Sustainable wheat production is challenged by climate change events such as drought and heat stress. Stay-green trait is an important characteristic for stability under climate severities. Phenotyping of complex traits is increasingly perceived as a bottleneck due to the elevated costs, labour, time and resources in large field conditions. Unmanned aerial vehicle (UAV) based phenotyping platforms using RGB imagery can facilitate the repeated non-destructive measurements of above canopy traits cost-effectively.  Here, we describe the use of UAV to quantify stay-green chrematistic in wheat using vegetation indices derived from RGB imagery. We detected stay-green traits with high heritability, as well as its impact on grain yield (GY), in a recombinant inbred lines (RIL) population of 146 lines derived from Zhongmai 175/Lunxuan 987 cultivars at various growth stages in the field. Selecting for stay-green genotypes using UAV-based traits was more effective than ground based-using traits. We identified nine quantitative trait loci (QTL) for stay-green related traits using a 50K single-nucleotide polymorphism array. QTLs for UAV based traits from RGB imaging and ground traits were mapped on chromosomes 1B, 2B, 3A and 4B. This integrated approach allowed us to identify an important, stay-green related locus on chromosome 4B that showed phenotypic variation up to 29.6% for both UAV and ground traits at late grain filling stage. Four QTLs on chromosomes 1B, 3A and 4B were validated for stay-green by developing kompetitive allele-specific PCR markers. Our results suggest that UAV-based RGB imagery is advantageous for temporal assessment of the genetics underlying for stay-green in wheat.