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The shapefile format is a digital vector storage format for storing geographic location and associated attribute information. This format lacks the capacity to store topological information. The shapefile format was introduced with ArcView GIS version 2 in the early 1990s. It is now possible to read and write geographical datasets using the ...
Feature class A dataset based on the vector data model, storing a list of objects with a geometric shape in one column and a set of attributes in additional columns. While this may seem similar to earlier vector file formats such as the shapefile , several enhancements have been added.
In geographic information systems, a feature is an object that can have a geographic location and other properties. [1] Common types of geometries include points , arcs , and polygons . Carriageways and cadastres are examples of feature data.
Raster data is stored in various formats; from a standard file-based structure of TIFF, JPEG, etc. to binary large object (BLOB) data stored directly in a relational database management system (RDBMS) similar to other vector-based feature classes. Database storage, when properly indexed, typically allows for quicker retrieval of the raster data ...
When working with geodatabases, it is important to understand feature classes which are a set of features, represented with points, lines, or polygons. With shapefiles, each file can only handle one type of feature. A geodatabase can store multiple feature classes or type of features within one file. [72]
Remote properties are a general feature of GML borrowed from RDF. An xlink:href attribute on a GML geometry property means that the value of the property is the resource referenced in the link. For example, a Building feature in a particular GML application schema might have a position given by the primitive GML geometry object type Point.
The logo of the United States Geological Survey (USGS) The Geographic Names Information System (GNIS) is a database of name and location information about more than two million physical and cultural features throughout the United States and its territories; as well as the associated states of the Marshall Islands, Federated States of Micronesia, and Palau; and Antarctica.
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.