Development of a UAV based topographic sensor for monitoring dynamic coastal environments

尽管我们的沿海环境在提供内陆保护免受海洋洪水以及与之相关的生境和经济价值方面受到重视，但由于成本高昂，重复监测主要限于每年一次的时间尺度。然而，管理沿海沉积物资源的影响是这样的，准确的，高时空分辨率的数据是必不可少的，以支持地貌的理解驾驶维修决策。高分辨率地形数据的定期交付将改变我们目前对大规模海滩动态的理解，通过提供沉积物移动高度的第一次~每日测量。与我们的CASE合作伙伴，佩文西海岸防御有限公司（见CASE合作伙伴部分），该项目将开发一种新颖的，小外形，移动的激光扫描传感器（MLS）将被集成到无人机（UAV）中。该传感器和平台将能够在几个小时内沿着佩文西海岸收集适当的高分辨率（高垂直精度和每平方米100个点）数据，提高对沉积动力学的理解。在船上的图像处理将使功能的发展（如木瓦吐）跟踪在努力开发的“智能”系统，可以监测动态环境features.以及直接影响的监测大面积的动态地形的研究，这将是非常感兴趣的那些开发的感觉和避免系统完全自主飞行和智能功能跟踪的进一步完善。

Despite the importance placed upon our coastal environments in terms of providing inland protection from marine flooding and the habitat and economic value associated with them, due to high costs, repeat monitoring is largely limited to annual timescales. Yet the implications for managing the coastal sediment resource are such that accurate, high spatio-temporal resolution data is essential to underpin the geomorphological understanding driving maintenance decisions. The regular delivery of high resolution topographic data will transform our current understanding of large scale beach dynamics, by providing the very first ~daily measurements of high the sediment is moving around.In conjunction with our CASE partner, Pevensey Coastal Defence Ltd (see CASE partner section), this project will develop a novel, small form factor, mobile laser scanning sensor (MLS) which will be integrated into an UAV (Unmanned Aerial Vehicle). The sensor and platform will be able to collect suitably high resolution (high vertical accuracy and 100s points per m2) data along the Pevensey coast in a matter of hours, improving the understanding of sediment dynamics. On board image processing will enable the development of feature (e.g. shingle spits) tracking in an effort to develop 'smart' systems which can monitor dynamic environmental features.As well as the immediate impact of this research for monitoring large areas of dynamic land forms, it will be of great interest to those developing sense and avoid systems for full autonomous flights and in further refinement of smart feature tracking.