Spatial Data Primer
What exactly *is* spatial data?
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What exactly *is* spatial data?
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A spatial data asset is any data asset that contains spatial or location information. This term is intentionally broad, and GeoDIDs are deliberately flexible enough to identify current and legacy spatial data types, as well as ones that haven't been developed yet.
Generally, spatial data assets to fall into two categories: raster and vector.
Raster data are composed of grid cells identified by row and column. The whole geographic area is divided into groups of individual cells, which represent an image. Satellite images, photographs, scanned images, etc., are examples of raster data ().
A (very) simplified representation of a 3x3 pixel raster image in Python:
To start, GeoDID modules will natively support GeoTIFF raster datasets.
Spatial data assets are data assets - binary files, or directories of files - that contain spatially-referenced information. For v0.0, GeoDIDs natively support GeoTIFF and GeoJSON files, which are commonly-used raster and vector data formats respectively. In the future, spatial data of any format can be identified using a GeoDID, and these format extensions can be built for the @astral-geodid
software modules.
In a vector dataset, features are individual units in the dataset, and each feature typically represents a point, line or polygon. These features are represented mathematically, usually by numbers that signify either the coordinates of the point, or the vertices (corners) of the geometry - read more .
More on and , a tool for creating and exploring GeoJSON files.
More information about , plus a .
Learn more background theory on spatial data .