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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.
The origin of the geodatabase was in the mid-1990s during the emergence of the first spatial databases.One early approach to integrating relational databases and GIS was the use of server middleware, a third-party program that stores the spatial data in database tables in a custom format, and translates it dynamically into a logical model that can be understood by the client software.
A georelational data model is a geographic data model that represents geographic features as an interrelated set of spatial and attribute data. The georelational model was the dominant form of vector file format during the 1980s and 1990s, including the Esri coverage and Shapefile. [1]
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.
Geospatial metadata (also geographic metadata) is a type of metadata applicable to geographic data and information.Such objects may be stored in a geographic information system (GIS) or may simply be documents, data-sets, images or other objects, services, or related items that exist in some other native environment but whose features may be appropriate to describe in a (geographic) metadata ...
Geospatial and hydrospatial analysis, or just spatial analysis, [70] is an approach to applying statistical analysis and other analytic techniques to data which has a geographical or spatial aspect.
Digital elevation model, map (image), and vector data. Like any digital image, raster GIS data is based on a regular tessellation of space into a rectangular grid of rows and columns of cells (also known as pixels), with each cell having a measured value stored.
A spatial data infrastructure (SDI), also called geospatial data infrastructure, [1] is a data infrastructure implementing a framework of geographic data, metadata, users and tools that are interactively connected in order to use spatial data in an efficient and flexible way.