2022 QUARTER 01

A B C D E F G H I J K L M N O P R S T U V W
GS-06 - Public participation GIS
  • Critique the assertion that public participation GIS promotes democracy
  • Explain how community organizations’ use of geospatial technologies can alter existing community power relations
  • Explain how geospatial technologies can assist community organizations at each rung of the ladder of public participation
  • Explain the challenge of representing within current GIS software local knowledge that is neither easily mapped nor verified
  • Discuss advantages and disadvantages of six models of GIS availability, including communitybased GIS, university-community partnerships, GIS facilities in universities and public libraries, “Map rooms,” Internet map servers, and neighborhood GIS centers.
  • Explain why some community organizations may encounter more difficulty than others in acquiring geospatial data from public and private organizations
GS-05 - Public participation in governing
  • Differentiate among universal/deliberative, pluralist/representative, and participatory models of citizen participation in governing
  • Defend or refute the argument that local knowledges are contested
  • Explain how community organizations represent the interests of citizens, politicians, and planners
  • Explain and respond to the assertion that “capturing local knowledge” can be exploitative
  • Describe an example of “local knowledge” that is unlikely to be represented in the geospatial data maintained routinely by government agencies
  • Explain how legislation such as the Community Reinvestment Act of 1977 provides leverage to community organizations
  • Describe the range of spatial scales at which community organizations operate
  • Compare the advantages and disadvantages of group participation and individual participation
  • Describe the six “rungs” of increasing participation in governmental decision-making that constitute a “ladder” of public participation
KE-28 - Publications
  • Describe the leading academic journals serving the GIS&T community
  • Select association and for-profit journals that are useful to entities managing enterprise GISs
  • Select and describe the leading trade journals serving the GIS&T community
  • Develop a bibliography of scholarly and professional articles and/or books that are relevant to a particular GIS&T project
PD-31 - PySAL and Spatial Statistics Libraries

As spatial statistics are essential to the geographical inquiry, accessible and flexible software offering relevant functionalities is highly desired. Python Spatial Analysis Library (PySAL) represents an endeavor towards this end. It is an open-source python library and ecosystem hosting a wide array of spatial statistical and visualization methods. Since its first public release in 2010, PySAL has been applied to address various research questions, used as teaching materials for pedagogical purposes in regular classes and conference workshops serving a wide audience, and integrated into general GIS software such as ArcGIS and QGIS. This entry first gives an overview of the history and new development with PySAL. This is followed by a discussion of PySAL’s new hierarchical structure, and two different modes of accessing PySAL’s functionalities to perform various spatial statistical tasks, including exploratory spatial data analysis, spatial regression, and geovisualization. Next, a discussion is provided on how to find and utilize useful materials for studying and using spatial statistical functions from PySAL and how to get involved with the PySAL community as a user and prospective developer. The entry ends with a brief discussion of future development with PySAL.

PD-11 - Python for GIS

Figure 1. PySAL within QGIS Processing Toolbox: Hot-spot analysis of Homicide Rates in Southern US Counties.

 

Python is a popular language for geospatial programming and application development. This entry provides an overview of the different development modes that can be adopted for GIS programming with Python and discusses the history of Python adoption in the GIS community. The different layers of the geospatial development stack in Python are examined giving the reader an understanding of the breadth that Python offers to the GIS developer. Future developments and broader issues related to interoperability and programming ecosystems are identified.

PD-15 - R for Geospatial Analysis and Mapping

R is a programming language as well as a computing environment to perform a wide variety of data analysis, statistics, and visualization. One of the reasons for the popularity of R is that it embraces open, transparent scholarship and reproducible research. It is possible to combine content and code in one document, so data, analysis, and graphs are tied together into one narrative, which can be shared with others to recreate analyses and reevaluate interpretations. Different from tools like ArcGIS or QGIS that are specifically built for spatial data, GIS functionality is just one of many things R offers. And while users of dedicated GIS tools typically interact with the software via a point-and-click graphical interface, R requires command-line scripting. Many R users today rely on RStudio, an integrated development environment (IDE) that facilitates the writing of R code and comes with a series of convenient features, like integrated help, data viewer, code completion, and syntax coloring. By using R Markdown, a particular flavor of the Markdown language, RStudio also makes it particularly easy to create documents that embed and execute R code snippets within a text and to render both, static documents (like PDF), as well as interactive html pages, a feature particularly useful for exploratory GIS work and mapping.

CV-20 - Raster Formats and Sources

Raster data is commonly used by cartographers in concert with vector data. Choice of raster file format is important when using raster data or producing raster output from vector data. Raster formats are designed for specific purposes and have limitations in color representation and data loss. The simplest raster formats are just a single two-dimensional array of pixels, where multi-band raster datasets use additional data values to represent color or other data. The article covers considerations for the intended use of raster formats. Formats and resolutions appropriate for the web may not be appropriate for print or higher resolution devices. Several types of raster sources are available including single band measures, imagery, and existing raster maps or basemaps. The future of raster will evolve as more formats, sources, and computational improvements are made.

DM-87 - Raster resampling
  • Evaluate methods used by contemporary GIS software to resample raster data on-the-fly during display
  • Select appropriate interpolation techniques to resample particular types of values in raster data (e.g., nominal using nearest neighbor)
  • Resample multiple raster data sets to a single resolution to enable overlay
  • Resample raster data sets (e.g., terrain, satellite imagery) to a resolution appropriate for a map of a particular scale
  • Discuss the consequences of increasing and decreasing resolution
PD-20 - Real-time GIS Programming and Geocomputation

Streaming data generated continuously from sensor networks, mobile devices, social media platforms and other edge devices have posed significant challenges to existing computing platforms for achieving both high throughput and low latency data processing in addition to scalable computing. This entry introduces a real-time computing and programming platform for time-critical GIS (Geographic Information System) applications. In this platform, advanced streaming data processing software, such as Apache Kafka and Spark Streaming, are integrated to enable data analytics in real-time. This computing platform can also be extended to integrate GeoAI (Geospatial Artificial Intelligence) based machine learning models to leverage both historical and streaming data to achieve real-time prediction and intelligent geospatial analytics. Two real-time geospatial applications in terms of flood simulation and climate data visualization are introduced to demonstrate how real-time programming and computing can help tackle real-world problems with important societal impacts.

DM-03 - Relational DBMS
  • Explain the advantage of the relational model over earlier database structures including spreadsheets
  • Define the basic terms used in relational database management systems (e.g., tuple, relation, foreign key, SQL, relational join)
  • Discuss the efficiency and costs of normalization
  • Describe the entity-relationship diagram approach to data modeling
  • Explain how entity-relationship diagrams are translated into relational tables
  • Create an SQL query that extracts data from related tables
  • Describe the problems associated with failure to follow the first and second normal forms (including data confusion, redundancy, and retrieval difficulties)
  • Demonstrate how search and relational join operations provide results for a typical GIS query and other simple operations using the relational DBMS within a GIS software application

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