All Topics

A B C D E F G H I J K L M N O P R S T U V W
KE-03 - Strategic Planning for GIS Design

Geographic Information Systems (GIS) are pervasive and have become an essential feature in many professional disciplines. Prior to adoption, implementation or use of any GIS, a system must be properly designed to meet its organizational goals, and this requires comprehensive strategic planning to take place ahead of the design. In this article, we discuss methods for strategic planning in GIS design, drawing from literature in Information Systems and GIS research and practice, and business management. We present a four-step approach toward planning for GIS design that will ensure the system is well-suited to further an organization’s long-term functions, applications, and users’ needs.

DC-11 - Street-level Imagery

Street-level imagery consists of collections of photographs taken from the perspective of moving pedestrians or vehicles. These collections are often stitched together digitally and georeferenced to create interactive and immersive landscapes that are virtually navigable by users. Such landscapes, sometimes called 360-degree panoramas, or bubbles, are uploaded onto web platforms, and linked with geographical databases, which allows users to search and explore the imagery in various ways. IT companies such as Google have created street-level imagery platforms that rely primarily on paid drivers, although they have begun to rely on contributor submissions to complement and expand their coverage. Recently services such as Mapillary and OpenStreetCam have advanced a model that relies primarily on volunteer contributors, leveraging community interest from projects such as OpenStreetMap. While street-level imagery has become a widespread tool with multiple commercial and non-commercial applications, it is also entangled various legal and public opinion controversies, due to its capabilities for private data collection and surveillance. 

FC-12 - Structured Query Language (SQL) and attribute queries

The structured query language (SQL) for database interrogation is presented and illustrated with a few examples using attribute tables one might find in a common GIS database.  A short background is presented on the history and goals that the creators of the SQL language hoped to achieve, followed by a review of SQL utility for data query, editing, and definition.  While the SQL language is rich in content and breadth, this article attempts to build on a simple SQL and then iteratively add additional complexity to highlight the power that SQL affords to the GIS professional who has limited programming capabilities.  The reader is asked to consider how minor modifications to SQL syntax can add complexity and even create more dynamic mathematical models with simple English-like command statements.  Finally, the reader is challenged to consider how terse SQL statements may be used to replace relatively long and laborious command sequences required by a GIS GUI approach.

CV-08 - Symbolization and the Visual Variables

Maps communicate information about the world by using symbols to represent specific ideas or concepts. The relationship between a map symbol and the information that symbol represents must be clear and easily interpreted. The symbol design process requires first an understanding of the underlying nature of the data to be mapped (e.g., its spatial dimensions and level of measurement), then the selection of symbols that suggest those data attributes. Cartographers developed the visual variable system, a graphic vocabulary, to express these relationships on maps. Map readers respond to the visual variable system in predictable ways, enabling mapmakers to design map symbols for most types of information with a high degree of reliability.

KE-21 - System Modelling for Effective GIS Management

A geographic information system in operation is highly complex, as the scope of the GIS&T Body of Knowledge demonstrates. Modern society relies on many complex systems, but most are self-contained mechanisms with limited and well defined interfaces. A GIS is a complex open system that extends across the realms of hardware, software, data, science, and human processes. A conceptual model of a GIS can be an effective tool to design, implement, operate, maintain, manage, and assessment tool.

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.

AM-42 - The Classic Transportation Problem

The classic transportation problem concerns minimizing the cost of transporting a single product from sources to destinations. It is a network-flow problem that arises in industrial logistics and is considered as a special case of linear programming. The total number of units produced at each source, the total number of units required at each destination and the cost to transport one unit from each source to each destination are the basic inputs. The objective is to minimize the total cost of transporting the 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 3) improving the current solution through iteration. Modeling and solving the classic transportation problem rely strongly on network models, least-cost path algorithms, and location-allocation analysis in the field of geographic information science (GIScience). Thus, it represents a key component in the network analytics and modeling area of GIS&T.

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.

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.

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.

Pages