Abstract Vegetation indices (VIs), such as normalized difference vegetation index (NDVI), are widely used to assess nitrogen (N) status in crop systems and are gaining interest in turfgrass management. However, most studies have been conducted in controlled settings, and their relevance under real‐world golf course conditions remains unclear. This study evaluated spatial relationships between VIs and turfgrass tissue N on sand‐capped fairways and explored how organic layer thickness, volumetric water content (VWC), and penetration resistance influenced those relationships. Data were collected in spring 2021 from four fairways, two hybrid bermudagrass and two zoysiagrass, at The Club at Carlton Woods in Houston, Texas. Multispectral unmanned aerial vehicle (UAV) imagery and ground‐based data from the Toro Precision Sense 6000 were used alongside tissue and soil samples collected on a georeferenced 8.5 × 8.5 m grid. Spatial data were analyzed using correlation analysis and kriged maps to visualize variability across fairways. The UAV‐based VIs were strongly interrelated ( r = 0.54–0.93) and correlated with ground‐based NDVI ( r = 0.41–0.84) but showed weak or no correlation with tissue N ( r = −0.27 to 0.25). In contrast, VIs were more closely related to VWC ( r = 0.44–0.74) and organic layer thickness ( r = 0.20–0.53), especially in zoysiagrass. These findings challenge assumptions from plot‐based studies and highlight that environmental and management variability affect remote sensing reliability. Further research should explore whether integrating VIs with plant and soil data into predictive models or machine learning frameworks could improve monitoring and guide N‐related decisions in sand‐capped systems.
Sapkota et al. (Thu,) studied this question.