A Phenology-Based Evaluation of the Optimal Proxy for Cropland Suitability Based on Crop Yield Correlations from Sentinel-2 Image Time-Series

Dorijan Radočaj () and Mladen Jurišić
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Dorijan Radočaj: Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia
Mladen Jurišić: Faculty of Agrobiotechnical Sciences Osijek, Josip Juraj Strossmayer University of Osijek, Vladimira Preloga 1, 31000 Osijek, Croatia

Agriculture, 2025, vol. 15, issue 8, 1-14

Abstract: Cropland suitability calculations quantify natural suitability according to abiotic conditions, thus making them crucial for sustainable land management. However, since ground-truth yield data are extremely scarce, there is a need to improve knowledge on the optimal proxy metric from satellite imagery, which represents cropland suitability and enables global applicability. This study evaluated four frequently used vegetation indices from Sentinel-2 image time-series (normalized difference vegetation index, enhanced vegetation index, enhanced vegetation index 2, and wide dynamic range vegetation index) with three phenology metrics for correlation analysis with maize and soybean yield. Four years (2019–2022) in two study areas (Iowa and Illinois) were utilized in this research, and 1000 ground-truth crop yield samples were created for each combination of study year and area. The combination of wide dynamic range vegetation index (WDRVI) and maximum vegetation index phenology metric (MAX) was an optimal proxy for maize yield prediction, while enhanced vegetation index 2 (EVI2) and MAX produced the highest correlation for soybean, producing Pearson’s correlation coefficient means of 0.506 and 0.519, respectively. This study improved our knowledge of the optimal proxy metric for cropland suitability by combining multiple large ground-truth crop yield datasets with 30 m spatial resolution satellite imagery, which can be further improved with the use of novel vegetation indices with improved resistance to a saturation effect.

Keywords: wide dynamic range vegetation index; enhanced vegetation index 2; phenology modeling; correlation analysis; maize yield; soybean yield (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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