柑橘植株冠层氮素和光合色素含量近地遥感估测
Estimation of nitrogen and pigments content in citrus canopy by low-altitude remote sensing
- 2015年19卷第6期 页码:1007-1018
纸质出版日期: 2015
DOI: 10.11834/jrs.20155078
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纸质出版日期: 2015 ,
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[1]刘雪峰,吕强,何绍兰,易时来,谢让金,郑永强,胡德玉,汪志涛,邓烈.柑橘植株冠层氮素和光合色素含量近地遥感估测[J].遥感学报,2015,19(06):1007-1018.
LIU Xuefeng, LYU Qiang, HE Shaolan, et al. Estimation of nitrogen and pigments content in citrus canopy by low-altitude remote sensing[J]. Journal of Remote Sensing, 2015,19(6):1007-1018.
柑橘植株营养状况的遥感监测是实现果树轻简高效管理和优质丰产的重要手段
但迄今有关基于低空遥感信息的果树营养诊断研究鲜见报道。本文采用具有490 nm、550 nm、570 nm、671 nm、680 nm、700 nm、720 nm、800 nm、840 nm、900 nm、950 nm等11个波段光谱的八旋翼飞行器(UAV)载多光谱遥感系统
获取距地面100 m高度的哈姆林甜橙植株春季冠层近地遥感信息
对比分析基于多元散射校正(MSC)和标准正态变量(SNV)两种预处理光谱和原始光谱(OS)的偏最小二乘(PLS)、多元线性回归(MLR)、主成分回归(PCR)及最小二乘支持向量机(LS-SVM)等4种模型对冠层叶片氮素、叶绿素a、叶绿素b和类胡萝卜素含量预测精度的影响。结果显示
距地面100 m高度的多光谱信息
通过SNV光谱预处理和MLR建模对冠层叶片氮素、叶绿素a和叶绿素b含量的预测效果均较好
预测集相关系数(Rp)值分别达0.8036、0.8065和0.8107
预测均方根误差(RMSEP)值分别为0.1363、0.0427和0.0243;而在SNV光谱预处理基础上的LS-SVM建模对冠层类胡萝卜素含量预测效果更优
Rp值达到了0.8535
RMSEP值为0.0117。表明利用机载多光谱图像信息可实现对柑橘植株冠层全氮及叶绿素a、叶绿素b和类胡萝卜素含量的较好估算
为大规模柑橘园植株冠层营养状况的精准和高效监测提供了一条新途径。
Remote measurement and diagnosis of the plants nutritional status is an important means for efficient easily and simple management system
and high-yield and high quality cultivation. So far
there is not yet much research on the nutrition diagnostic of fruit trees through low-altitude remote sensing data. We carried out the following experiments in order to provide a theoretical basis and technical support for the research and development of nutritional diagnosis technology of fruit trees based on low-altitude remote sensing data. In this work
the multi-spectral image information of ‘Hamlin ’orange plant canopies were obtained by a multi-spectral camera array mounted on the eight rotor Unmanned Aerial Vehicle( UAV) at an altitude of 100 m above the canopyat 11: 00—13: 00 on a sunny day in spring. Then
the multi-spectral images were pre-processed by Pixel Wrench 2 of tetracam
average spectral reflectance of the whole canopy were individually extracted based on ENVI 4. 7. Twenty leaves from the mature spring shoots were collected from around crown of every tree. Total nitrogen
chlorophyll a
chlorophyll b and carotenoids contents of each plant were measured in the laboratory. The characteristic wavelengths were extracted by means of the correlation analysis of the average spectra of the plants with the nutrition content. A total amount of 88 citrus trees were collected and randomly grouped into two sets of samples: 66 plants for the calibration set and 22 plants for the prediction set. The two kinds of spectral pre-processing methods( Multiplicative Scatter Correction( MSC) and Standard Normal Variable( SNV)) were adopted and four kinds of modeling methods( Partial Least Squares( PLS)
Multiple Linear Regression( MLR)
Principal Component Regression( PCR)and Least Squares Support Vector Machine( LS-SVM)) were employed to estimate total nitrogen
chlorophyll a
chlorophyll b
and carotenoids content in canopy leaves. The results showed that the prediction accuracy of the MLR model based on SNV spectral pre-processing methods was the best for the prediction of total nitrogen
chlorophyll a and chlorophyll b content
correlation coefficients of prediction( Rp) were 0. 8036
0. 8065
0. 8107
and Root Mean Square Error of Prediction( RMSEP) were 0. 1363
0. 0427 and 0. 0243
respectively. The LS-SVM model based on SNV spectral pre-processing methods for the carotenoids content of crown was the best
which is with Rp= 0. 8535
RMSEP = 0. 0117. The results demonstrated that the airborne multi-spectral image information of citrus plants canopy could be used to estimate total nitrogen
chlorophyll a
chlorophyll b and carotenoids content in canopy leaves. This research results would provide a new way for accurate
efficient prediction of plants nutrition status of largescale citrus orchards.
甜橙冠层光合色素氮近地遥感
sweet orangecanopyphotosynthetic pigmentsnitrogenlow-altitude remote sensing
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