Abstract
Abstract. The massive amounts of spatio-temporal information often present in LiDAR data sets make their storage, processing, and visualisation computationally demanding. There is an increasing need for systems and tools that support all the spatial and temporal components and the three-dimensional nature of these datasets for effortless retrieval and visualisation. In response to these needs, this paper presents a scalable, distributed database system that is designed explicitly for retrieving and viewing large LiDAR datasets on the web. The ultimate goal of the system is to provide rapid and convenient access to a large repository of LiDAR data hosted in a distributed computing platform. The system is composed of multiple, share-nothing nodes operating in parallel. Namely, each node is autonomous and has a dedicated set of processors and memory. The nodes communicate with each other via an interconnected network. The data management system presented in this paper is implemented based on Apache HBase, a distributed key-value datastore within the Hadoop eco-system. HBase is extended with new data encoding and indexing mechanisms to accommodate both the point cloud and the full waveform components of LiDAR data. The data can be consumed by any desktop or web application that communicates with the data repository using the HTTP protocol. The communication is enabled by a web servlet. In addition to the command line tool used for administration tasks, two web applications are presented to illustrate the types of user-facing applications that can be coupled with the data system.
Highlights
Laser scanning or Light Detection And Ranging (LiDAR) is one of the latest technologies for airborne topographic mapping
As an effort towards constructing a scalable spatio-temporal database to provide web service access to LiDAR point cloud and full waveform data, this paper presents the key LiDAR database components in a data system called Ariadne3D
As HBase does not have built-in spatial capabilities, extensions are developed in Ariadne3D to index LiDAR point cloud and full waveform (FWF) data stored in HBase and to enable spatial and temporal queries
Summary
Laser scanning or Light Detection And Ranging (LiDAR) is one of the latest technologies for airborne topographic mapping. Retention of full waveform data is becoming a more common practice in LiDAR data acquisition Due to their high potential value and wide range of applications (US Geological Survey, 2020), airborne LiDAR data are being acquired at massive scales. In the United States, the US Geological Survey is leading the 3D Elevation Program (3DEP), a decade-long national project that aims to complete the acquisition of nationwide LiDAR mapping by 2023. The first national LiDAR scan of the Netherlands (Actueel Hoogtebestand Nederland 1 AHN1) completed in 2003 with most of the country mapped at a density under 1 points/m2. AHN4 is set to start in 2020 and to complete by 2023 (https://www.ahn.nl/ahn-4) Those few selected examples of large-scale LiDAR projects illustrate the massive amounts of LiDAR data being collected worldwide. The FWF LiDAR dataset collected over 2 km in Dublin city in Ireland by Laefer et al (2017) is the only large-scale FWF LiDAR dataset publicly available outside the US known to the authors
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