干旱区研究 ›› 2024, Vol. 41 ›› Issue (6): 1069-1078.doi: 10.13866/j.azr.2024.06.15
孙法福1,2,3(), 赖宁1,2, 耿庆龙1,2, 李永福1,2, 吕彩霞1,2, 信会男1,2, 李娜1,2, 陈署晃1,2(
)
收稿日期:
2023-12-01
修回日期:
2024-04-20
出版日期:
2024-06-15
发布日期:
2024-07-03
通讯作者:
陈署晃. E-mail: chensh66@163.com
作者简介:
孙法福(1997-),男,硕士研究生,主要从事农业遥感相关研究. E-mail: 18253289263@163.com
基金资助:
SUN Fafu1,2,3(), LAI Ning1,2, GENG Qinglong1,2, LI Yongfu1,2, LV Caixia1,2, XIN Huinan1,2, LI Na1,2, CHEN Shuhuang1,2(
)
Received:
2023-12-01
Revised:
2024-04-20
Online:
2024-06-15
Published:
2024-07-03
摘要:
叶片氮浓度(LNC)是反应作物光合作用、营养状况和长势的重要指标,为精准高效地估测不同生育期冬小麦叶片氮浓度,以新冬22为研究对象,利用无人机搭载Pika L高光谱相机获取4个关键生育期冬小麦冠层反射率数据。基于波段优化算法和相关性分析筛选LNC敏感光谱指数,结合逐步回归、多元线性回归和偏最小二乘回归建立关键生育期冬小麦叶片氮浓度估测模型,并与单变量估测模型进行比较。结果表明:基于波段优化算法筛选的组合光谱指数与LNC的相关性优于传统植被指数,且达到极显著性相关;在单变量LNC估测模型中,组合光谱指数构建的模型精度优于传统植被指数,其中,扬花期差值光谱指数(DSI(R940、R968))建立的估测模型最好,R2为0.789;多变量估测模型精度均优于单变量估测模型,其中,基于偏最小二乘回归构建的LNC估算模型最好,孕穗期和扬花期拟合效果较优,模型决定系数均为0.923,均方根误差为0.082、0.084。本研究结果可以作为冬小麦LNC估测和长势监测的科学依据。
孙法福, 赖宁, 耿庆龙, 李永福, 吕彩霞, 信会男, 李娜, 陈署晃. 基于无人机高光谱影像的冬小麦叶片氮浓度遥感估测[J]. 干旱区研究, 2024, 41(6): 1069-1078.
SUN Fafu, LAI Ning, GENG Qinglong, LI Yongfu, LV Caixia, XIN Huinan, LI Na, CHEN Shuhuang. Estimation of nitrogen contentration in winter wheat leaves based on hyperspectral images of UAV[J]. Arid Zone Research, 2024, 41(6): 1069-1078.
表3
光谱指数及其定义"
光谱指数类型 | 光谱特征指数 | 定义 | 文献 |
---|---|---|---|
任意两波段光谱指数 | DSI(差值光谱指数) | Ri-Rj | 本研究 |
RSI(比值光谱指数) | Ri/Rj | 本研究 | |
NDSI(归一化光谱指数) | (Ri-Rj)/(Ri+Rj) | 本研究 | |
植被指数 | SR(简单比值指数) | R750/R706 | [ |
NDRE(红边归一化光谱指数) | (R790-R720)/(R790+R720) | [ | |
MTCI(陆地叶绿素指数) | (R750-R710)/(R710-R680) | [ | |
NDVI(归一化植被指数) | (R780-R670)/(R780+R670) | [ | |
GNDVI(绿色归一化植被指数) | (R750-R550)/(R750+R550) | [ | |
RNDRE(红边归一化植被指数) | (R750-R705)/(R750+R706) | [ | |
VOG(红边指数) | R742/R722 | [ | |
CIred-edge(红光叶绿素光谱指数) | (R780/R710)-1 | [ | |
CIgreen(绿光叶绿素光谱指数) | (R780/R550)-1 | [ | |
RVI(比值植被指数) | R790/R670 | [ |
表4
光谱指数入选波段与叶片氮浓度的相关性"
生育时期 | 光谱指数 | 相关系数 |
---|---|---|
拔节期 | DSI(R644、R688) | -0.864** |
RSI(R596、R692) | 0.836** | |
NDSI(R596、R692) | -0.837** | |
孕穗期 | DSI(R826、R790) | 0.858** |
RSI(R632、R620) | 0.863** | |
NDSI(R620、R632) | 0.863** | |
扬花期 | DSI(R940、R968) | 0.877** |
RSI(R494、R514) | 0.870** | |
NDSI(R514、R494) | 0.869** | |
灌浆期 | DSI(R914、R912) | 0.811** |
RSI(R444、R520) | 0.808** | |
NDSI(R444、R520) | -0.810 ** |
表5
不同生育时期单个光谱参数的小麦叶片氮浓度(LNC)估测模型"
光谱 指数 | 线性函数 | 二次函数 | 指数函数 | 幂函数 | |||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
A | B | C | D | A | B | C | D | A | B | C | D | A | B | C | D | ||||
SR | 0.530* | 0.538* | 0.549* | 0.476* | 0.531* | 0.636** | 0.567* | 0.578* | 0.523* | 0.548* | 0.581* | 0.546* | 0.519* | 0.508* | 0.598** | 0.616** | |||
NDRE | 0.504* | 0.560* | 0.585* | 0.533* | 0.509* | 0.650** | 0.585* | 0.575* | 0.504* | 0.572* | 0.613** | 0.622* | 0.483* | 0.537* | 0.604** | 0.660** | |||
MTCI | 0.541* | 0.553* | 0.583* | 0.507* | 0.543* | 0.583* | 0.592* | 0.595* | 0.538* | 0.570* | 0.605** | 0.579* | 0.520* | 0.538* | 0.619** | 0.656** | |||
NDVI | 0.476* | 0.360 | 0.476* | 0.356 | 0.507* | 0.571* | 0.492* | 0.429* | 0.478* | 0.362 | 0.525* | 0.401* | 0.457* | 0.353 | 0.521* | 0.423* | |||
GNDVI | 0.490* | 0.439* | 0.521* | 0.240 | 0.511* | 0.633** | 0.541* | 0.273 | 0.491* | 0.446* | 0.567* | 0.269 | 0.473* | 0.429* | 0.555* | 0.278 | |||
RNDRE | 0.510* | 0.468* | 0.556* | 0.549* | 0.529* | 0.633** | 0.562* | 0.572* | 0.511* | 0.479* | 0.597** | 0.643* | 0.484* | 0.453* | 0.586* | 0.665** | |||
VOG | 0.515* | 0.556* | 0.577* | 0.505* | 0.517* | 0.656** | 0.580* | 0.578* | 0.513* | 0.568* | 0.608* | 0.586* | 0.510* | 0.548* | 0.612** | 0.617** | |||
CIred-edge | 0.524* | 0.569* | 0.564* | 0.470* | 0.524* | 0.631** | 0.581* | 0.580* | 0.517* | 0.578* | 0.589* | 0.539* | 0.501* | 0.524* | 0.606** | 0.639** | |||
CIgreen | 0.506* | 0.561* | 0.530* | 0.429* | 0.506* | 0.652** | 0.564* | 0.560* | 0.499* | 0.563* | 0.562* | 0.491* | 0.491* | 0.503* | 0.584* | 0.587* | |||
RVI | 0.511* | 0.507* | 0.454* | 0.407* | 0.511* | 0.644** | 0.520* | 0.535* | 0.494* | 0.504* | 0.501* | 0.477* | 0.502* | 0.429* | 0.531* | 0.575* | |||
DSI | 0.747** | 0.737** | 0.769** | 0.657** | 0.752** | 0.739** | 0.770** | 0.705** | 0.777** | 0.701** | 0.757** | 0.652** | 0.777** | 0.689** | 0.789** | 0.736** | |||
RSI | 0.699** | 0.743** | 0.757** | 0.652** | 0.700** | 0.781** | 0.759** | 0.671** | 0.704** | 0.746** | 0.756** | 0.697** | 0.706** | 0.747** | 0.757** | 0.708** | |||
NDSI | 0.700** | 0.744** | 0.756** | 0.657** | 0.701** | 0.781** | 0.759** | 0.672** | 0.706** | 0.747** | 0.757** | 0.705** | 0.668** | 0.702** | 0.750** | 0.686** |
表6
不同生育时期多个光谱参数的小麦叶片氮浓度(LNC)估测模型"
生育期 | 模型类型 | 模型表达式 | R2 | RMSE | |
---|---|---|---|---|---|
拔节期 | 逐步回归 | y=4.941+328.631×DSI | 0.785** | 0.152 | |
多元线性回归 | y=5.237+1.643×SR-7.167×NDRE-0.371×MTCI-0.69×VOG+2.107×CIred-edge-1.298×CIgreen+416×DSI-12.857×NDSI | 0.810** | 0.148 | ||
偏最小二乘回归 | y=-439.214+2.537×SR-0.644×CIgreen-847.763×NDSI-4.84×NDRE-0.166×MTCI+534.02×DSI+441.385×RSI-1.491×CIred-edge+2.067×VOG | 0.827** | 0.125 | ||
孕穗期 | 逐步回归 | y=121.58×DSI+64.851×NDSI+0.676 | 0.886** | 0.146 | |
多元线性回归 | y=-25.266-3.528×SR-63.571×NDRE-0.808×MTCI+35.126×VOG+2.556×CIred-edge-0.299×CIgreen+120.277×DSI+69.302×NDSI | 0.915** | 0.088 | ||
偏最小二乘回归 | y=1989.584-3.786×SR-67.171×NDRE-1.078×MTCI+36.272×VOG+3.021×CIred-edge-0.287×CIgreen+135.439×DSI-2015.69×RSI-3856.162×NDSI | 0.923** | 0.082 | ||
扬花期 | 逐步回归 | y=-8.102+26.947×DSI+13.905×RSI-4.374×NDRE | 0.899** | 0.106 | |
多元线性回归 | y=-10.266+0.444×RS-5.814×NDRE-0.276×MTCI-0.45×CIred-edge+0.228×CIgreen-0.848×VOG+17.924×RSI+29.493×DSI | 0.916** | 0.086 | ||
偏最小二乘回归 | y=-20.042+0.476×SR-5.603×NDRE-0.309×MTCI-0.47×CIred-edge+0.226×CIgreen-0.814×VOG+15.656×NDSI+27.821×RSI+29.548×DSI | 0.923** | 0.084 | ||
灌浆期 | 逐步回归 | y=3.344+247.593×DSI-7.417×NDSI | 0.753** | 0.212 | |
多元线性回归 | y=-19.407+1.844×SR-35.582×NDRE+3.161×MTCI+22.083×VOG-5.733×CIred-edge-0.529×CIgreen+406.249×DSI-2.746×RSI-3.227×NDSI | 0.815** | 0.126 | ||
偏最小二乘回归 | y=1.952+1.646×SR-2.536×NDRE+2.848×MTCI+3.772×VOG-4.888×CIred-edge-0.74×CIgreen+0.327×DSI+0.565×RSI+0.591×NDSI | 0.862** | 0.125 |
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