| Inversion of cotton growth indexes at drip irrigation subunit scale based on UAV multi\|spectral remote sensing |
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| DOI：10.7606/j.issn.1000-7601.2025.05.22 |
| Key Words: cotton growth index inversion model UAV multispectral remote sensing drip irrigation subunit |
| Author Name | Affiliation | | XU Yawei | State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China | | WANG Zhen | State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China | | LI Yanfeng | State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China | | LI Jiusheng | State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100048, China |
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| Abstract: |
| Based on the UAV remote sensing platform equipped with RTK module and 4 bands multi\|spectral camera, canopy surface elevation and multi\|spectral image data at cotton bud stage, flowering stage, and bolling stage were collected. The cotton plant height, leaf area index, and biomass at drip irrigation subunit scale were determined. The Digital Surface Model was constructed for retrieving cotton plant height. Partial Least Squares Regression, Support Vector Machine, and Random Forest models were used to establish inverse models of cotton leaf area index and biomass. The optimal model was used to predict the crop growth index at drip irrigation subunit scale. The results showed that the determination coefficient (R2) of the telemetry cotton height and measured plant height based on the digital surface model method was 0.59. The random forest model had the best inversion effect for cotton leaf area index (LAI) and biomass, while the model R2 were 0.56 and 0.74, respectively. The coefficient R2 between measured and predicted plant height for the drip irrigation subunits was 0.83. The average difference between the measured and predicted leaf area index at bud stage, flowering stage, and bolling stage were 0.17, 0.46, and 0.97, respectively. The average difference between the measured and predicted biomass was 0.12 t·hm-2, 1.37 t·hm-2, and 3.17 t·hm-2, respectively, and the data points basically fell within the 95% agreement limit. The measured value of crop growth index in drip irrigation subunits were consistent with the predicted value. |
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