基于遥感时序与生育期模型的倒伏损害定量估算方法
By constructing instantaneous lodging intensity and cumulative lodging loss index, and adaptively adjusting the parameters of the dual-logic function time series model, the problem of low accuracy in estimating vegetation lodging damage in existing technologies is solved, and accurate quantitative estimation of lodging damage and reflection of actual yield loss are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- JIANGSU ACAD OF AGRI SCI
- Filing Date
- 2025-11-07
- Publication Date
- 2026-07-17
AI Technical Summary
Existing dual-logic function time-series fitting models cannot accurately capture the true magnitude of vegetation lodging damage when fitting it, resulting in low calculation accuracy and failing to meet the requirements for accurate estimation of localized sudden lodging damage.
By constructing instantaneous lodging intensity, cumulative lodging loss index, and calibration factor, the parameters of the dual-logistic function time series model are adaptively adjusted, including the preprocessing of remote sensing time series data, calculation of instantaneous lodging intensity, construction of cumulative lodging loss index, and calculation of calibration factor, to improve the accuracy of quantitative estimation of lodging damage.
It improves the sensitivity to lodging events, reflects the cumulative damage to vegetation, enables accurate prediction and quantitative estimation of lodging damage, and improves the accuracy of estimation results and the ability to reflect actual yield losses.
Smart Images
Figure CN121459166B_ABST