[1]刘新侠,杨鑫宇,付春晓,等.基于无人机多光谱估算冬小麦作物系数[J].江苏农业学报,2025,(06):1169-1178.[doi:doi:10.3969/j.issn.1000-4440.2025.06.013]
　LIU Xinxia,YANG Xinyu,FU Chunxiao,et al.Crop coefficient estimation of winter wheat based on unmanned aerial vehicle (UAV) multispectral data[J].,2025,(06):1169-1178.[doi:doi:10.3969/j.issn.1000-4440.2025.06.013]
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基于无人机多光谱估算冬小麦作物系数()
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江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2025年06期
页码:
1169-1178
栏目:
农业信息工程
出版日期:
2025-06-30

文章信息/Info

Title:
Crop coefficient estimation of winter wheat based on unmanned aerial vehicle (UAV) multispectral data
作者:
刘新侠1; 2; 杨鑫宇1; 2; 付春晓1; 承达瑜3; 于锐1; 2
(1.河北工程大学水利水电学院,河北邯郸056038；2.河北省智慧水利重点实验室,河北邯郸056038；3.河北工程大学矿业与测绘工程学院,河北邯郸056038)
Author(s):
LIU Xinxia1; 2; YANG Xinyu1; 2; FU Chunxiao1; CHENG Dayu3; YU Rui1; 2
(1.School of Water Conservancy and Hydroelectric Power, Hebei University of Engineering, Handan 056038， China;2.Hebei Key Laboratory of Intelligent Water Conservancy, Handan 056038， China;3.School of Mining and Geomatics Engineering, Hebei University of Engineering, Handan 056038， China)
关键词:
冬小麦; 无人机; 多光谱; 作物系数; 植被指数
Keywords:
winter wheat; unmanned aerial vehicle (UAV); multispectral; crop coefficient; vegetation index
分类号:
S127
DOI:
doi:10.3969/j.issn.1000-4440.2025.06.013
文献标志码:
A
摘要:
作物系数(Kc)是用于衡量植物对水分需求的一个重要参数,高效、及时地获取Kc对优化灌溉管理,提升农业用水效率具有重要意义。本研究以冬小麦为研究对象,利用联合国粮食及农业组织（FAO）推荐的双作物系数法,并结合观测得到的冬小麦长势参数(株高、叶面积指数),进行冬小麦作物系数的估算；同时利用无人机遥感获取多光谱的冬小麦影像,分析不同时期(拔节期、抽穗期和开花期)8种常用植被指数（归一化植被指数、重归一化植被指数、土壤调节植被指数、转化叶绿素吸收反射指数、增强型植被指数、绿色归一化植被指数、比值植被指数、差值植被指数）与FAO推荐方法得到的作物系数的相关性；根据决定系数(R2)选取适宜的植被指数建立作物系数估算模型,并与FAO推荐方法估算的作物系数进行比较。结果表明,拔节期至开花期,归一化植被指数(NDVI)、重归一化植被指数(RDVI)、土壤调节植被指数(SAVI)和转化叶绿素吸收反射指数(TCARI)等4种植被指数与Kc的相关性较好。基于TCARI/RDVI建立的冬小麦作物系数估算模型精度更高,拔节期、抽穗期和开花期估算模型的均方根差(RMSE)分别为0.14、0.12和0.15,拔节期、抽穗期和开花期的模型性能系数(EF)分别为0.66、0.88和0.71。利用估算模型生成的作物系数分布图可为冬小麦的合理灌溉提供科学依据。
Abstract:
Crop coefficient (Kc) is a critical parameter for quantifying crop water requirements, and its efficient and timely acquisition is essential for optimizing irrigation management and improving agricultural water use efficiency. In this study, winter wheat was taken as the research object, and the crop coefficient of winter wheat was estimated by using the dual crop coefficient approach recommended by the Food and Agriculture Organization of the United Nations (FAO), combined with the observed winter wheat growth parameters (plant height, leaf area index). The correlation between eight common vegetation indices (normalized difference vegetation index, renormalized difference vegetation index, soil-adjusted vegetation index, transformed chlorophyll absorption in reflectance index, enhanced vegetation index, green normalized difference vegetation index, ratio vegetation index, difference vegetation index) and Kc derived from FAO-recommended methods was analyzed at different growth stages (jointing, heading, and flowering periods) using multispectral imagery acquired through unmanned aerial vehicle (UAV) remote sensing. According to the coefficient of determination (R2), the appropriate vegetation index was selected to establish the crop coefficient estimation model. Crop coefficient values estimated by the model were compared with those obtained by the FAO-recommended algorithm. The results showed that the normalized difference vegetation index (NDVI), renormalized difference vegetation index (RDVI), soil-adjusted vegetation index (SAVI) and transformed chlorophyll absorption in reflectance index (TCARI) had a good correlation with Kc during jointing stage to flowering stage. The crop coefficient estimation model of winter wheat based on TCARI/RDVI was more accurate. The root mean square errors (RMSE) at jointing stage, heading stage and flowering stage were 0.14, 0.12 and 0.15, respectively. The model efficiency coefficients (EF) at jointing stage, heading stage and flowering stage were 0.66, 0.88 and 0.71, respectively. The crop coefficient distribution map generated by this model can provide a scientific basis for reasonable irrigation of winter wheat.

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备注/Memo

备注/Memo:
收稿日期：2024-07-29基金项目：河北省重大科技成果转化专项(22287401Z);国家自然科学基金项目(42071246)作者简介：刘新侠(1978-),女,河北沧州人,博士,教授,研究方向为水资源规划与管理。(E-mail)55962967@qq.com通讯作者：付春晓,(E-mail)chunxiao999999@163.com
更新日期/Last Update: 2025-07-16