Winter wheat phenology classification using stacking ensemble learning algorithm based on Sentinel-1A SAR images

Haoxin Duan; Huijin Yang; Jianhui Zhao; Ning Li

doi:10.1117/12.3020989

19 January 2024 Winter wheat phenology classification using stacking ensemble learning algorithm based on Sentinel-1A SAR images

Haoxin Duan, Huijin Yang, Jianhui Zhao, Ning Li

Author Affiliations +

Proceedings Volume 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023); 1298010 (2024) https://doi.org/10.1117/12.3020989
Event: Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 2023, Lianyungang, China

Abstract

Crop monitoring and phenology estimation based on the satellite systems have become an important research area due to high demand on crops. Synthetic Aperture Radar (SAR) is a kind of microwave remote sensing equipment, which has the advantage of all-weather and all-day, and can realize large-scale and periodic crop phenological monitoring. Besides, thanks to the high temporal resolution of new generation space-based sensors, it has been possible to monitor growth cycle of crops by classification algorithms. A stacking ensemble learning algorithm using time series Sentinel-1A SAR images for winter wheat phenology classification was proposed in this paper based on multiple machine learning models, including Random Forest (RF), Support Vector Machine (SVM), K-nearest Neighbor(K-NN), Naive Bayes (NB) and BP Neural Network (BP) models. The experimental results showed that, comparing with each single model, the stacking ensemble learning algorithm proposed in this paper had the optimal performance, with the highest overall recognition accuracy of 81.40%, demonstrating its effectiveness and application potential for winter wheat phenology identification.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Haoxin Duan, Huijin Yang, Jianhui Zhao, and Ning Li "Winter wheat phenology classification using stacking ensemble learning algorithm based on Sentinel-1A SAR images", Proc. SPIE 12980, Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023), 1298010 (19 January 2024); https://doi.org/10.1117/12.3020989

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