Development of classification tools for multi-spectral LiDAR data

多光谱激光雷达数据分类工具的开发

• 批准号: 488260-2015
• 负责人: AbdElrahman, AhmedShaker
• 金额: $ 2.91万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=618071
• 关键词: Development; classification; tools; multi; spectral

Multi-Spectral Light Detection and Ranging (LiDAR) sensors are a new and emerging technology serving several civil, industrial and military applications. With the launch of the new Teledyne Optech sensor "Titan", applications using LiDAR technology entered a new era. The Titan sensor is a laser scanner sensor which operates in three different wavelengths simultaneously (1550, 1064, and 532 nm) and allows recording of object properties from the reflectance of the laser energy of objects. The use of the back scatter energy of the LiDAR sensor pulses (intensity data) has been extensively explored over the last few years. Recent research showed the potential use of the intensity data in land cover classification. However, extensive processing is required to radiometrically correct the intensity data and there is a need for special classification algorithms to maximize the benefit from the use of the LiDAR intensity data. The proposed project will contribute to the Titan technology by further developing and enhancing the radiometric correction models of the LiDAR intensity data. The research team will collaborate with the industrial partner to embed its developments of the radiometric correction process within the process of data collection and delivery. The proposed project is also aiming to develop new image and point classification algorithms that use both the range and intensity data collected by the new sensor for land cover classification. Special focus is given to develop algorithms that work efficiently for land/water delineation automatically from the LiDAR multispectral data. The project will have a direct impact on the LiDAR industry, taking the lead on facilitating the use of multi-spectral LiDAR data. It will also support Canadian leadership in the laser industry.

多光谱光探测和测距（LiDAR）传感器是一种新兴的技术，服务于多种民用，工业和军事应用。随着新型Teledyne Optech传感器“Titan”的推出，使用LiDAR技术的应用进入了一个新时代。Titan传感器是一种激光扫描传感器，可同时在三种不同波长（1550、1064和532 nm）下工作，并可通过物体激光能量的反射率记录物体属性。在过去的几年里，人们广泛探索了激光雷达传感器脉冲（强度数据）反向散射能量的使用。最近的研究表明，强度数据在土地覆盖分类中具有潜在的用途。然而，需要大量的处理来辐射校正强度数据，并且需要特殊的分类算法来最大化使用LiDAR强度数据的益处。拟议项目将通过进一步开发和加强激光雷达强度数据的辐射校正模型，为泰坦技术作出贡献。研究团队将与工业合作伙伴合作，将其辐射校正过程的开发嵌入数据收集和交付过程中。拟议项目还旨在开发新的图像和点分类算法，利用新传感器收集的范围和强度数据进行土地覆盖分类。特别注重开发算法，有效地自动从激光雷达多光谱数据的土地/水划定。该项目将对激光雷达行业产生直接影响，率先促进多光谱激光雷达数据的使用。它还将支持加拿大在激光行业的领导地位。