Optimization of morphological and developmental characteristics is critical to maximize the yield potential in crop varieties. Plant height is a key agronomic trait that is an important breeding target in many crops due to its association with biomass and grain yield. However, the slow and static nature of the conventional measurements is a major bottleneck to elucidate the genetic basis of the temporal dynamics of plant height in field experiments. We estimated canopy height measurements using unmanned aerial systems (UAS) based digital elevation models for 546 elite spring wheat breeding lines grown in normal and early planting field experiments. Plant height estimates were extracted for 2400 plots at 34 timepoints using digital elevation models from UAS imaging. A logistic growth function was fit to derive genotype specific growth parameters, namely: upper asymptote (final height), slope (growth rate), and inflection point (time of maximum growth rate). These growth parameters exhibited very high heritability (0.82-0.93) in the two studied environments. By leveraging these highly heritable phenotypic measurements, we found 35 associations to genetic markers in the population. Multiple coincident signals at known developmental genes were observed for growth rate, heading and maturity dates, as well as agronomic traits, suggesting a significant genetic interdependence of morphological and developmental processes in wheat. Significant physiological tradeoffs associated with faster crop growth in two environments were also uncovered. Through integration of dynamic height measurements with physiology and genomics, our study demonstrates the considerable power of field high-throughput phenotyping to dissect the genetic and physiological underpinnings of growth components. This supports the importance of large-scale, field-based phenomics to uncover the biological underpinnings of complex plant developmental traits directly in breeding programs.