This time, four different news items from around the open source and open data worlds
Software: TOPS (Total Open Station)
For the surveying crowd, a new project surfaced a few weeks ago. TOPS (Total Open Station)  is an open source, Python-based system for downloading and processing data from total station devices. Historically, the software to work with a particular model station has been provided by the hardware vendor, which means N different programs for N different devices. TOPS promises to simplify this process by having one software system that understands the formats from multiple devices.
TOPS represents the kind of software that the open source world often excels at: providing an abstraction layer on top of device-specific protocols, so that tools (or users!) at the next level up in the stack dont have to know or care whats underneath. Interoperability through de facto or de jure standardization: it all just looks and feels the same.
TOPS is a young project, only at version 0.3, but it already supports several station models and has several users in the field of archeology.
OpenTopography (OT)  is a website that describes itself as a portal to high-resolution topography data and tools. Its mission statement is broad and ambitious:
Democratize online access to high-resolution (meter to sub-meter scale), Earth science-oriented, topography data acquired with LiDAR and other technologies.
Harness cutting edge cyberinfrastructure to provide Web service-based data access, processing, and analysis capabilities that are scalable, extensible, and innovative.
Promote discovery of data and software tools through community populated metadata catalogs.
Partner with public domain data holders to leverage OpenTopography infrastructure for data discovery, hosting and processing.
Provide professional training and expert guidance in data management, processing, and analysis.
Foster interaction and knowledge exchange in the Earth science LiDAR user community.
As of this writing, their site is hosting 20,000 km2 of data covering almost 100 billion point returns all of it free of copyright restrictions for both commercial and noncommercial usage. This is open data at its best. The OT effort is funded in part by NSF and hosted by the San Diego Supercomputer Center at UCSD.
(In a future column, I hope to provide more links to more providers of free data of interest to the lidar community.)
As its mission says, the OpenTopography project is not just about hosting data they also provide tools. Points2Grid (P2G)  is the open source tool they have built and shared for generating DEMs (regularly-gridded elevation data) from point clouds.
Nave grid generation can be done with a very simple algorithm: divide the (x,y) surface area into uniform cells, then take the average (or min, or max) of all the points that fall into each cell. Unfortunately, of course, this approach doesnt provide a very good approximation for areas with highly contrasting elevations. P2G uses a more sophisticated approach, trading off some computational efficiency for very good representational accuracy.
The P2G command-line tool can be used essentially like this:
points2grid -i cloud.las -o dem.grid
Various options are available for specifying file formats, controlling the grid size, and so on.
P2G 1.0.1 was recently released under the BSD open source license, which makes it friendly for use even in commercial and government settings. (P2G relies on libLAS, another open source library which we discussed in an earlier column.)
The Point Cloud Library (PCL)  is an open source library for manipulating very generic point cloud data filtering, segmenting, transforming, and much more. (By way of contrast, the libLAS and PDAL libraries and the lastools suite are more focused on the interchange and low-level processing of lidar data.) PCL deserves a whole column of its own, and someday soon Ill do that, but for now I just want to highlight an award they just received.
For the past five years, the Ministry of Knowledge and Economy of Korea has held the Open Source Software World Challenge, a competition designed to highlight and recognize the best projects the open source world has to offer. This year, in a field of 56 projects from 22 countries, PCL was given the grand prize.
Clearly this award shows that the PCL team has done some great work (and in a relatively short time, too). But what I find even more impressive is that a library filled with such lets be candid deeply mathematical algorithms could win such an award. I would have expected the prize to go to something more readily accessible by the judges perhaps a new browser extension, or yet another social media service, or even some new cloud-based thing. The PCL team deserves much credit for presenting an otherwise intimidating topic in a readily usable form for us users.
We in the lidar and point cloud communities should be grateful we have such highly regarded tools to work with.