Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps

• Published in: Agronomy (Basel) Vol. 15; no. 6; p. 1329
• Main Authors: Radočaj, Dorijan, Plaščak, Ivan, Jurišić, Mladen
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2025
• Subjects: Agricultural equipment; Agricultural production; Agriculture; Chlorophyll; combine harvester; Combine harvesters; Corn; Correlation coefficient; Correlation coefficients; Crop yield; Crops; Food security; Loam soils; Phenology; phenology analysis; Physiology; Remote sensing; Senescence; Three Red-Edge Vegetation Index; Vegetation; Vegetation index; Croatia; Germany
• ISSN: 2073-4395; 2073-4395
• DOI: 10.3390/agronomy15061329

To authors’ knowledge, no previous studies thoroughly focused on determining the single optimal combination of vegetation index and phenology metric for maize yield assessment based on ground truth yield map from combine harvester. Therefore, the main objective of this study was to evaluate correlation between all combinations of eight vegetation indices and seven phenology metrics with maize yield. A specific focus was put on evaluating saturation-resistant vegetation indices and utilizing Sentinel-2 images, including novel vegetation indices such as Inverted Difference Vegetation Index (IDVI), Three Red-Edge Vegetation Index (NDVI3RE) and Plant Phenology Index (PPI). Twelve parcels located in Eastern Croatia were observed during 2022 and 2023, with a total area of ground truth data of 67.61 ha. The analysis of vegetation indices and phenology metrics indicated varying strengths of correlation with maize yield, with the combination of NDVI3RE and Senescence producing the highest Pearson correlation coefficient (0.506). However, the relationship of optimal combination of vegetation index and phenology metric with maize yield based on combined dataset which included parcels 1–12 on individual parcels varied notably and is likely indicative of interannual weather variations. Overall, the reduced saturation effect in red-edge-based index suggests that it may be more suitable for maize yield prediction.