All Topics

PD-37 - Open Source Software Development

Open source geospatial software is now ubiquitous – it is used and supported across industries, in government agencies, as well as research institutions and academia. This entry describes general principles of open source software development and provides an overview of the development platforms and tools. Specific focus is on the Open Source Geospatial Foundation’s software stack, its development principles, practices, and initiatives. Several additional major open source software systems with geospatial support are also briefly discussed with examples of open source applications developed by integrating multiple libraries and packages.

FC-35 - Openness

The philosophy of Openness and its use in diverse areas is attracting increasing attention from users, developers, businesses, governments, educators, and researchers around the world. The technological, socio-cultural, economic, legal, institutional, and philosophical issues related to its principles, applications, benefits, and barriers for its use are growing areas of research. The word “Open” is commonly used to denote adherence to the principles of Openness. Several fields are incorporating the use of Openness in their activities, some of them are of particular relevance to GIS&T (Geographic Information Science and Technology) such as: Open Data, Free and Open Source Software; and Open Standards for geospatial data, information, and technologies. This entry presents a definition of Openness, its importance in the area of GISc&T is introduced through a list of its benefits in the fields of Open Data, Open Source Software, and Open Standards. Then some of the barriers, myths, or inhibitors to Openness are presented using the case of Free and Open Source Software (FOSS) and FOSS for Geospatial Applications (FOSS4G).

KE-33 - Organizational Models for GIS Management

Organizational structures and management practices for GIS programs are numerous and complex. This topic begins with an explanation of organizational and management concepts and context that are particularly relevant to GIS program and project management, including strategic planning and stakeholders. Specific types of organizations that typically use GIS technology are described and organizational structure types are explained. For GIS Program management, organizational placement, organizational components, and management control and policies are covered in depth. Multi-organizational GIS Programs are also discussed. Additional topics include management roles and technology trends that affect organizational structure. It concludes with a general description of GIS Project management. 

AM-04 - Overlay

Overlay operation is a critical and powerful tool in GIS that superimposes spatial and attribute information from various thematic map layers to produce new information. Overlay operations facilitate spatial analysis and modeling processes when being used with other spatial operations (e.g. buffer, dissolve, merge) to solve real-world problems. For both vector and raster data models, the input layers need to be spatially aligned precisely with each other to ensure a correct overlay operation. In general, vector overlay is geometrically and computationally complex. Some most used vector overlay operations include intersection, union, erase, and clip. Raster overlay combines multiple raster layers cell by cell through Boolean, arithmetic, or comparison operators. This article provides an overview of the fundamentals of overlay operations, how they are implemented in vector and raster data, and how suitability analysis is conducted.

AM-38 - Pattern Recognition and Matching

People recognize and characterize patterns to understand the world. Spatial data exhibit distinctive characteristics that render most aspatial recognition and matching methods unsuitable or inefficient. In past decades, a plethora of methods have been developed for spatial pattern recognition and matching to account for these spatial characteristics. This entry first focuses on the methods of spatial pattern recognition, including an overview of the basic concepts and common  types. Methods for spatial pattern matching are then introduced. An example scenario of the distribution of tree species in the Arbuckle Mountains of south-central Oklahoma illustrates covered concepts. The entry concludes with brief remarks on continuing challenges and future directions in spatial pattern recognition and matching in the Big Data and artificial intelligence era.

FC-04 - Perception and Cognitive Processing of Geographic Phenomena: a Choropleth Map Case Study

The near ubiquity of maps has created a population the is well adept at reading and understanding maps.  But, while maps are familiar, understanding how the human brain processes that information is less known.  Discussing the processing of geographic phenomena could take different avenues: specific geospatial thinking skills, general perception and cognition processes, or even different parts of the human brain that are invoked when thinking geographically.  This entry focuses on tracing the processing of geographic phenomena using a choropleth map case study, beginning from perception — the moment the phenomena enter the human brain via our senses, to cognition — how meaning and understanding are generated. 

FC-03 - Philosophical Perspectives

This entry follows in the footsteps of Anselin’s famous 1989 NCGIA working paper entitled “What is special about spatial?” (a report that is very timely again in an age when non-spatial data scientists are ignorant of the special characteristics of spatial data), where he outlines three unrelated but fundamental characteristics of spatial data. In a similar vein, I am going to discuss some philosophical perspectives that are internally unrelated to each other and could warrant individual entries in this Body of Knowledge. The first one is the notions of space and time and how they have evolved in philosophical discourse over the past three millennia. Related to these are aspects of absolute versus relative conceptions of these two fundamental constructs. The second is a brief introduction to key philosophical approaches and how they impact geospatial science and technology use today. The third is a discussion of which of the promises of the Quantitative Revolution in Geography and neighboring disciplines have been fulfilled by GIScience (and what is still missing). The fourth and final one is an introduction to the role that GIScience may play in what has recently been formalized as theory-guided data science.

DM-36 - Physical Data Models

Constructs within a particular implementation of database management software guide the development of a physical data model, which is a product of a physical database design process. A physical data model documents how data are to be stored and accessed on storage media of computer hardware.  A physical data model is dependent on specific data types and indexing mechanisms used within database management system software.  Data types such as integers, reals, character strings, plus many others can lead to different storage structures. Indexing mechanisms such as region-trees and hash functions and others lead to differences in access performance.  Physical data modeling choices about data types and indexing mechanisms related to storage structures refine details of a physical database design. Data types associated with field, record and file storage structures together with the access mechanisms to those structures foster (constrain) performance of a database design. Since all software runs using an operating system, field, record, and file storage structures must be translated into operating system constructs to be implemented.  As such, all storage structures are contingent on the operating system and particular hardware that host data management software. 

AM-07 - Point Pattern Analysis

Point pattern analysis (PPA) focuses on the analysis, modeling, visualization, and interpretation of point data. With the increasing availability of big geo-data, such as mobile phone records and social media check-ins, more and more individual-level point data are generated daily. PPA provides an effective approach to analyzing the distribution of such data. This entry provides an overview of commonly used methods in PPA, as well as demonstrates the utility of these methods for scientific investigation based on a classic case study: the 1854 cholera outbreaks in London.

DM-85 - Point, Line, and Area Generalization

Generalization is an important and unavoidable part of making maps because geographic features cannot be represented on a map without undergoing transformation. Maps abstract and portray features using vector (i.e. points, lines and polygons) and raster (i.e pixels) spatial primitives which are usually labeled. These spatial primitives are subjected to further generalization when map scale is changed. Generalization is a contradictory process. On one hand, it alters the look and feel of a map to improve overall user experience especially regarding map reading and interpretive analysis. On the other hand, generalization has documented quality implications and can sacrifice feature detail, dimensions, positions or topological relationships. A variety of techniques are used in generalization and these include selection, simplification, displacement, exaggeration and classification. The techniques are automated through computer algorithms such as Douglas-Peucker and Visvalingam-Whyatt in order to enhance their operational efficiency and create consistent generalization results. As maps are now created easily and quickly, and used widely by both experts and non-experts owing to major advances in IT, it is increasingly important for virtually everyone to appreciate the circumstances, techniques and outcomes of generalizing maps. This is critical to promoting better map design and production as well as socially appropriate uses.