Global agricultural production is required to double by 2050 to meet the demands of an increasing population and the challenges of a changing climate. Changing climatic conditions, including increasing temperatures, more variable precipitation, and drought are likely to put pressure on maintaining both high crop yields and a steady supply of food. On the other hand, assuming other factors are not limiting, rising atmospheric CO2 levels may lead to increased crop productivity, as the increased availability of carbon dioxide can promote enhanced rates of plant photosynthesis. The varying abilities of different crops or cultivars to adapt to water, temperature or nutrient pressures signifies the inherent resilience of a given agricultural system, and the likelihood and the degree to which they will be impacted by climate change. Understanding how current and future plant growth conditions affect crop yield is a major priority for ensuring food security, for adapting crop selection and management strategies and for guiding crop breeding programmes. The key challenge here is linking plant behaviour that can be measured at the leaf-level in the laboratory, to plant behaviour at the national or global scale, and predicting future behaviour under forecasted climate conditions. As environmental drivers operate and interact at multiple temporal and spatial scales, addressing this challenge will require transforming how we understand, monitor and predict plant responses to stress. Observations from satellites have revolutionised spatial ecology in recent years; making it possible to monitor ecological trends over large spatial scales, and to scale from the plant to the globe. Increasingly sophisticated instruments and techniques allow scientists to examine changing vegetation trends in response to climate change from satellites at unprecedented levels of accuracy. These advances have been made possible by sensor developments, an increasing archive of legacy satellite data, and new and emerging techniques such as solar-induced chlorophyll fluorescence, which has been shown to be closely related to plant productivity. Whilst still in its infancy, solar-induced chlorophyll fluorescence has shown potential to remotely monitor crop growth, using drones through to satellites. However, these remote sensing techniques must first be underpinned by a process-based understanding of the connections between the remote sensing signal and plant characteristics. In this research, controlled laboratory experiments will be used to understand how plant stress manifests in changes to the leaf biochemical and structural properties, and in turn, how optical reflectance signatures, can be used to measure these changes. These optical markers will then be used to 'scale up' our observations, first using drone technology at the field scale, and then and at national and global scales using satellite data. This remote sensing data on crop health will be used within sophisticated biosphere models to predict plant performance under current conditions and forecasted future conditions. These approaches in combination will provide a technological basis for a complete picture at different scales, to fully exploit the resources available for crop improvement. The overarching goal of the research is to assess the ability of nationally and globally important agricultural crops to maintain their growth and performance under different environmental stresses. This research will deploy a cutting-edge, cross-disciplinary approach using controlled growth chambers, novel remote sensing techniques and plant science methods to scale from the leaf to the globe, and provide a step-change understanding in the future pressures that crops may face in light of a changing climate and their underlying resilience.