Towards Autonomy for Unoccupied Aerial Systems in UN SDGs

该项目将使用来自世界各地的一些森林压力案例研究(例如，使用无人驾驶航空系统(UAS)捕获的藤本植物感染)，以利用人工智能在远程捕获数据上的力量来检测压力的压力源。然后，将利用高光谱和/或超空间和/或超时间遥感数据的力量，开发用于森林监测的自主遥感。将在更广泛的联合国全球目标的背景下探讨从林业中吸取的经验教训。

This project will use a number of case studies of forest stress (e.g., liana infestation captured using unoccupied aerial systems (UAS)) from around the World to exploit the power of AI on remotely captured data to detect the source of stress of stress. The power of hyperspectral and/or hyperspatial and/or hypertemporal remotely captured data will then be used to develop autonomous remote sensing for forest monitoring. The learnings from forestry will be explored in the context of the wider UN Global Goals.