Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps
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 correlat...
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MDPI AG
2025-05-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/15/6/1329 |
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| author | Dorijan Radočaj Ivan Plaščak Mladen Jurišić |
| author_facet | Dorijan Radočaj Ivan Plaščak Mladen Jurišić |
| author_sort | Dorijan Radočaj |
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| description | 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 (NDVI<sub>3RE</sub>) 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 NDVI<sub>3RE</sub> 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. |
| format | Article |
| id | doaj-art-bcc9482063d940ad8283bd87f6ec0518 |
| institution | Kabale University |
| issn | 2073-4395 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
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| series | Agronomy |
| spelling | doaj-art-bcc9482063d940ad8283bd87f6ec05182025-08-20T03:24:29ZengMDPI AGAgronomy2073-43952025-05-01156132910.3390/agronomy15061329Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield MapsDorijan Radočaj0Ivan Plaščak1Mladen Jurišić2Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, CroatiaFaculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, CroatiaFaculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, CroatiaTo 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 (NDVI<sub>3RE</sub>) 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 NDVI<sub>3RE</sub> 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.https://www.mdpi.com/2073-4395/15/6/1329combine harvesterThree Red-Edge Vegetation Indexsenescencephenology analysis |
| spellingShingle | Dorijan Radočaj Ivan Plaščak Mladen Jurišić Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps Agronomy combine harvester Three Red-Edge Vegetation Index senescence phenology analysis |
| title | Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps |
| title_full | Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps |
| title_fullStr | Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps |
| title_full_unstemmed | Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps |
| title_short | Fusion of Sentinel-2 Phenology Metrics and Saturation-Resistant Vegetation Indices for Improved Correlation with Maize Yield Maps |
| title_sort | fusion of sentinel 2 phenology metrics and saturation resistant vegetation indices for improved correlation with maize yield maps |
| topic | combine harvester Three Red-Edge Vegetation Index senescence phenology analysis |
| url | https://www.mdpi.com/2073-4395/15/6/1329 |
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