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Agronomy
Volume 15
Issue 2
10.3390/agronomy15020406
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Article

Study on the Automatic Selection of Sensitive Hyperspectral Bands for Rice Nitrogen Retrieval Based on a Maximum Inscribed Rectangle

by
Yaobing Fan
1,
Youxing Chen
1,
Shangrong Wu
2,3,*,
Wei Kuang
4,
Jieyang Tan
5,
Yan Zha
2,3,
Baohua Fang
4 and
Peng Yang
2,3
1
School of Information and Communication Engineering, North University of China, Taiyuan 030051, China
2
State Key Laboratory of Efficient Utilization of Arable Land in China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
3
Key Laboratory of Agricultural Remote Sensing, Ministry of Agriculture and Rural Affairs, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
4
Hunan Rice Research Institute, Hunan Academy of Agricultural Sciences, Changsha 410125, China
5
Institute of Agricultural Economics and Regional Planning, Hunan Academy of Agricultural Sciences, Changsha 410125, China
*
Author to whom correspondence should be addressed.
Agronomy 2025, 15(2), 406; https://doi.org/10.3390/agronomy15020406
Submission received: 30 December 2024 / Revised: 1 February 2025 / Accepted: 4 February 2025 / Published: 5 February 2025
(This article belongs to the Section Precision and Digital Agriculture)
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Abstract

Most existing studies on the optimal bandwidth selection for plant nitrogen are based on the sensitive band center, and determine the optimal bands by manually adjusting the bandwidth, step by step. However, this method has a high level of manual involvement and is time-consuming. This paper focused on rice as the research subject, based on determining the center of the rice plant nitrogen-sensitive bands and the maximum region Ω of the fitted R2 between the narrow-band vegetation indices (N-VIs) and plant nitrogen, a method was proposed to automatically select the optimal bandwidth by constructing inscribed rectangles. UAV hyperspectral images were used to carry out the spatial inversion and precision verification of the rice plant nitrogen, based on the optimal width of sensitive bands. The results revealed that the optimal bandwidths, automatically selected on the basis of N-VIs via the inscribed rectangle method, achieved good results in the remote sensing inversion of plant nitrogen at the rice jointing and flowering stages, with the coefficient of determination (R2) greater than 0.49 to satisfy the requirement of significance (p < 0.05) and the normalized root mean square error (NRMSE) and mean relative error (MRE) of less than 13%. These findings indicate that the method of crop plant nitrogen inversion band center screening and automatic search for the optimal bandwidth in this study has certain feasibility, which provides a new idea for screening the optimal bandwidth on the basis of the sensitive band center and provides technical support for the design of satellite band parameters.
Keywords: unmanned aerial vehicle (UAV); hyperspectral; nitrogen retrieval; bandwidth; rice unmanned aerial vehicle (UAV); hyperspectral; nitrogen retrieval; bandwidth; rice

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MDPI and ACS Style

Fan, Y.; Chen, Y.; Wu, S.; Kuang, W.; Tan, J.; Zha, Y.; Fang, B.; Yang, P. Study on the Automatic Selection of Sensitive Hyperspectral Bands for Rice Nitrogen Retrieval Based on a Maximum Inscribed Rectangle. Agronomy 2025, 15, 406. https://doi.org/10.3390/agronomy15020406

AMA Style

Fan Y, Chen Y, Wu S, Kuang W, Tan J, Zha Y, Fang B, Yang P. Study on the Automatic Selection of Sensitive Hyperspectral Bands for Rice Nitrogen Retrieval Based on a Maximum Inscribed Rectangle. Agronomy. 2025; 15(2):406. https://doi.org/10.3390/agronomy15020406

Chicago/Turabian Style

Fan, Yaobing, Youxing Chen, Shangrong Wu, Wei Kuang, Jieyang Tan, Yan Zha, Baohua Fang, and Peng Yang. 2025. "Study on the Automatic Selection of Sensitive Hyperspectral Bands for Rice Nitrogen Retrieval Based on a Maximum Inscribed Rectangle" Agronomy 15, no. 2: 406. https://doi.org/10.3390/agronomy15020406

APA Style

Fan, Y., Chen, Y., Wu, S., Kuang, W., Tan, J., Zha, Y., Fang, B., & Yang, P. (2025). Study on the Automatic Selection of Sensitive Hyperspectral Bands for Rice Nitrogen Retrieval Based on a Maximum Inscribed Rectangle. Agronomy, 15(2), 406. https://doi.org/10.3390/agronomy15020406

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