Abstract Agroforestry systems (AFS) offer a promising strategy to address environmental challenges while supporting rising food demands. However, the complex interactions between trees and crops complicate research, particularly regarding their effects on crop yields. This study presents a methodological approach using multispectral unmanned aerial system (UAS) data to investigate a maize-cultivated alley cropping system in eastern Germany as a case study. Growth parameters, namely the Normalized Difference Vegetation Index (NDVI) and plant height, were derived as proxies for yield and analyzed in relation to the distance from tree stripes. Additionally, direction-dependent regression analyses were conducted to assess whether spatial variations in the field could be attributed to the trees. Two distinct patterns emerged: first, a pronounced increase in NDVI was observed at close proximity to the trees, correlated with tree height and schematically illustrated for two representative tree stripes; second, at greater distances, fluctuations in NDVI were associated with the trees but lacked consistent directional trends. Considerable inconsistencies were also observed in plant height variations. The discussion highlights potential drivers of the close-range NDVI increase, the applicability of UAS for AFS research, and limitations in generalizing findings from a single case study. Overall, the results demonstrate that tree effects on crop growth and vitality are detectable but marginal in terms of their influence on maize yields at this site, while showcasing the utility of UAS-based approaches for field-scale analysis of AFS.
Kunzmann et al. (Sat,) studied this question.
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