Plants express their genetic potential through traits shaped by both environment and management, and modern sensing technologies now allow these traits to be captured at scale. Advances in drones, satellites, hyperspectral imaging, thermal cameras, and LiDAR have transformed high-throughput phenotyping from a labour-intensive process into one that is rapid, non-destructive, and spatially extensive. These sensing platforms generate spectral phenotypes that integrate structural, physiological, and temporal plant traits, enabling researchers to link genotype, phenotype, and environment in real-world conditions. Applications extend across domains: crop breeding and precision agriculture, post-mining land rehabilitation, and biodiversity monitoring. Examples include detecting stress responses, separating native vegetation from invasive species, and linking spectral traits to underlying genetic variation. To frame these advances, this chapter reviews current advances, highlights challenges in data interpretation and scaling, and proposes an Eco-Physical-Cyber framework to guide future research and practice in connecting genes to landscapes.