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ABSTRACT
Detecting the field maturity moment for maize (Zea mays L.) crop represents a relevant point to estimate its optimal harvest time. Knowing the optimal harvest time (defined by grain moisture content) at the end of the crop season is a major concern for maize farmers, as it could lead to substantial economic losses if not harvested on time. For this crop, optimal harvest time usually occurs 3–4 weeks after field maturity, depending on weather conditions. Therefore, this study focused on the interferometric coherence time-series analysis at the end of the maize crop season, to indirectly estimate the field maturity. For such purpose, a coherence object-based change detection method using Sentinel-1 SAR images was developed aiming to estimate the potential field maturity time. These estimations were assessed using an independent data set of field maturity dates obtained through field inspection and crop growth modelling. The technique was tested over 52 fields in the northwest region of Kansas, United States, with a detection rate of 80%, and a field maturity estimation error of 10 days (assessed with the root mean square error). The proposed method constitutes a promising approach to estimating the maize field maturity in near-real time, determining the field harvest readiness, and developing a decision support tool to assist farmers in prioritizing the allocation of fields at harvest time.
Acknowledgements
We thank Javier Fernandez for manuscript review.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
Sentinel-1 images used in this study are available in the Copernicus Open Access Hub. Field polygons employed in the method calibration are available from the corresponding author, Amherdt S., upon reasonable request. Location and maturity time of the maize fields that support the findings in this study are available in the Supplementary material (Table S2).
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/01431161.2023.2184214