点云LAS解析研究

1.背景

由于需要初步研究了下LAS点云格式的解析，记录如下，

版本为1.0、1.1、1.2、1.3、1.4这几个版本，有些库并没有支持所有这些版本，比如laspy、libLAS（仅处于维护状态，由PDAL库代替）对1.3和1.4没有很好地支持，

而PDAL库是开源的，跨平台的，且对这几个版本的LAS格式都能支持，

2.PDAL介绍

这里摘录介绍，

How is it different than other tools?

LAStools

One of the most common open source processing tool suites available for LiDAR processing is LAStools from Martin Isenburg. PDAL is different in philosophy in a number of important ways:

1. All components of PDAL are released as open source software under an OSI-approved license.
2. PDAL allows application developers to provide proprietary extensions that act as stages in processing pipelines. These might be things like custom format readers, specialized exploitation algorithms, or entire processing pipelines.
3. PDAL can operate on point cloud data of any format – not just ASPRS LAS. LAStools can read and write formats other than LAS, but relates all data to its internal handling of LAS data, limiting it to dimension types provided by the LAS format.
4. PDAL is coordinated by users with its declarative JSON syntax. LAStools is coordinated by linking lots of small, specialized command line utilities together with intricate arguments.
5. PDAL is an open source project, with all of its development activities available online at https://github.com/PDAL/PDAL

What tasks are PDAL good at?

PDAL is great at point cloud data translation work flows. It allows users to apply algorithms to data by providing an abstract API to the content – freeing users from worrying about many data format issues. PDAL’s format-free worry does come with a bit of overhead cost. In most cases this is not significant, but for specific processing work flows with specific data, specialized tools will certainly outperform it.

In exchange for possible performance penalty or data model impedance, developers get the freedom to access data over an abstract API, a multitude of algorithms to apply to data within easy reach, and the most complete set of point cloud format drivers in the industry. PDAL also provides a straightforward command line, and it extends simple generic Python processing through Numpy. These features make it attractive to software developers, data managers, and scientists.

What are PDAL’s weak points?

PDAL doesn’t provide a friendly GUI interface, it expects that you have the confidence to dig into the options of Filters, Readers, and Writers. We sometimes forget that you don’t always want to read source code to figure out how things work. PDAL is an open source project in active development, and because of that, we’re always working to improve it. Please visit Community to find out how you can participate if you are interested. The project is always looking for contribution, and the mailing list is the place to ask for help if you are stuck.

3.参考

1、点云数据的读取（las、txt、xyz格式）

备注：2016年的博客，涉及库LibLAs库；

https://blog.csdn.net/u013045316/article/details/51941850

2、点云Las文件是什么？

备注：涉及库LasTools工具、Laspy Tools

https://blog.csdn.net/qq_40985985/article/details/111184361

3、https://liblas.org/

截至2018年，libLAS已由PDAL项目取代，处于休眠或维护模式。libLAS不提供PDAL支持的LAS或LAZ 1.4。PDAL还提供了对更多格式的支持，PDAL管道的概念，Python支持，并具有OSGeo4W，Docker / Ubuntu / Alpine和OSX Homebrew的软件包。此外，纯Python的laspy http://laspy.org库更好地表达了libLAS的Python功能 ，如果您最终希望用Python处理LAS数据，请使用它代替libLAS。

简而言之，如果您是新手，请从PDAL开始。

4、https://pdal.io/about.html#what-is-pdal

PDAL is Point Data Abstraction Library. It is a C/C++ open source library and applications for translating and processing point cloud data.

 It is not limited to LiDAR data, although the focus and impetus for many of the tools in the library have their origins in LiDAR.