conceal, disallow or disavow, even as it speaks, permits and claims. A critical ethics of GIS investigates this situated power-knowledge. Two concepts from educational pedagogy are suggested: threshold and troublesome knowledge. As we use and continue to learn GIS, these concepts may enrich our experience by usefully leading us astray. This points finally to how ethical critique is practical, empirical and political, rather than abstract or theoretical.

DA-01 - GIS&T and Agriculture

Agriculture, whether in the Corn Belt of the United States, the massive rice producing areas of Southeast Asia, or the bean harvest of a smallholder producer in Central America, is the basis for feeding the world. Agriculture systems are highly complex and heterogeneous in both space and time. The need to contextualize this complexity and to make more informed decisions regarding agriculture has led to GIS&T approaches supporting the agricultural sciences in many different areas. Agriculture represents a rich resource of spatiotemporal data and different problem contexts; current and future GIScientists should look toward agricultural as a potentially rewarding area of investigation and, likewise, one where new approaches have the potential to help improve the food, environmental, and economic security of people around the world.

DA-08 - GIS&T and Archaeology

topo map and LiDAR image

Figure 1.  USGS topo map and bare earth (LiDAR) image of Tennessee’s Mound Bottom State Archaeological Area. Bare Earth DEM processed by Zada Law.

Archaeology provides a glimpse into the lives of past peoples and histories that may have otherwise been forgotten. Geographic Information Systems and Technology (GIS&T) has become an invaluable tool in this endeavor by advancing the identification, documentation, and study of archaeological resources. Large scale mapping techniques have increased the efficiency of site surveys even in challenging environments. GIS&T refers to such things as remote sensing, spatial analysis, and mapping tools. The use of GIS&T for archaeology is a truly interdisciplinary field as it borrows principles from geology, oceanography, botany, meteorology and more in order to further the science. This chapter discusses some of the primary GIS&T tools and techniques used in archaeology and the primary ways in which they are applied.

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