LIDAR sensors quickly produce millions of points with large numbers of
variables measured on each point. The challenge for a point cloud database
extension is efficiently storing this data while allowing high fidelity access
to the many variables stored.
PostgreSQL Pointcloud deals with all this variability by using a "schema
document" to describe the contents of any particular LIDAR point. Each point
contains a number of dimensions, and each dimension can be of any data type,
with scaling and/or offsets applied to move between the actual value and the
value stored in the database. The schema document format used by PostgreSQL
Pointcloud is the same one used by the [PDAL](http://pointcloud.org) library.
Note that this needs cmake 3.7.2p3 to build.
ok dcoppa@
Laspy is a pythonic library for reading, modifying and writing LAS
files, ie point cloud data. Support for LAZ is limited to reading LAS
version 1.0-1.4 files. Laspy is compatible with Python 2.6+ and 3.5+.
Laspy includes a set of command line tools which can be used to do basic
file operations like format translation and validation as well as
comparing LAS files.
WWW: https://github.com/laspy/laspy
ok sthen@
PDAL is a C++ BSD library for translating and manipulating point cloud
data. It is very much like the GDAL library which handles raster and
vector data.
In addition to the library code, PDAL provides a suite of command-line
applications that users can conveniently use to process, filter,
translate, and query point cloud data.
WWW: https://pdal.io
ok sthen@ ajacoutot@
This library provides a command-line-interface (CLI) and Python library
to make access to Planet's public Data API easy to use.
The Data API is a REST HTTP API interface to Planet's imagery archive.
The API supports the following tasks: quick-searching assets and viewing
thumbnails of imagery; filtering imagery by location, date, satellite
source, cloud cover, and many other attributes; and downloading imagery
and metadata in several formats.
Feedback sthen@, danj@
OK danj@
