Crops ›› 2023, Vol. 39 ›› Issue (2): 245-252.doi: 10.16035/j.issn.1001-7283.2023.02.035

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Unmanned Aerial Vehicle Hyperspectral Estimation of Nitrogen Content in Cotton Leaves Based on RF and SPA

Yi Xiang1(), Lü Xin1(), Zhang Lifu1,3, Tian Min2, Zhang Ze1, Fan Xianglong1   

  1. 1Agriculture College of Shihezi University/Key Laboratory of Oasis Eco-Agriculture, Xinjiang Production and Construction Corps, Shihezi 832003, Xinjiang, China
    2College of Mechanical and Electrical Engineering, Shihezi University, Shihezi 832003, Xinjiang, China
    3Aerospace Information Research Institute, Chinese Academy of Sciences/State Key Laboratory of Remote Sensing Science, Beijing 100094, China
  • Received:2021-09-22 Revised:2021-10-23 Online:2023-04-15 Published:2023-04-11

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Abstract:

In order to analysis the relationship between cotton leaf nitrogen content (LNC) and canopy spectral reflection characteristics, and achieve rapid, accurate and nondestructive monitoring of nitrogen level in the process of crop growth, based on the cotton plot experiment in Xinjiang Shihezi University Teaching and Experimental Ground in 2019, multiplicative scatter correction, smoothing algorithm, standard normal variate and first derivative were used to pretreat the original spectra of the cotton canopy. Random frog (RF) algorithm and successive projections algorithm (SPA) were used to select characteristic wavelengths and combine with partial least squares regression to establish a spectral prediction model of nitrogen content in cotton leaves. RF and SPA algorithms selected five sensitive characteristic bands of LNC from the cotton canopy spectra of 398-1000nm, and the number of bands decreased by 93.0%-96.3%, which effectively reduced the spectral redundancy information. The determination coefficient and root mean square error of partial least squares regression of LNC constructed based on SPA algorithm screening sensitive band were 0.52 and 2.55, respectively, and the determination coefficient and root mean square error of model verification were 0.70 and 2.37, respectively. The model had good accuracy and stability. It can be used as a method to estimate nitrogen content in cotton leaves by unmanned aerial vehicle.

Key words: Cotton, Unmanned aerial vehicle (UAV), Hyperspectral, Random frog, Successive projections algorithm, Partial least squares regression

Fig.1

Canopy hyperspectral reflectance at different nitrogen levels"

Fig.2

Correlation between spectral reflectance and LNC in cotton canopy"

Fig.3

Characteristic wavelength screening results of RF and SPA algorithms"

Table 1

The effective wavelengths selection for hyperspectral sample"

预处理方法
Pretreatment		 提取算法
Extraction
algorithm		 特征波长数量
Number of characteristic
wavelengths		 特征波长
Characteristic wavelength (nm)
原始光谱Original spectrum RF 10 400、445、516、520、556、669、700、705、722、898
SPA 10 403、414、676、762、953、967、971、980、996、1000
MSC RF 10 518、705、707、722、856、862、898、907、918、598
SPA
 18
 400、518、538、589、629、662、762、791、862、916、924、947、956、962、964、971、976、987
SG RF 10 400、485、516、669、691、700、705、722、845、598
SPA
 19
 398、403、407、412、414、427、516、556、669、720、938、964、967、971、976、980、993、996、1000
SNV RF 10 503、520、536、556、598、705、747、827、860、913
SPA 10 498、762、940、942、953、962、967、982、993、1000
FD RF 10 467、491、511、556、558、583、600、609、622、463
SPA
 17
 733、736、760、933、936、942、949、953、962、969、978、980、982、989、991、993、998

Table 2

Analysis of LNC estimation effect of PLSR in cotton leaves"

处理
Treatment		 训练集Train set 验证集Test set
R2 RMSE R2 RMSE
原始-RF Origin-RF 0.57 2.73 0.47 2.78
原始-SPA Origin-SPA 0.42 2.87 0.56 2.80
MSC-RF 0.53 2.59 0.57 2.73
MSC-SPA 0.46 2.81 0.60 2.57
SG-RF 0.48 2.72 0.61 2.55
SG-SPA 0.50 2.67 0.55 2.76
SNV-RF 0.54 2.56 0.58 2.67
SNV-SPA 0.41 2.90 0.52 2.85
FD-RF 0.53 2.78 0.68 2.67
FD-SPA 0.52 2.55 0.70 2.37

Fig.4

Comparison of measured values and estimated values of RF-PLSR model under different pretreatments"

Fig.5

Comparison of measured values and estimated values of SPA-PLSR model under different pretreatments"

Fig.6

Hyperspectral image and LNC inversion distribution map of cotton field"

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