Processing LiDAR at the Speed of Light

Author: Linda Duffy

LiDAR数据可能是一件好事。最新一代的机载激光雷达传感器能够收集非常密集的点云，其中包含许多应用程序的关键信息；但是，对于缺乏投资所需计算基础架构的资源的初学者和公司来说，处理和管理这些庞大的数据集令人生畏。较长的处理时间可以缩短整个工作流程并延迟最重要的步骤 - 分析数据并向客户提供可行的情报以实现决策。

空中激光雷达数据

Solspecis a geospatial data collection, processing and analytics company with unique expertise in remote sensing applications of earth science. This Denver-based company started out offering drone acquisition and processing services, primarily to the oil and gas industry, but soon pivoted to a scalable aerial strategy serving a broad range of customers.

In 2019, SolSpec purchased a pair ofLeica TerrainMapper线性模式激光雷达传感器内置数字cameras that capture 4-band data (RGB and NIR) and cover more ground in a far shorter time than a drone. The aircraft-mounted system flies much higher and faster, efficiently collecting a broader area, and making it a scalable tool for diverse situations. On average, a single day of capture at 20 points per square metre (ppsm) produces 1 TB of highly accurate data.

“By collecting higher point densities with the TerrainMapper, we provide better data to our customers,” says Seth Tribbey, VP of Sales and Marketing at SolSpec. “This translates into more valid analytics to support the decisions being made.”

高性能计算技术

在将传统的处理工作流程确定为基于空中激光雷达数据加快信息的障碍之后，Solspec意识到云提供了机会扩展多台机器以并行处理数据。为了利用云的近乎无限的计算能力，创新的公司在高性能计算和机器学习骨架上构建了Solspec引擎。

Leica HxMap这是一个多传感器平台，旨在利用TerrainMapper数据的好处，具有开放的接口处理工作流，可容纳云处理，这在行业中是独一无二的。可以将HXMAP从单个工作站安装到高端集群环境，并具有数百个节点用于大量生产。可以使用许多命令行应用程序在不同的发动机中进行编排工作流，这些应用程序可以脚本脚本以实现各种工作流以生产不同的输出产品。亚搏彩票手机版下载

When deployed on top of the SolSpec Engine in the Amazon Web Services (AWS) cloud, HxMap processes large volumes of aerial data in a compressed time frame. Deployment of HxMap into the AWS cloud on Linux allowed SolSpec to rapidly scale data processing capacity. The company increased its processing speed for large airborne LiDAR data sets by up to 60 times, which reduced post-processing costs and decreased the data delivery time to the customer. In addition, by building decision-ready analytics into the SolSpec Engine, SolSpec significantly reduced “time-to-decision” with LiDAR data.

Tribbey说：“六边形在拥抱新技术和与我亚搏苹果app们合作的意愿方面表现出的灵活性是我们合作伙伴关系的主要动力。”“我们已经自动化了专有的TerrainMapper格式，采用了核心库，并将其改编成在云引擎顶部运行。与常规提供者相比，这种结构使我们能够从原始波形数据到点云到一小部分的地形模型。”

Solspec Geohazard Analytic建立在机器学习的基础上，并在15,000个历史滑坡上接受了培训，即使在植被覆盖的地区，也可以在数字地形模型中识别滑坡标志。礼貌的索尔斯克。

Real-life applications

One flagship product for SolSpec is Right-of-Way (ROW) Integrity Management. Pipeline operators frequently deal with environmental conditions like landslides and erosion that threaten to rupture pipes and interrupt service. If there is a thick tree canopy obscuring the slide activity, it is difficult to identify problems. The TerrainMapper effectively penetrates tree canopies to collect high density point clouds that contain a great level of detail. After processing data in the cloud, machine-learning algorithms are used to identify hazards through the canopy, alerting customers more quickly to potential issues.

Similarly, SolSpec’s vegetation management solutions are highly dependent on rich, high density point clouds combined with the high resolution 4-band spectral data from the TerrainMapper. By leveraging spectral and structural data, SolSpec data scientists have developed algorithms that detect where vegetation is encroaching on powerlines, predict wildfire risk, identify wetlands, classify vegetation types for assessing reclamation activities, and many other applications.

Tribbey说：“我们与TerrainMapper的数据收集与HXMAP的处理之间有着完美的婚姻。”“这使我们能够利用AWS上几乎无限的计算能力，并更快地传递信息。”

SOLSPEC的表面水文分析模型的水文能量和高分辨率数字地形模型的表面流量准确鉴定侵蚀问题。礼貌的索尔斯克。

简化激光雷达价值链

Solspec’s ultimate goal is to transform aerial data into actionable risk analysis, decision support and predictive modelling. By combining aerial data and project-specific data with machine learning tools, SolSpec produces comprehensive reports about site conditions more quickly than other providers.

Approximately half of a LiDAR project’s cost is acquiring data, and the other half is processing. A conventional provider may take 30 hours to process 3 square miles of data (20 ppsm, QL1) in the office, while the SolSpec Engine does the same work in 20 minutes in the cloud. Processing with HxMap on the super-fast SolSpec Engine is a key competitive advantage to support time-sensitive decision making.

“Hexagon was an obvious choice for us as a partner because of its reputation in the aerial LiDAR industry,” continues Tribbey. “Its sensors and software are very reliable and produce excellent results.”

The combined time savings of processing in the cloud and automating analytics with machine-learning algorithms increases the value of LiDAR data and expands its usefulness to a variety of markets.

“SolSpec helps its customers identify, measure, prioritise and monitor the most common environmental threats to their infrastructure on a recurring basis,” explains Tribbey. “We streamline the entire LiDAR value chain by processing more quickly, managing the data, running the analytics, and providing the answers that customers need. This enables our customers to quickly make decisions about erosion, geohazards, vegetation, encroachment, structures, and more at scale.”