Advanced techniques for hyperspectral/LiDAR sensor data integration

集成的高光谱和激光雷达数据将成为广泛的环境和交通工程应用的重要工具。激光雷达数据主要提供扫描环境的3D几何图形，而高光谱传感器提供有关调查对象的辐射方面的数据。多传感器集成一直是多年来研究的热点之一。然而，许多挑战还没有得到解决，特别是当从激光雷达和高光谱传感器收集的数据被整合时。这是由于传感器数据收集技术和收集的数据的处理方式不同造成的。这项拟议的研究计划侧重于开发多传感器集成和数据处理的创新技术和技术。该计划的主要目标是：a)开发低成本的轻量级3D-高光谱测绘系统，具有室内和室外测绘的平台切换能力；b)开发用于室内3D建模和制图的新方法和算法；以及c)开发用于点云分类和特征提取的遗传算法。开发的一体化3D高光谱测绘系统将允许用户以“即插即用”的概念切换采集模式(即从机载、地面和移动平台)。将开发一种创新的软件，首次自动整合激光雷达捕获的数据和高光谱传感器。将开发一种新的室内测绘和三维建模方法，而不依赖室内基础设施(例如WiFi信号)或全球导航卫星系统信号。将进一步开发新的算法，以进一步提高基于多传感器系统收集的数据进行信息提取的自动化程度。所开发的技术将服务于新兴环境和交通监测与建模(ETMM)的各种应用。主要重点将放在智能城市3D建模、噪声测绘、用于采矿的室内测绘以及道路质量检测。拟议的研究计划是发明轻量级3D-高光谱测绘系统的第一个项目，该系统具有平台切换能力，并与相应的知识发现数据处理算法相关联。拟议的研究工作将作为若干基础研究的核心，这些研究将促进激光雷达和高光谱数据处理在工程应用中的使用。这项研究可能会支持该行业的技术转让和商业化，并巩固HQP的培训。

Integrated hyperspectral and LiDAR data will be an essential tool for a wide variety of environmental and transportation engineering applications. LiDAR data provide primarily the 3D geometry of the scanned environment while hyperspectral sensors deliver data on the radiometric aspects of the surveyed objects. Multi-sensor integration has been one of the active research topics for several years. However, many challenges have not been solved yet; particularly, when data collected from LiDAR and hyperspectral sensors are integrated. This is due to the differences of the sensor data collection techniques and how the data collected is processed. This proposed research program focuses on the development of innovative techniques and technologies for multi-sensor integration and data processing. The program main objectives are: a) Develop low-cost light-weight 3D-hyperspectral mapping system with platform-switching capability for indoor and outdoor mapping; b) Develop new approaches and algorithms for indoor 3D modelling and mapping; and c) Develop genetic algorithms for point cloud classification and feature extraction. The developed all-in-one 3D-hyperspectral mapping system will allow users to switch collection modes (i.e. from airborne, terrestrial, and mobile platforms) with a "plug-and-go" concept. An innovative software will be developed to automatically integrate, for the first time, data captured by LiDAR, and hyperspectral sensors. A new approach will be developed for indoor mapping and 3D modelling without any dependence on indoor infrastructure (e.g. WiFi signal) or GNSS signals. New algorithms will be further developed to further improve the automation of information extraction based on the data collected by the multi-sensor systems. The techniques developed will serve in variety of applications in emerging environment and transportation Monitoring and Modelling (ETMM). Primarily focus will be given to smart city 3D modelling, noise mapping, indoor mapping for mining, and road quality detection. The proposed research program is the first of its kind at inventing a light-weight 3D-hyperspectral mapping system with platform switching capability associated with the corresponding data processing algorithms for knowledge discovery. The proposed research work will serve as a core for a number of fundamental research studies yet to come to facilitate the use of LiDAR and hyperspectral data processing for engineering applications. The research will potentially support technology transfer and commercialisation to the industry and consolidates the training of HQP.