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DC-29 - Volunteered Geographic Information

Volunteered geographic information (VGI) refers to geo-referenced data created by citizen volunteers. VGI has proliferated in recent years due to the advancement of technologies that enable the public to contribute geographic data. VGI is not only an innovative mechanism for geographic data production and sharing, but also may greatly influence GIScience and geography and its relationship to society. Despite the advantages of VGI, VGI data quality is under constant scrutiny as quality assessment is the basis for users to evaluate its fitness for using it in applications. Several general approaches have been proposed to assure VGI data quality but only a few methods have been developed to tackle VGI biases. Analytical methods that can accommodate the imperfect representativeness and biases in VGI are much needed for inferential use where the underlying phenomena of interest are inferred from a sample of VGI observations. VGI use for inference and modeling adds much value to VGI. Therefore, addressing the issue of representativeness and VGI biases is important to fulfill VGI’s potential. Privacy and security are also important issues. Although VGI has been used in many domains, more research is desirable to address the fundamental intellectual and scholarly needs that persist in the field.

CP-32 - On the Origins of Computing and GIST: Part 2, A Perspective on the Role of Peripheral Devices

GIS implementations in the late-1960s to mid-1980s required the use of exotic peripheral devices to encode and display geospatial information. Data encoding was normally performed in one of two modes: automated raster scanning and manual (vector) coordinate recording. Raster scanning systems in this era were extremely expensive, operated in batch mode, and were located at a limited number of centralized facilities, such as federal mapping agencies. Coordinate digitizers were more widely distributed and were often configured with dedicated minicomputers to handle editing and formatting tasks. Data display devices produced hardcopy and softcopy output. Two commonly encountered hardcopy devices were line printers and pen plotters. Softcopy display consisted of cathode ray tube devices that operated using frame buffer and storage tube technologies. Each device was driven by specialized software provided by device manufacturers, leading to widespread hardware-software incompatibly. This problem led to the emergence of device independence to promote increased levels of interoperability among disparate input and output devices.

CP-23 - Google Earth Engine

Google Earth Engine (GEE) is a cloud-based platform for planetary scale geospatial data analysis and communication.  By placing more than 17 petabytes of earth science data and the tools needed to access, filter, perform, and export analyses in the same easy to use application, users are able to explore and scale up analyses in both space and time without any of the hassles traditionally encountered with big data analysis.  Constant development and refinement have propelled GEE into one of the most advanced and accessible cloud-based geospatial analysis platforms available, and the near real time data ingestion and interface flexibility means users can go from observation to presentation in a single window.

DC-25 - Changes in Geospatial Data Capture Over Time: Part 1, Technological Developments

Geographic Information Systems (GIS) are fueled by geospatial data.  This comprehensive article reviews the evolution of procedures and technologies used to create the data that fostered the explosion of GIS applications. It discusses the need to geographically reference different types of information to establish an integrated computing environment that can address a wide range of questions. This includes the conversion of existing maps and aerial photos into georeferenced digital data.  It covers the advancements in manual digitizing procedures and direct digital data capture. This includes the evolution of software tools used to build accurate data bases. It also discusses the role of satellite based multispectral scanners for Earth observation and how LiDAR has changed the way that we measure and represent the terrain and structures. Other sections deal with building GIS data directly from street addresses and the construction of parcels to support land record systems. It highlights the way Global Positioning Systems (GPS) technology coupled with wireless networks and cloud-based applications have spatially empowered millions of users. This combination of technology has dramatically affected the way individuals search and navigate in their daily lives while enabling citizen scientists to be active participants in the capture of spatial data. For further information on changes to data capture, see Part 2: Implications and Case Studies. 

CP-10 - Social Media Analytics

Social media streams have emerged as new sources to support various geospatial applications. However, traditional geospatial tools and systems lack the capacities to process such data streams, which are generated dynamically in extremely large volumes and with versatile contents. Therefore, innovative approaches and frameworks should be developed to detect an emerging event discussed over the social media, understand the extent, consequences of the event, as well as it time-evolving nature, and eventually discover useful patterns. In order to harness social media for geospatial applications, this entry introduces social media analytics technologies for harvesting, managing, mining, analyzing and visualizing the spatial, temporal, text, and network information of social media data.

DC-10 - Aerial Photography: History and Georeferencing

In 1903, Julius Neubranner, a photography enthusiast, designed and patented a breast-mounted aerial camera for carrier pigeons. Weighing only 70 grams, the camera took automatic exposures at 30-second intervals along the flight line flown by the bird. Although faster than balloons, they were not always reliable in following their flight paths. Today the pigeon corps has been replaced by unmanned aerial vehicles, but aerial photography continues to be an important source of data for use in a wide range of geospatial applications. Processing of the imagery to remove various types of distortion is a necessary step before the images can be georeferenced and used for mapping purposes. 

CP-16 - On the Origins of Computing and GIS&T: Part I, A Computer Systems Perspective

This paper describes the evolutionary path of hardware systems and the hardware-software interfaces that were used for GIS&T development during its “childhood”, the era from approximately the late 1960s to the mid-1980s.  The article is structured using a conceptualization that developments occurred during this period in three overlapping epochs that have distinctive modes of interactivity and user control: mainframes, minicomputers and workstations.  The earliest GIS&T applications were developed using expensive mainframe computer systems, usually manufactured by IBM. These mainframes typically had memory measured in kilobytes and operated in batch mode with jobs submitted using punched cards as input.  Many such systems used an obscure job control language with a rigid syntax. FORTRAN was the predominant language used for GIS&T software development. Technological developments, and associated cost reductions, led to the diffusion of minicomputers and a shift away from IBM. Further developments led to the widespread adoption of single user workstations that initially used commodity processors and later switched to reduced instruction set chips. Many minicomputers and workstations ran some variant of the UNIX operating system, which substantially improved user interactivity.

CP-27 - GIS and Computational Notebooks

Researchers and practitioners across many disciplines have recently adopted computational notebooks to develop, document, and share their scientific workflows—and the GIS community is no exception. This chapter introduces computational notebooks in the geographical context. It begins by explaining the computational paradigm and philosophy that underlie notebooks. Next it unpacks their architecture to illustrate a notebook user’s typical workflow. Then it discusses the main benefits notebooks offer GIS researchers and practitioners, including better integration with modern software, more natural access to new forms of data, and better alignment with the principles and benefits of open science. In this context, it identifies notebooks as the “glue” that binds together a broader ecosystem of open source packages and transferable platforms for computational geography. The chapter concludes with a brief illustration of using notebooks for a set of basic GIS operations. Compared to traditional desktop GIS, notebooks can make spatial analysis more nimble, extensible, and reproducible and have thus evolved into an important component of the geospatial science toolkit.

CP-26 - eScience, the Evolution of Science

Science—and research more broadly—face many challenges as its practitioners struggle to accommodate new challenges around reproducibility and openness.  The current practice of science limits access to knowledge, information and infrastructure, which in turn leads to inefficiencies, frustrations and a lack of rigor.  Many useful research outcomes are never used because they are too difficult to find, or to access, or to understand.

New computational methods and infrastructure provide opportunities to reconceptualize how science is conducted, how it is shared, how it is evaluated and how it is reused.  And new data sources changed what can be known, and how well, and how frequently.  This article describes some of the major themes of eScience/eResearch aimed at improving the process of doing science.

CP-08 - Spatial Cloud Computing

The scientific and engineering advancements in the 21st century pose grand computing challenges in managing big data, using complex algorithms to extract information and knowledge from big data, and simulating complex and dynamic physical and social phenomena. Cloud computing emerged as new computing model with the potential to address these computing challenges. This entry first introduces the concept, features and service models of cloud computing. Next, the ideas of generalized architecture and service models of spatial cloud computing are then elaborated to identify the characteristics, components, development and applications of spatial cloud computing for geospatial sciences. 

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