Leveraging Existing Infrastructure and Multisource Data for Enhanced Vegetation Phenology Monitoring

该项目由地理空间系统博士培训中心开展，重点是通过现有的交通摄像头网络、行车记录仪、无人机和遥感数据改善对植被物候（研究植物季节性生命周期事件的时间）的监测。目的是评估和增强这些基础设施和历史数据在生态观测方面的能力，特别是在捕捉物候变化方面的能力。该研究的一个组成部分包括改进图像处理和机器学习算法，以提取准确的物候指标，并将这些数据与气象和卫星图像相结合，以提供沿交通网络的植被物候的整体视图。该项目代表了一种创新的生态监测方法，利用地理空间技术来加强对不断变化的环境景观中植被物候的理解和管理。

This project, conducted within the Centre for Doctoral Training in Geospatial Systems, focuses on improving the monitoring of vegetation phenology (the study of the timing of seasonal life cycle events in plants) through existing traffic camera networks, dashcams, drones, and remote sensing data. The aim is to assess and augment the capability of these infrastructures and historical data in ecological observation, particularly in capturing phenological changes.An integral part of the research involves refining image processing and machine learning algorithms to extract accurate phenological metrics and integrating this data with meteorological and satellite imagery to offer a holistic view of vegetation phenology along transportation networks.This project represents an innovative approach to ecological monitoring, utilising geospatial technologies to enhance the understanding and management of vegetation phenology in changing environmental landscapes.