Introduction: Traditional forest tree breeding involves a lengthy process of crossing, testing, and selection, known as the breeding cycle, which requires significant logistical efforts and faces limitations like experimental trial sizes and the precision of measurements. The advent of genomics introduced the possibility of developing molecular tools to accurately identify the genome shared among individuals, forming the basis of the Breeding without Breeding (BWB) approach. This method aims to bypass artificial mating but has been limited by the need for structured open-pollinated trials. Recent advances in remote sensing technology now offer a way to phenotype trees accurately and extensively, considering environmental factors and enabling the assessment of various tree attributes at a landscape scale.

Methods In Sweden, a significant portion of commercial Norway spruce forests are regenerated from improved progenies, making it an ideal setting to combine molecular pedigree reconstruction with remote sensing. This integration forms the basis of Landscape Breeding, a novel strategy aimed at enhancing genetic diversity and improving seed orchards by selecting superior trees directly from commercial forests, thereby expediting forest enhancement for sustainable biomass production.

Results and Conclusion We developed a method that merges genetic, genomic, and remote sensing data to scan Norway spruce stands, covering a clonal archive, a progeny trial, and commercial forests. Preliminary data processing is underway, with remote sensing data being used for genetic analysis. This method demonstrates the efficacy of remote sensing in evaluating tree genetics on a landscape level, marking a significant advancement in forest breeding strategies.