卫星数据+专用视觉Transformer的甜菜早期产量预测（Sentinel-2影像应用）
利用Sentinel-2卫星影像和专用视觉Transformer进行甜菜早期产量预测，方法新颖，有实际应用价值，但发表于8天前，时效性较低。
基于Sentinel-2光学影像的早期甜菜产量预测研究。通过紧耦合领域知识与机器学习，使用极小Vision Transformer patch size与全部Sentinel-2谱段，提升了模型表现。研究通过调整训练设置与基于排名的低产田检测方法，能在生长周期早期识别出大量低产田，为精准农业田间管理提供早期决策依据。
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Computer Science > Computer Vision and Pattern Recognition
arXiv:2607.17661 (cs)
[Submitted on 20 Jul 2026]
Title:Early Yield Prediction for Sugar Beet Fields using Satellite Data -- Learnings from Specialized Vision Transformers
Authors:Philipp Vaeth, Bhumika Laxman Sadbhave, Denise Dejon, Gunther Schorcht, Magda Gregorova
View a PDF of the paper titled Early Yield Prediction for Sugar Beet Fields using Satellite Data -- Learnings from Specialized Vision Transformers, by Philipp Vaeth and 4 other authors
Abstract:Remote sensing has become an increasingly valuable tool for agricultural monitoring, particularly through the use of publicly available satellite imagery. However, effectively integrating domain knowledge into machine learning methods remains challenging. This study presents a real-world example of early sugar beet harvest yield forecasting from purely optical Sentinel-2 imagery, demonstrating how a tight integration of domain knowledge and machine learning can lead to synergistic gains. We empirically find that using very small vision transformer patch sizes and all available Sentinel-2 spectral bands improves our model despite being uncommon design choices in the domain. As a practical contribution, we were able to identify a large fraction of low-yield fields in a different year early on in the growth cycle through a modified training setup and a ranking-based detection of underperforming fields.
Subjects:Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG)
Cite as:arXiv:2607.17661 [cs.CV]
(or arXiv:2607.17661v1 [cs.CV] for this version)
https://doi.org/10.48550/arXiv.2607.17661
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arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Philipp Vaeth [view email]
[v1] Mon, 20 Jul 2026 08:11:07 UTC (4,067 KB)
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View a PDF of the paper titled Early Yield Prediction for Sugar Beet Fields using Satellite Data -- Learnings from Specialized Vision Transformers, by Philipp Vaeth and 4 other authors
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