This document explains the Point Cloud Extension to the SpatioTemporal Asset Catalog (STAC) specification. It adds fields to a STAC Item, to enable STAC to more fully describe point cloud datasets. The point clouds can come from either active or passive sensors, and data is frequently acquired using tools such as LiDAR or coincidence-matched imagery.
Field Name Type Description pc:count integer REQUIRED. The number of points in the Item. pc:type string REQUIRED. Phenomenology type for the point cloud. Possible valid values might includelidar
, eopc
, radar
, sonar
, or other
pc:schemas [Schema Object] A sequential array of Items that define the dimensions and their types. pc:density number Number of points per square unit area. pc:statistics [Stats Object] A sequential array of Items mapping to pc:schemas
defines per-channel statistics.
A sequential array of Items that define the dimensions or channels of the point cloud, their types, and their sizes (in full bytes).
Field Name Type Description name string REQUIRED. The name of the dimension. size integer REQUIRED. The size of the dimension in bytes. Whole bytes only are supported. type string REQUIRED. Dimension type. Valid values arefloating
, unsigned
, and signed
A sequential array of Items mapping to pc:schemas
defines per-channel statistics. The channel name is required and at least one statistic.
All contributions are subject to the STAC Specification Code of Conduct. For contributions, please follow the STAC specification contributing guide Instructions for running tests are copied here for convenience.
The same checks that run as checks on PR's are part of the repository and can be run locally to verify that changes are valid. To run tests locally, you'll need npm
, which is a standard part of any node.js installation.
First you'll need to install everything with npm once. Just navigate to the root of this repository and on your command line run:
Then to check markdown formatting and test the examples against the JSON schema, you can run:
This will spit out the same texts that you see online, and you can then go and fix your markdown or examples.
If the tests reveal formatting problems with the examples, you can fix them with:
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