Bridging scales in remote sensing of vegetation stress

该项目旨在开发可操作的升级算法，以从星载任务对地球的光学观测中绘制植被应力指标。这些方法使用计算机辐射转移模型和无人驾驶飞机系统，并将为在广阔和难以进入的澳大利亚和南极地区定期进行植物健康卫星监测铺平道路。更准确和及时的早期应激症状遥感地图将提供干旱、疾病和害虫的早期预警，告诉人们何时何地保护野生自然系统的生态功能，并有助于维持甚至增加农业粮食生产。

This project aims to develop operational upscaling algorithms to map vegetation stress indicators from space-borne missions’ optical observations of the Earth. These approaches use computer radiative transfer models and unmanned aircraft systems called drones, and will pave the way for regular satellite monitoring of plant health in extensive and inaccessible Australian and Antarctic areas. More accurate and timely remote sensing maps of early stress symptoms will provide early warnings of droughts, diseases and pests, tell when and where to protect ecological functions of wild natural systems, and help to sustain or even increase agricultural food production.