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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.

CV-04 - Scale and Generalization

Scale and generalization are two fundamental, related concepts in geospatial data. Scale has multiple meanings depending on context, both within geographic information science and in other disciplines. Typically it refers to relative proportions between objects in the real world and their representations. Generalization is the act of modifying detail, usually reducing it, in geospatial data. It is often driven by a need to represent data at coarsened resolution, being typically a consequence of reducing representation scale. Multiple computations and graphical modication processes can be used to achieve generalization, each introducing increased abstraction to the data, its symbolization, or both.

AM-09 - Classification and Clustering

Classification and clustering are often confused with each other, or used interchangeably. Clustering and classification are distinguished by whether the number and type of classes are known beforehand (classification), or if they are learned from the data (clustering). The overarching goal of classification and clustering is to place observations into groups that share similar characteristics while maximizing the separation of the groups that are dissimilar to each other. Clusters are found in environmental and social applications, and classification is a common way of organizing information. Both are used in many areas of GIS including spatial cluster detection, remote sensing classification, cartography, and spatial analysis. Cartographic classification methods present a simplified way to examine some classification and clustering methods, and these will be explored in more depth with example applications.

DA-05 - GIS&T and Local Government

GIS is an important tool for local governments. It is utilized to provide spatial information, metrics, and visualizations to constituents, businesses, and decision-makers. Internally, a well-managed GIS can be the basis for innovation and process improvement and can be a single source for employees to find a plethora of integrated data. This entry discusses how GIS supports local government, important considerations for maintaining a successful local government GIS, and current trends. This entry is based on the author’s experience in a GIS program at a medium-sized city in the Rocky Mountain Region of the United States. Not everything discussed may apply to other areas of the country or world. Additionally, smaller-sized programs may not have the resources to implement everything discussed. The key purpose of this entry is to provide students and instructors with tangible examples of processes, skills, and organizational structures that make for an effective local government GIS.

PD-12 - Commercialization of GIS Applications

The commercialization of GIS applications refers to the process of bringing a software solution to market. The process involves three broad categories of tasks: identifying a problem or aspect of a problem that a GIS application can solve or address; designing and creating a GIS application to address the problem; and developing and executing a marketing plan to reach those with the problem, the potential users. Ideally these categories would be addressed in this order, but in practice, aspects of each are likely to be addressed and iterated throughout the commercialization process.

Bringing a GIS application to market requires expertise in 1) the target industry or market (e.g., forestry); 2) software development (how to design and build a product); 3) law (licenses, contracts, taxes); and 4) business (how to fund development, guide the process, evaluate success, marketing). A single individual or organization, referred to as the provider in this discussion, may lead or execute all three categories of tasks, or engage third parties when specific expertise is required.

FC-27 - Thematic Accuracy Assessment

Geographic Information System (GIS) applications often involve various analytical techniques and geographic data to produce thematic maps for gaining a better understanding of geospatial situations to support spatial decisions. Accuracy assessment of a thematic map is necessary for evaluating the quality of the research results and ensuring appropriate use of the geographic data. Thematic accuracy deals with evaluating the accuracy of the attributes or labels of mapped features by comparing them to a reference that is assumed to be true. The fundamental practice presents the remote sensing approach to thematic accuracy assessment as a good guidance. For instance, the accuracy of a remote sensing image can be represented as an error matrix when the map and reference classification are conducted based on categories. This entry introduces basic concepts and techniques used in conducting thematic accuracy with an emphasis on land cover classification based on remote sensing images. The entry first introduces concepts of spatial uncertainty and spatial data quality standards and further gives an example of how spatial data quality affects thematic accuracy. Additionally, the entry illustrates the techniques that can be used to access thematic accuracy as well as using spatial autocorrelation in thematic accuracy sampling design.

GS-29 - GIS Participatory Modeling

Participatory research is increasingly used to better understand complex social-environmental problems and design solutions through diverse and inclusive stakeholder engagement. A growing number of approaches are helping to foster co-production of knowledge among diverse stakeholders. However, most methods don’t allow stakeholders to directly interact with the models that often drive environmental decision-making. Geospatial participatory modeling (GPM) is an approach that engages stakeholders in co-development and interpretation of models through dynamic geovisualization and simulations. GPM can be used to represent dynamic landscape processes and spatially explicit management scenarios, such as land use change or climate adaptation, enhancing opportunities for co-learning. GPM can provide multiple benefits over non-spatial approaches for participatory research processes, by (a) personalizing connections to problems and their solutions, (b) resolving abstract notions of connectivity, and (c) clarifying the scales of drivers, data, and decision-making authority. An adaptive, iterative process of model development, sharing, and revision can drive innovation of methods, improve model realism or applicability, and build capacity for stakeholders to leverage new knowledge gained from the process. This co-production of knowledge enables participants to more fully understand problems, evaluate the acceptability of trade-offs, and build buy-in for management actions in the places where they live and work.

FC-21 - Resolution

Resolution in the spatial domain refers to the size of the smallest measurement unit observed or recorded for an object, such as pixels in a remote sensing image or line segments used to record a curve. Resolution, also called the measurement scale, is considered one of the four major dimensions of scale, along with the operational scale, observational scale, and cartographic scale. Like the broader concept of scale, resolution is a fundamental consideration in GIScience because it affects the reliability of a study and contributes to the uncertainties of the findings and conclusions. While resolution effects may never be eliminated, techniques such as fractals could be used to reveal the multi-resolution property of a phenomenon and help guide the selection of resolution level for a study.

DA-36 - GIS&T and Public Policy

Public policy is the formal and informal guiding principles that are used by governments and other decision-making entities to guide our everyday lives. Geographic Information Science and Technology (GIS&T) has had an impact on the public policy process since GIS&T’s earliest beginnings in the 1960s. Advances in the development and availability of both geospatial technology and geospatial data paralleled a growing use of data-driven rational planning and decision-making models in policy making at all levels of government. Today more than ever, successful public policy depends on high-quality data and the technology that communicates its meaning effectively. Beyond the rational application of scientific or systematic methods, public policy is about values and how values affect, and are affected by, policies. This requires delivery of credible information in a transparent, understandable form not only to decision makers responsible for adopting policy, but also to various categories of stakeholders whose behavior will be impacted in some way by the policy’s implementation. GIS&T continues to play an important role in that endeavor, including making value conflicts more seeable and knowable. Included in the entry is a summary of the public policy process and its participants, followed by a brief overview of how GIST’s role in public policy has evolved over the last 50 years. The entry concludes by outlining a sample of real-world applications and presenting a discussion of related issues and future considerations.

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. 

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