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The book has 10 chapters, divided into two sections on geodesy and on techniques for visualization of spatial data; each chapter has separate sections on theory and practice. [1] For practical aspects of geographic information systems it uses ArcGIS as its example system. [2]
An example of gridded data would be a satellite image of forest density that has been digitized on a grid. An example of a point set would be the latitude/longitude coordinates of all elm trees in a particular plot of land. More complicated forms of data include marked point sets and spatial time series.
There are also many different types of geodata, including vector files, raster files, geographic databases, web files, and multi-temporal data. Spatial data or spatial information is broader class of data whose geometry is relevant but it is not necessarily georeferenced, such as in computer-aided design (CAD), see geometric modeling.
Because the world is much more complex than can be represented in a computer, all geospatial data are incomplete approximations of the world. [9] Thus, most geospatial data models encode some form of strategy for collecting a finite sample of an often infinite domain, and a structure to organize the sample in such a way as to enable interpolation of the nature of the unsampled portion.
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 ...
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 .
Geographers use statistics in numerous ways: [citation needed] To describe and summarize spatial data. To make generalizations concerning complex spatial patterns. To estimate the probability of outcomes for an event at a given location. To use samples of geographic data to infer characteristics for a larger set of geographic data (population).
This is a list of GIS data sources (including some geoportals) that provide information sets that can be used in geographic information systems (GIS) and spatial databases for purposes of geospatial analysis and cartographic mapping. This list categorizes the sources of interest.