Regional corn mature period prediction method based on time sequence LAI curve integral area

Abstract

The invention belongs to the field of agricultural remote sensing and discloses a regional corn mature period prediction method based on a time sequence LAI curve integral area. The method comprises the steps of (S1) obtaining a planting area map of corns of a 500-meter grid unit, (S2) reconstructing a LAI time sequence by using a filtering algorithm with MODISLAI products in a corn growth period, (S3) using a dynamic threshold method to obtain a specific date of a tasseling stage, (S4) calculating corn growth periods of past three years, and calculating a percentage average value Rave of an integral area from the tasseling stage to a mature stage in an integral total area from seedling emergence to matureness, (S5) forming a whole growth period LAI integral curve, (S6) calculating an area ratio Rpre day by day in a forecast interval, and taking a corresponding date as a corn mature period when Rpre is larger than or equal to Rave, and (S7) predicting a mature period by a 500-meter grid unit, generating a regional corn mature period prediction spatial distribution map, and guiding the timely harvest of crops.

Description

technical field [0001] The invention belongs to the field of agricultural remote sensing, and in particular relates to a regional corn maturity prediction method based on the integrated area of ​​time series LAI curves. Background technique [0002] The traditional method of predicting maturity period is based on visual observation method based on field observation, that is, it mainly directly observes the growth status of crops at fixed points on the ground to predict maturity. Carry out spatiotemporal analysis of large-scale crop maturity; in recent years, through the continuous efforts of domestic and foreign researchers, some methods and models for crop maturity prediction have been developed, such as the application of meteorological statistical models to study the effects of factors such as temperature, photoperiod, and precipitation on crop maturity. The influence of crops, to achieve the prediction of crop maturity, although the model is simple and easy to use, with ...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the following problems in the existing technology: how to combine large-scale and high-timeliness remote sensing data with agricultural meteorological data, and introduce meteorological ensemble forecast data to construct a regional corn maturity prediction based on the integrated area of ​​time series LAI curve Method, fully considering the predictability of accumulated temperature for the maturity period, proposed to integrate the accumulated temperature information into the LAI time series to drive the CSDM model, generate a simulated LAI curve with predictive performance, and finally establish a maturity period prediction model based on the integral area, and Predict the crop maturity period to solve the problem that the current maturity period prediction cannot meet the requirements of precision agriculture in terms of spatial resolution and prediction timeliness

Images