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FC-17 - Proximity and Distance Decay

Distance decay is an essential concept in geography. At its core, distance decay describes how the relationship between two entities generally gets weaker as the separation between them increases. Inspired by long-standing ideas in physics, the concept of distance decay is used by geographers to analyze two kinds of relationships. First, the term expresses how measured interactions (such as trade volume or migration flow) generally decrease as the separation between entities increases, as is analyzed by spatial interaction models. Second, the term is used to describe how the implicit similarity between observations changes with separation, as measured by variograms. For either type of relationship, we discuss how "separation" must be clearly articulated according to the mechanism of the relationship under study. In doing this, we suggest that separation need not refer to positions in space or time, but can involve social or behavioral perceptions of separation, too. To close, we present how the "death of distance" is transforming distance decay in uneven ways.

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.

CP-29 - Enterprise GIS

Enterprise GIS is the implementation of GIS infrastructure, processes and tools at scale within the context of an organization, shaped by the prevailing information technology patterns of the day. It can be framed as an infrastructure enabling a set of capabilities, and a process for establishing and maintaining that infrastructure. Enterprise GIS facilitates the storage, sharing and dissemination of geospatial information products (data, maps, apps) within an organization and beyond. Enterprise GIS is integrated into, and shaped by the business processes, culture and context of an organization. Enterprise GIS implementations require general-purpose IT knowledge in the areas of performance tuning, information security, maintenance, interoperability, and data governance. The specific enabling technologies of Enterprise GIS will change with time, but currently the prevailing pattern is a multi-tiered services-oriented architecture supporting delivery of GIS capabilities on the web, democratizing access to and use of geospatial information products.

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.

DM-66 - Spatial Indexing

A spatial index is a data structure that allows for accessing a spatial object efficiently. It is a common technique used by spatial databases.  Without indexing, any search for a feature would require a "sequential scan" of every record in the database, resulting in much longer processing time. In a spatial index construction process, the minimum bounding rectangle serves as an object approximation. Various types of spatial indices across commercial and open-source databases yield measurable performance differences. Spatial indexing techniques are playing a central role in time-critical applications and the manipulation of spatial big data.

DM-62 - Database Administration

Organizations with a responsibility for maintaining large-scale, multi-user spatial databases often turn to server-based relational database management systems to achieve their goals.  The administration of such databases has many dimensions.  Industry standards in the areas of data storage and services should be researched and applied to ensure a sound, comprehensive database design as well as to promote interoperability with external entities.  Data validation tools should be implemented to improve the accuracy and efficiency of data maintenance activities.  Metadata should be maintained according to industry standards to protect the organization’s investment in data and to increase the likelihood of the data being located by clearinghouse and portal search tools.  Database security strategies can prevent unauthorized access to data and lessen the chances of data loss due to accidental data corruption.  Database performance should be monitored and strategies implemented to ensure that data can be retrieved from the system with acceptable response times.  Finally, trends in the field such as the increasing need to manage large volumes of data call for spatial database managers to be knowledgeable of non-relational data models as well, such as NoSQL data models.

DM-16 - Linear Referencing

Linear referencing is a term that encompasses a family of concepts and techniques for associating features with a spatial location along a network, rather than referencing those locations to a traditional spherical or planar coordinate system. Linear referencing is used when the location on the network, and the relationships to other locations on the network, are more significant than the location in 2D or 3D space. Linear referencing is commonly used in transportation applications, including roads, railways, and pipelines, although any network structure can be used as the basis for linearly referenced features. Several data models for storing linearly referenced data are available, and well-defined sets of procedures can be used to implement linear referencing for a particular application. As network analysis and network based statistical analysis become more prevalent across disciplines, linear referencing is likely to remain an important component of the data used for such analyses.

AM-80 - Capturing Spatiotemporal Dynamics in Computational Modeling

We live in a dynamic world that includes various types of changes at different locations over time in natural environments as well as in human societies. Modern sensing technology, location-aware technology and mobile technology have made it feasible to collect spatiotemporal tracking data at a high spatial and temporal granularity and at affordable costs. Coupled with powerful information and communication technologies, we now have much better data and computing platforms to pursue computational modeling of spatiotemporal dynamics. Researchers have attempted to better understand various kinds of spatiotemporal dynamics in order to predict, or even control, future changes of certain phenomena. A simple approach to representing spatiotemporal dynamics is by adding time (t) to the spatial dimensions (x,y,z) of each feature. However, spatiotemporal dynamics in the real world are more complex than a simple representation of (x,y,z,t) that describes the location of a feature at a given time. This article presents selected concepts, computational modeling approaches, and sample applications that provide a foundation to computational modeling of spatiotemporal dynamics. We also indicate why the research of spatiotemporal dynamics is important to geographic information systems (GIS) and geographic information science (GIScience), especially from a temporal GIS perspective.

FC-22 - Geometric Primitives and Algorithms

Geometric primitives are the representations used and computations performed in a GIS that concern the spatial aspects of the data, data objects described by coordinates. In vector geometry, we distinguish in zero-, one-, two-, and three-dimensional objects, better known as points, linear features, areal or planar features, and volumetric features. A GIS stores and performs computations on all of these. Often, planar features form a collective known as a (spatial) subdivision. Computations on geometric objects show up in data simplification, neighborhood analysis, spatial clustering, spatial interpolation, automated text placement, segmentation of trajectories, map matching, and many other tasks. They should be contrasted with computations on attributes or networks.

There are various kinds of vector data models for subdivisions. The classical ones are known as spaghetti and pizza models, but nowadays it is recognized that topological data models are the representation of choice. We overview these models briefly.

Computations range from simple to highly complex: deciding whether a point lies in a rectangle needs four comparisons, whereas performing map overlay on two subdivisions requires advanced knowledge of algorithm design. We introduce map overlay, Voronoi diagrams, and Delaunay triangulations and mention algorithmic approaches to compute them.

CV-23 - Map analysis
  • Create a profile of a cross section through a terrain using a topographic map and a digital elevation model (DEM)
  • Measure point-feature movement and point-feature diffusion on maps
  • Describe maps that can be used to find direction, distance, or position, plan routes, calculate area or volume, or describe shape
  • Explain how maps can be used in determining an optimal route or facility selection
  • Explain how maps can be used in terrain analysis (e.g., elevation determination, surface profiles, slope, viewsheds, and gradient)
  • Explain how the types of distortion indicated by projection metadata on a map will affect map measurements
  • Explain the differences between true north, magnetic north, and grid north directional references
  • Compare and contrast the manual measurement of the areas of polygons on a map printed from a GIS with those calculated by the computer and discuss the implications these variations in measurement might have on map use
  • Determine feature counts of point, line, and area features on maps
  • Analyze spatial patterns of selected point, line, and area feature arrangements on maps
  • Calculate slope using a topographic map and a DEM
  • Calculate the planimetric and actual road distances between two locations on a topographic map
  • Plan an orienteering tour of a specific length that traverses slopes of an appropriate steepness and crosses streams in places that can be forded based on a topographic map
  • Describe the differences between azimuths, bearings, and other systems for indicating directions

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