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Spatial statistics is a field of applied statistics dealing with spatial data. It involves stochastic processes ( random fields , point processes ), sampling , smoothing and interpolation , regional ( areal unit ) and lattice ( gridded ) data, point patterns , as well as image analysis and stereology .
Local spatial autocorrelation statistics provide estimates disaggregated to the level of the spatial analysis units, allowing assessment of the dependency relationships across space. G {\displaystyle G} statistics compare neighborhoods to a global average and identify local regions of strong autocorrelation.
A GIS system to create, visualize, manage, and analyze spatial data. Supports desktop, web, and mobile applications. In addition to spatial data editing and visualization, ArcGIS provides spatial analysis and modeling features including overlay, surface, proximity, suitability, and network analysis, as well as interpolation analysis and other ...
Spatial descriptive statistics is the intersection of spatial statistics and descriptive statistics; these methods are used for a variety of purposes in geography, particularly in quantitative data analyses involving Geographic Information Systems (GIS).
GIS data acquisition includes several methods for gathering spatial data into a GIS database, which can be grouped into three categories: primary data capture, the direct measurement phenomena in the field (e.g., remote sensing, the global positioning system); secondary data capture, the extraction of information from existing sources that are ...
Geostatistics is a branch of statistics focusing on spatial or spatiotemporal datasets.Developed originally to predict probability distributions of ore grades for mining operations, [1] it is currently applied in diverse disciplines including petroleum geology, hydrogeology, hydrology, meteorology, oceanography, geochemistry, geometallurgy, geography, forestry, environmental control, landscape ...
Getis–Ord statistics, also known as G i *, are used in spatial analysis to measure the local and global spatial autocorrelation.Developed by statisticians Arthur Getis and J. Keith Ord they are commonly used for Hot Spot Analysis [1] [2] to identify where features with high or low values are spatially clustered in a statistically significant way.
Web processing services allow users to perform GIS calculations on spatial data. [3] Web processing services standardize inputs, and outputs, for spatial data within an internet GIS and may have standardized algorithms for spatial statistics.