2019 QUARTER 03

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

DC-15 - Mission planning

Plan an aerial imagery mission in response to a given request for proposals and map of a study area, taking into consideration vertical and horizontal control, atmospheric conditions, time of year, and time of day

Mobile devices refer to a computing system intended to be used by hand, such as smartphones or tablet computers. Mobile devices more broadly refer to mobile sensors and other hardware that has been made for relatively easy transportability, including wearable fitness trackers. Mobile devices are particularly relevant to Geographic Information Systems and Technology (GIS&T) in that they house multiple locational sensors that were until recently very expensive and only accessible to highly trained professionals. Now, mobile devices serve an important role in computing platform infrastructure and are key tools for collecting information and disseminating information to, from, and among heterogeneous and spatially dispersed audiences and devices. Due to the miniaturization and the decrease in the cost of computing capabilities, there has been widespread social uptake of mobile devices, making them ubiquitous. Mobile devices are embedded in Geographic Information Science (GIScience) meaning GIScience is increasingly permeating lived experiences and influencing social norms through the use of mobile devices. In this entry, locational sensors are described, with computational considerations specifically for mobile computing. Mobile app development is described in terms of key considerations for native versus cross-platform development. Finally, mobile devices are contextualized within computational infrastructure, addressing backend and frontend considerations.

CV-40 - Mobile Maps and Responsive Design

Geographic information increasingly is produced and consumed on mobile devices. The rise of mobile mapping is challenging traditional design conventions in research, industry, and education, and cartographers and GIScientists now need to accommodate this mobile context. This entry introduces emerging design considerations for mobile maps. First, the technical enablements and constraints that make mobile devices unique are described, including Global Positioning System (GPS) receivers and other sensors, reduced screensize and resolution, reduced processing power and memory capacity, less reliable data connectivity, reduced bandwidth, and physical mobility through variable environmental conditions. Scholarly influences on mobile mapping also are reviewed, including location-based services, adaptive cartography, volunteered geographic information, and locational privacy. Next, two strategies for creating mobile maps are introduced—mobile apps installed onto mobile operating systems versus responsive web maps that work on mobile and nonmobile devices—and core concepts of responsive web design are reviewed, including fluid grids, media queries, breakpoints, and frameworks. Finally, emerging design recommendations for mobile maps are summarized, with representation design adaptations needed to account for reduced screensizes and bandwidth and interaction design adaptations needed to account for multi-touch interaction and post-WIMP interfaces.

DM-21 - Modeling three-dimensional (3-D) entities

Identify GIS application domains in which true 3-D models of natural phenomena are necessary
Illustrate the use of Virtual Reality Modeling Language (VRML) to model landscapes in 3-D
Explain how octatrees are the 3-D extension of quadtrees
Explain how voxels and stack-unit maps that show the topography of a series of geologic layers might be considered 3-D extensions of field and vector representations respectively
Explain how 3-D models can be extended to additional dimensions
Explain the use of multi-patching to represent 3-D objects
Explain the difficulties in creating true 3-D objects in a vector or raster format
Differentiate between 21/2-D representations and true 3-D models

DM-19 - Modeling uncertainty

Differentiate among modeling uncertainty for entire datasets, for features, and for individual data values
Describe SQL extensions for querying uncertainty information in databases
Describe extensions to relational DBMS to represent different types of uncertainty in attributes, including both vagueness/fuzziness and error-based uncertainty
Discuss the role of metadata in representing and communicating dataset-level uncertainty
Create a GIS database that models uncertain information
Identify whether it is important to represent uncertainty in a particular GIS application
Describe the architecture of data models (both field- and object-based) to represent feature-level and datum-level uncertainty
Evaluate the advantages and disadvantages of existing uncertainty models based on storage efficiency, query performance, ease of data entry, and ability to implement in existing software

AM-44 - Modelling Accessibility

Modelling accessibility involves combining ideas about destinations, distance, time, and impedances to measure the relative difficulty an individual or aggregate region faces when attempting to reach a facility, service, or resource. In its simplest form, modelling accessibility is about quantifying movement opportunity. Crucial to modelling accessibility is the calculation of the distance, time, or cost distance between two (or more) locations, which is an operation that geographic information systems (GIS) have been designed to accomplish. Measures and models of accessibility thus draw heavily on the algorithms embedded in a GIS and represent one of the key applied areas of GIS&T.

KE-15 - Models of benefits

Describe recent models of the benefits of GIS&T applications
Explain how profit considerations have shaped the evolution of GIS&T
Outline the elements of a business case that justifies an organization’s investment in an enterprise geospatial information infrastructure
Discuss the extent to which external costs and benefits enhance the economic case for GIS

AM-13 - Multi-criteria evaluation

Describe the implementation of an ordered weighting scheme in a multiple-criteria aggregation
Compare and contrast the terms multi-criteria evaluation, weighted linear combination, and site suitability analysis
Differentiate between contributing factors and constraints in a multi-criteria application
Explain the legacy of multi-criteria evaluation in relation to cartographic modeling
Determine which method to use to combine criteria (e.g., linear, multiplication)
Create initial weights using the analytical hierarchy process (AHP)
Calibrate a linear combination model by adjusting weights using a test data set

DC-16 - Nature of Multispectral Image Data

A multispectral image comprises a set of co-registered images, each of which captures the spatially varying brightness of a scene in a specific spectral band, or electromagnetic wavelength region. An image is structured as a raster, or grid, of pixels. Multispectral images are used as a visual backdrop for other GIS layers, to provide information that is manually interpreted from images, or to generate automatically-derived thematic layers, for example through classification. The scale of multispectral images has spatial, spectral, radiometric and temporal components. Each component of scale has two aspects, extent (or coverage), and grain (or resolution). The brightness variations of an image are determined by factors that include (1) illumination variations and effects of the atmosphere, (2) spectral properties of materials in the scene (particularly reflectance, but also, depending on the wavelength, emittance), (3) spectral bands of the sensor, and (4) display options, such as the contrast stretch, which affect the visualization of the image. This topic review focuses primarily on optical remote sensing in the visible, near infrared and shortwave infrared parts of the electromagnetic spectrum, with an emphasis on satellite imagery.

AM-05 - Neighborhoods

Neighborhoods mean different things in varied contexts like computational geometry, administration and planning, as well as urban geography and other fields. Among the multiple contexts, computational geometry takes the most abstract and data-oriented approach: polygon neighborhoods refer to polygons sharing a boundary or a point, and point neighborhoods are defined by connected Thiessen polygons or other more complicated algorithms. Neighborhoods in some regions can be a practical and clearly delineated administration or planning units. In urban geography and some related social sciences, the terms neighborhood and community have been used interchangeably on many occasions, and neighborhoods can be a fuzzy and general concept with no clear boundaries such that they cannot be easily or consensually defined. Neighborhood effects have a series of unique meanings and several delineation methods are commonly used to define social and environmental effects in health applications.