Winter wheat LAI inversion considering morphological characteristics at different growth stages coupled with microwave scattering model and canopy simulation model
To better eliminate the adverse effects of the ground surface on winter wheat Leaf area index (LAI) inversions and to further improve the accuracy of regional winter wheat LAI inversion using SAR remote sensing data, considering the morphological characteristics at different wheat growth stages, a w...
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Veröffentlicht in: | Remote sensing of environment 2020-04, Vol.240, p.111681, Article 111681 |
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Sprache: | eng |
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Zusammenfassung: | To better eliminate the adverse effects of the ground surface on winter wheat Leaf area index (LAI) inversions and to further improve the accuracy of regional winter wheat LAI inversion using SAR remote sensing data, considering the morphological characteristics at different wheat growth stages, a winter wheat LAI inversion model coupled with the microwave scattering model (MSM) for winter wheat at different growth stages (MSMDGS) and the canopy scattering simulation model (CSSM) was proposed. In this research, taking Hengshui City of Huanghuaihai Plain of North China as the study region, using RADARSAT-2 data as image sources and based on parameter sensitivity analysis and model calibration, the proposed model was applied and validated. The LAI inversion results of winter wheat showed that the proposed model had good performance in the regional application and that LAI inversion results with high accuracy could be obtained. Among the three key growth stages (jointing stage, booting stage and heading stage) of winter wheat, the R2, adjusted R2 and RMSE between the LAI inversion value and the ground-measured data were 0.918, 0.917 and 0.675, respectively, which indicated that the winter wheat LAI inversion model coupled with MSMDGS and CSSM had certain feasibility and applicability.
•A microwave scattering model for wheat at different growth stages was proposed.•A winter wheat LAI inversion model coupled with MSM and CSSM was constructed.•The calibration, application and validation of model were finished effectively.•The proposed LAI inversion model had high accuracy in the regional application. |
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ISSN: | 0034-4257 1879-0704 |
DOI: | 10.1016/j.rse.2020.111681 |