OpenTopography Tool Registry

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The OpenTopography Tool Registry provides a community populated clearinghouse of software, utilities, and tools oriented towards high-resolution topography data (e.g. collected with lidar technology) handling, processing, and analysis. Tools registered below range from source code to full-featured software applications. We welcome contributions to the registry via the Contribute a Tool page.

Appearance of a tool in the OpenTopography Tool Registry does not imply endorsement, recommendation, or support, by the NSF OpenTopography Facility and is meant simply as a service to our users. OpenTopography does not guarantee the completeness or accessibility of specific content and links contributed by users. If you have been directly involved with the development of a registered tool and are not the original contributor of the tool to the registry, please email info@opentopography.org to supply updates or modifications to its entry.
Tool Name Date   Tool Type Rating
1   Point Cloud Library (PCL 13 Aug 2011 Point Cloud Analysis
Keywords: point clouds, visualization, processing, segmentation, filtering, feature estimation, registration
License: BSD license

Description: The Point Cloud Library (or PCL) is a large scale, open project for point cloud processing.

The PCL framework contains numerous state-of-the art algorithms including filtering, feature estimation, surface reconstruction, registration, model fitting and segmentation.

PCL is released under the terms of the BSD license and is open source software. It is free for commercial and research use. The project is financially supported by multiple companies, including: Willow Garage, NVidia, Google, and Toyota


2   LiForest(LiDAR Forest Software) 9 Mar 2014 Point Cloud Analysis
Keywords: Forest metrics, regression models, individual tree segmentation, point cloud segmentation
License: Commercial License

Description: LiForest (LiDAR software for forestry applications) provides a platform that enables users to freely manipulate the LiDAR point cloud and extract useful information specially for forest studies. It consists of several primary modules for LiDAR point cloud data processing, including point cloud I/O, LiDAR-based forest metric calculation, digital model generation, regression models and individual tree segmentation.

3   Lidar360 5 Jul 2018 Visualization, Point Cloud Analysis, DEM generation, DEM Analysis, Data Management / Handling, Software Suite
Keywords: Point Cloud Processing, Terrain Classification, ALS Forestry, TLS Forestry, Lidar Power line Survey
License: Commercial License

Description: Lidar360 is a comprehensive point cloud post-processing software suite developed by GreenValley International Inc (GVI). It offers a huge collection of tools and functions, from basic point cloud management tools like outlier removal, normalization, projection, and extraction, to advanced algorithms for industry-specific applications, e.g. Terrain, ALS/TLS Forestry, and Powerline Survey. The Lidar360 suite consists of 5 modules (as of June 2018):
1. Framework -- contains a number of core toolsets to effectively visualize and interact with lidar point cloud including display modes, statistics, data management, classification tools, vector editing and strip adjustment;
2. Terrain -- a suite of GIS tools for calculating slope, roughness, aspect & contours from surface models. Additionally, it contains tools for repairing surface models, i.e., spikes, holes and extraneous values;
3 & 4. ALS/TLS Forestry -- The ALS Forestry functions allow users to calculate essential forest metrics including elevation, intensity, canopy cover, LAI etc., and provides regression models and segmentation algorithms such as CHM Segmentation & Point Cloud Segmentation. The TLS Forestry tools are specifically designed to work with terrestrial lidar data. It offers a wealth of tools including Gaussian Mixture Model Classification and TLS Point Cloud segmentation, enabling the users to better classify ground, leaf and trunk points and segment individual trees from TLS point cloud data; and,
5. Power