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KE-32 - Competence in GIS&T Knowledge Work

“Competence” is a word that rolls off the tongues of instructional designers, education administrators, and HR people. Others find it hard to swallow. For some GIS&T educators, competence connotes an emphasis on vocational instruction that’s unworthy of the academy. This entry challenges skeptical educators to rethink competence not just as readiness for an occupation, but first and foremost as the readiness to live life to the fullest, and to contribute to a sustainable future. The entry considers the OECD’s “Key Competencies for a Successful Life and Well-Functioning Society,” as well as the specialized GIS&T competencies specified in the U.S. Department of Labor’s Geospatial Technology Competency Model. It presents findings of a survey in which 226 self-selected members of Esri’s Young Professionals Network observe that competencies related to the GTCM’s Software and App Development Segment were under-developed in their university studies. Looking ahead, in the context of an uncertain future in which, some say, many workers are at risk of “technological unemployment,” the entry considers which GIS&T competencies are likely to be of lasting value.

AM-90 - Computational Movement Analysis

Figure 1. Group movement patterns as illustrated in this coordinated escape behavior of a group of mountain goat (Rubicapra rubicapra) evading approaching hikers on the Fuorcla Trupchun near the Italian/Swiss border are at the core of computational movement analysis. Once the trajectories of moving objects are collected and made accessible for computational processing, CMA aims at a better understanding of the characteristics of movement processes of animals, people or things in geographic space.

 

Computational Movement Analysis (CMA) develops and applies analytical computational tools aiming at a better understanding of movement data. CMA copes with the rapidly growing data streams capturing the mobility of people, animals, and things roaming geographic spaces. CMA studies how movement can be represented, modeled, and analyzed in GIS&T. The CMA toolbox includes a wide variety of approaches, ranging from database research, over computational geometry to data mining and visual analytics.

DM-34 - Conceptual Data Models

Within an initial phase of database design, a conceptual data model is created as a technology-independent specification of the data to be stored within a database. This specification often times takes the form of a formalized diagram.  The process of conceptual data modeling is meant to foster shared understanding among data modelers and stakeholders when creating the specification.  As such, a conceptual data model should be easily readable by people with little or no technical-computer-based expertise because a comprehensive view of information is more important than a detailed view. In a conceptual data model, entity classes are categories of things (person, place, thing, etc.) that have attributes for describing the characteristics of the things.  Relationships can exist between the entity classes.  Entity-relationship diagrams have been and are likely to continue to be a popular way of characterizing entity classes, attributes and relationships.  Various notations for diagrams have been used over the years. The main intent about a conceptual data model and its corresponding entity-relationship diagram is that they should highlight the content and meaning of data within stakeholder information contexts, while postponing the specification of logical structure to the second phase of database design called logical data modeling. 

GS-13 - Epistemological critiques

As GIS became a firmly established presence in geography and catalysed the emergence of GIScience, it became the target of a series of critiques regarding modes of knowledge production that were perceived as problematic. The first wave of critiques charged GIS with resuscitating logical positivism and its erroneous treatment of social phenomena as indistinguishable from natural/physical phenomena. The second wave of critiques objected to GIS on the basis that it was a representational technology. In the third wave of critiques, rather than objecting to GIS simply because it represented, scholars engaged with the ways in which GIS represents natural and social phenomena, pointing to the masculinist and heteronormative modes of knowledge production that are bound up in some, but not all, uses and applications of geographic information technologies. In response to these critiques, GIScience scholars and theorists positioned GIS as a critically realist technology by virtue of its commitment to the contingency of representation and its non-universal claims to knowledge production in geography. Contemporary engagements of GIS epistemologies emphasize the epistemological flexibility of geospatial technologies.

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.

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.

DA-04 - GIS&T and Civil Engineering

Civil Engineering, which includes sub-disciplines such as environmental, geotechnical, structural, and water resource engineering, is increasingly dependent on the GIS&T for the planning, design, operation and management of civil engineering infrastructure systems.  Typical tasks include the management of spatially referenced data sets, analytic modeling for making design decisions and estimating likely system behavior and impacts, and the visualization of systems for the decision-making process and garnering stakeholder support.

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