2022 QUARTER 04

A B C D E F G H I J K L M N O P R S T U V W
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.

CP-27 - GIS and Computational Notebooks

Researchers and practitioners across many disciplines have recently adopted computational notebooks to develop, document, and share their scientific workflows—and the GIS community is no exception. This chapter introduces computational notebooks in the geographical context. It begins by explaining the computational paradigm and philosophy that underlie notebooks. Next it unpacks their architecture to illustrate a notebook user’s typical workflow. Then it discusses the main benefits notebooks offer GIS researchers and practitioners, including better integration with modern software, more natural access to new forms of data, and better alignment with the principles and benefits of open science. In this context, it identifies notebooks as the “glue” that binds together a broader ecosystem of open source packages and transferable platforms for computational geography. The chapter concludes with a brief illustration of using notebooks for a set of basic GIS operations. Compared to traditional desktop GIS, notebooks can make spatial analysis more nimble, extensible, and reproducible and have thus evolved into an important component of the geospatial science toolkit.

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.

PD-14 - GIS and Parallel Programming

Programming is a sought after skill in GIS, but traditional programming (also called serial programming) only uses one processing core. Modern desktop computers, laptops, and even cellphones now have multiple processing cores, which can be used simultaneously to increase processing capabilities for a range of GIS applications. Parallel programming is a type of programming that involves using multiple processing cores simultaneously to solve a problem, which enables GIS applications to leverage more of the processing power on modern computing architectures ranging from desktop computers to supercomputers. Advanced parallel programming can leverage hundreds and thousands of cores on high-performance computing resources to process big spatial datasets or run complex spatial models.

Parallel programming is both a science and an art. While there are methods and principles that apply to parallel programming--when, how, and why certain methods are applied over others in a specific GIS application remains more of an art than a science. The following sections introduce the concept of parallel programming and discuss how to parallelize a spatial problem and measure parallel performance.

PD-19 - GIS APIs

GIS APIs are collections of library modules that resemble various functionalities of GIS software through programming. GIS APIs evolved from desktop GIS. GIS APIs, as a distributed solution, are interoperable, scalable, light-weight, user-friendly, and versatile to a wide range of GIS users. This entry provides an overview of common GIS APIs, their functionalities as well as other related APIs. The general procedure to develop customized GIS applications is briefly discussed and demonstrated in a case study.

FC-10 - GIS Data Properties

Data properties are characteristics of GIS attribute systems and values whose design and format impacts analytical and computational processing.  Geospatial data are expressed at conceptual, logical, and physical levels of database abstraction intended to represent geographical information. The appropriate design of attribute systems and selection of properties should be logically consistent and support appropriate scales of measurement for representation and analysis. Geospatial concepts such as object-field views and dimensional space for relating objects and qualities form data models based on a geographic matrix and feature geometry. Three GIS approaches and their attribute system design are described: tessellations, vectors, and graphs.

GS-29 - GIS Participatory Modeling

Participatory research is increasingly used to better understand complex social-environmental problems and design solutions through diverse and inclusive stakeholder engagement. A growing number of approaches are helping to foster co-production of knowledge among diverse stakeholders. However, most methods don’t allow stakeholders to directly interact with the models that often drive environmental decision-making. Geospatial participatory modeling (GPM) is an approach that engages stakeholders in co-development and interpretation of models through dynamic geovisualization and simulations. GPM can be used to represent dynamic landscape processes and spatially explicit management scenarios, such as land use change or climate adaptation, enhancing opportunities for co-learning. GPM can provide multiple benefits over non-spatial approaches for participatory research processes, by (a) personalizing connections to problems and their solutions, (b) resolving abstract notions of connectivity, and (c) clarifying the scales of drivers, data, and decision-making authority. An adaptive, iterative process of model development, sharing, and revision can drive innovation of methods, improve model realism or applicability, and build capacity for stakeholders to leverage new knowledge gained from the process. This co-production of knowledge enables participants to more fully understand problems, evaluate the acceptability of trade-offs, and build buy-in for management actions in the places where they live and work.

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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