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Spatial data science & location intelligence Spatial SQL, spatial data science, location analytics, site selection, data visualization, mapping, geocoding and app development. Access to a catalog of 1,000s of spatial datasets. Proprietary (with free trial available). Fract No Linux, Windows, Unix, iOS, Android, Windows Phone, Cloud: Fract, Inc.
A spatiotemporal database embodies spatial, temporal, and spatiotemporal database concepts, and captures spatial and temporal aspects of data and deals with: Geometry changing over time and/or Location of objects moving over invariant geometry (known variously as moving objects databases [ 1 ] or real-time locating systems ).
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 ...
The Geospatial Data Abstraction Library (GDAL) is a computer software library for reading and writing raster and vector geospatial data formats (e.g. shapefile), and is released under the permissive X/MIT style free software license by the Open Source Geospatial Foundation.
GeoServer – Allows users to share and edit geospatial data. Written in Java using GeoTools. deegree – Java framework; PyWPS – implementation of the OGC Web Processing Service standard, using Python; pygeoapi - A Python server implementation of the OGC API suite of standards for geospatial data.
The transformation phase of a spatial ETL process allows a variety of functions; some of these are similar to standard ETL, but some are unique to spatial data. [3] Spatial data commonly consists of a geographic element and related attribute data; therefore spatial ETL transformations are often described as being either geometric transformations – transformation of the geographic element ...
The field develops software and web services to model and analyse spatial data, serving the needs of geosciences and related scientific and engineering disciplines. The term is often used interchangeably with Geomatics , although the two have distinct focuses; Geomatics emphasizes acquiring spatial knowledge and leveraging information systems ...
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.