ACTION-189: Cochrane to create a matrix of datatypes related to best practices for inclusion in bp document

Common Spatial data types – A data publishers view of different spatial data that they may wish to share

•Vectors – represent real world features and events using coordinate values. Can be thought of as drawings as apposed to paintings. There are several major subtypes
--Points – Approximate location of real world events and objects.
o Linear networks – Lines representing real world features in 1 dimension which connect to form pathways on which analysis can be done e.g. roads, utilities, waterways.
o Linear features – Lines representing real world objects and events e.g. trajectories, fences, walls
o Polygons – 2 dimensional representations of real world features and events. May form a fabric with rules of topology that describe how the features behave with each other
o 3D plus –
 TINs
 CityGML – LODs
 * Batched 3D Models – for buildings, terrain, massive models, etc.
 * Instanced 3D Models – for trees, bolts, valves, etc.
 * Point Clouds – for massive point clouds
 * Vector Data – for 3D points, polylines, and polygons, including extrusions
 * Composite – a tile of tiles to allow aggregation
• Raster - In raster data the entire area of the map is subdivided into a grid of tiny cells. A value is stored in each of these cells to represent the nature of whatever is present at the corresponding location on the ground. Raster data can be thought of as a matrix of values. Is analogous to painting as apposed to drawing.
o Gridded - The major use of raster data involves storing map information as digital images, in which the cell values relate to the pixel colours of the image and cell size corresponds to a measured distance. To reproduce the image the computer reads each of these cell values one by one and applies them to the pixels on the screen. Each cell has regular dimensions that relate to a real world measurement. To be shared on the web for use with other spatial data, images must be first registered and rectified to a projected CRS.
 Thematic
 Continuous – orthophoto imagery
o DEMs
o Point clouds
• CAD, Site plans & BIM – not generally tied to real world coordinates and thus difficult to use in conjunction with other spatial data.
• Sensor (Time series) data – collection of data at intervals
o mobile sensors (vehicle tracking),
o remote sensing (satellites),
o static sensors (river monitoring).
• Labels and Symbology
• Models and processing
• GPS data (Vector with Coordinates)