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The format supports raster attribute tables, image pyramids, meta-data and in-built statistics while also handling very large files and compression throughout.\r\n\r\nBased on the [HDF5](https://www.hdfgroup.org/HDF5/) standard, it also provides a base from which other formats can be derived and is a good choice for long term data archiving. An independent software library (libkea) provides complete access to the KEA image format and a GDAL driver allowing KEA images to be used from any GDAL supported software. \r\n\r\n# Download #\r\n## Binaries ##\r\n\r\nBinaries for Windows, Linux and Mac are available through Conda.\r\n\r\nDrivers for ArcMap and ERDAS Imagine are available from [releases](https://github.com/ubarsc/kealib/releases)\r\n\r\n## Source ##\r\n\r\nKEALib requires: [HDF5](https://www.hdfgroup.org/HDF5/) with the C++ libraries and headers. [GDAL](http://gdal.org/) is required to build the GDAL driver.\r\n\r\n# Documentation #\r\n\r\nSome documentation on compilation is available in the [KEALib wiki](https://github.com/ubarsc/kealib/wiki).\r\n\r\nDocumentation on the GDAL data model and API is available from the [GDAL website](http://gdal.org/).\r\n\r\nThere is also a [paper](http://dx.doi.org/10.1016/j.cageo.2013.03.025) describing the features of the format.\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fubarsc%2Fkealib","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fubarsc%2Fkealib","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fubarsc%2Fkealib/lists"}