Remote Sensing Inversion of Tobacco SPAD Based on UAV Hyperspectral Imagery

Soil plant analysis development (SPAD) represents relative chlorophyll content, which directly affects tabacco health. Accurate monitoring of tobacco canopy SPAD is vital to guide field management. Due to low correlation, few number of features and single model, the existed inversion models have low...

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Bibliographic Details
Published inIGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium pp. 3478 - 3481
Main Authors Qin, Rui, He, Lei, Li, Yuxia, He, Jixian, Gao, Jun, Yan, Fangfang, Yu, Yufan, Liao, Kunwei, Lu, Liming, Jian, Sichun, Kang, Hanghui
Format Conference Proceeding
LanguageEnglish
Published IEEE 16.07.2023
Subjects
Correlation
Feature extraction
Hyperspectral image
Indexes
Kmeans
Robustness
Soil
SPAD
Tabacco
Task analysis
Vegetation mapping
XGBoost
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Summary:Soil plant analysis development (SPAD) represents relative chlorophyll content, which directly affects tabacco health. Accurate monitoring of tobacco canopy SPAD is vital to guide field management. Due to low correlation, few number of features and single model, the existed inversion models have low accuracy and poor robustness. This paper expanded samples from hyperspectral images using PROSAIL, so as to avoid overfitting. In the aspect of feature extraction, the optimized vegetation index is added to increase the correlation between features and SPAD. The inversion model combines K-means and XGBoost to form a mixed model. The results show that the mixed model has better effect on the validation set than other models, R 2 =0.83, RMSE=3.9.
ISSN:2153-7003
DOI:10.1109/IGARSS52108.2023.10282002