Spatial analysis in the context of "Field (geography)"

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⭐ Core Definition: Spatial analysis

Spatial analysis is any of the formal techniques which study entities using their topological, geometric, or geographic properties, primarily used in urban design. Spatial analysis includes a variety of techniques using different analytic approaches, especially spatial statistics. It may be applied in fields as diverse as astronomy, with its studies of the placement of galaxies in the cosmos, or to chip fabrication engineering, with its use of "place and route" algorithms to build complex wiring structures. In a more restricted sense, spatial analysis is geospatial analysis, the technique applied to structures at the human scale, most notably in the analysis of geographic data. It may also applied to genomics, as in transcriptomics data, but is primarily for spatial data.

Complex issues arise in spatial analysis, many of which are neither clearly defined nor completely resolved, but form the basis for current research. The most fundamental of these is the problem of defining the spatial location of the entities being studied. Classification of the techniques of spatial analysis is difficult because of the large number of different fields of research involved, the different fundamental approaches which can be chosen, and the many forms the data can take.

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Spatial analysis in the context of Environmental geography

Integrated geography (also referred to as integrative geography, environmental geography or human–environment geography) is where the branches of human geography and physical geography overlap to describe and explain the spatial aspects of interactions between human individuals or societies and their natural environment, these interactions being called coupled human–environment system.

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Spatial analysis in the context of Transport network

A transport network, or transportation network, is a network or graph in geographic space, describing an infrastructure that permits and constrains movement or flow.Examples include but are not limited to road networks, railways, air routes, pipelines, aqueducts, and power lines. The digital representation of these networks, and the methods for their analysis, is a core part of spatial analysis, geographic information systems, public utilities, and transport engineering. Network analysis is an application of the theories and algorithms of graph theory and is a form of proximity analysis.

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Spatial analysis in the context of Geographic information science

Geographic information science (GIScience, GISc) or geoinformation science is a scientific discipline at the crossroads of computational science, social science, and natural science that studies geographic information, including how it represents phenomena in the real world, how it represents the way humans understand the world, and how it can be captured, organized, and analyzed. It is a sub-field of geography, specifically part of technical geography. It has applications to both physical geography and human geography, although its techniques can be applied to many other fields of study as well as many different industries.

As a field of study or profession, it can be contrasted with geographic information systems (GIS), which are the actual repositories of geospatial data, the software tools for carrying out relevant tasks, and the profession of GIS users. That said, one of the major goals of GIScience is to find practical ways to improve GIS data, software, and professional practice; it is more focused on how GIS is applied in real life as opposed to being a geographic information system tool in and of itself. The field is also sometimes called geographical information science.

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Spatial analysis in the context of Geographical feature

In geography and particularly in geographic information science, a geographic feature or simply feature (also called an object or entity) is a representation of phenomenon that exists at a location in the space and scale of relevance to geography; that is, at or near the surface of Earth. It is an item of geographic information, and may be represented in maps, geographic information systems, remote sensing imagery, statistics, and other forms of geographic discourse. Such representations of phenomena consist of descriptions of their inherent nature, their spatial form and location, and their characteristics or properties.

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Spatial analysis in the context of Geographic information system

A geographic information system (GIS) consists of integrated computer hardware and software that store, manage, analyze, edit, output, and visualize geographic data. Much of this often happens within a spatial database; however, this is not essential to meet the definition of a GIS. In a broader sense, one may consider such a system also to include human users and support staff, procedures and workflows, the body of knowledge of relevant concepts and methods, and institutional organizations.

The uncounted plural, geographic information systems, also abbreviated GIS, is the most common term for the industry and profession concerned with these systems. The academic discipline that studies these systems and their underlying geographic principles, may also be abbreviated as GIS, but the unambiguous GIScience is more common. GIScience is often considered a subdiscipline of geography within the branch of technical geography.

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Spatial analysis in the context of Kriging

In statistics, originally in geostatistics, kriging or Kriging (/ˈkrɡɪŋ/), also known as Gaussian process regression, is a method of interpolation based on Gaussian process governed by prior covariances. Under suitable assumptions of the prior, kriging gives the best linear unbiased prediction (BLUP) at unsampled locations. Interpolating methods based on other criteria such as smoothness (e.g., smoothing spline) may not yield the BLUP. The method is widely used in the domain of spatial analysis and computer experiments. The technique is also known as Wiener–Kolmogorov prediction, after Norbert Wiener and Andrey Kolmogorov.

The theoretical basis for the method was developed by the French mathematician Georges Matheron in 1960, based on the master's thesis of Danie G. Krige, the pioneering plotter of distance-weighted average gold grades at the Witwatersrand reef complex in South Africa. Krige sought to estimate the most likely distribution of gold based on samples from a few boreholes. The English verb is to krige, and the most common noun is kriging. The word is sometimes capitalized as Kriging in the literature.

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Spatial analysis in the context of Aetiology

Etiology (/ˌtiˈɒləi/; alternatively spelled aetiology or ætiology) is the study of causation or origination. The word is derived from the Greek word αἰτιολογία (aitiología), meaning "giving a reason for" (from αἰτία (aitía) 'cause' and -λογία (-logía) 'study of'). More completely, etiology is the study of the causes, origins, or reasons behind the way that things are, or the way they function, or it can refer to the causes themselves. The word is commonly used in medicine (pertaining to causes of disease or illness) and in philosophy, but also in physics, biology, psychology, political science, geography, cosmology, spatial analysis and theology in reference to the causes or origins of various phenomena.

In the past, when many physical phenomena were not well understood or when histories were not recorded, myths often arose to provide etiologies. Thus, an etiological myth, or origin myth, is a myth that has arisen, been told over time or written to explain the origins of various social or natural phenomena. For example, Virgil's Aeneid is a national myth written to explain and glorify the origins of the Roman Empire. In theology, many religions have creation myths explaining the origins of the world or its relationship to believers.

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