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Spatial data represents various aspects of geography as layers on a map. Attribute data stores information about those layers as rows and columns in a table.
GIS stands for Geographic Information Systems. These are information systems (software) used to manage geographic data. Geographic data (or geodata) are data describing the location, position or spread of things, usually using coordinates.
geospatial data, spatial data can be data in any format with any coordinate reference in any storage type. geographic data (outside the national geographic context) is rdbms native spatially enabled lat/lon data. geodata is any type of data as a service served by a web server.
The process of data mining consists of several steps, including data selection, data cleaning, integration, storage, transformation, data mining, pattern evaluation, and knowledge representation.
How do you design and implement a spatial data mining project from start to finish? Define the problem and the data. Choose the methods and tools. Apply the methods and tools. Analyze and interpret the results. Validate and generalize the results. Review and improve the project. Heres what else to consider.
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Spatial data is any type of data that directly or indirectly references a specific geographical area or location. Sometimes called geospatial data or geographic information, spatial data can also numerically represent a physical object in a geographic coordinate system.
Examples of spatial data include maps, satellite images, GPS data, and other geospatial information. Spatial data mining involves analyzing and discovering patterns, relationships, and trends in this data to gain insights and make informed decisions.
In a geographical context, weather and climate data track changes in temperature and meteorological information over time. Demographic trends, land use patterns, and lightning strikes are also examples of multi-temporal geodata.

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