A large-scale crop phenology extraction method based on morphological model method

Abstract

The invention discloses a large-scale crop phenology extraction method based on a morphological model method. Obtain the multi-year vegetation index time series curve in the local geographical area; use the double logistic function fitting method to smoothly fit the vegetation index time series curve; use the reference curve and reference point of the agricultural gas station to establish a morphological model; use transformation to fit the morphological model; use The optimal scaling parameter is calculated to obtain the extraction value of the phenological period in the local geographical area. The method of the invention utilizes the macroscopic characteristics of the curve, can reduce the influence of local fluctuation and noise of the curve, and has better extraction accuracy; and can simultaneously extract each phenological period of the crop, without setting different metric standards, and can Applied to the extraction of large-scale crop phenology.

Description

technical field [0001] The invention relates to the field of agricultural remote sensing, in particular to a large-scale crop phenology extraction method based on a morphological model method. Background technique [0002] Agricultural production is the cornerstone of human society, and extensive and reliable agricultural information is an important basis for ensuring regional and global food security. The phenology of crops is reflected in the seasonal changes in their physiological characteristics and their physiological responses to environmental conditions with growth, which can reflect the impact of climate change on agro-ecosystems. Crop phenological information can provide important decision-making information for crop irrigation scheduling and fertilization management; accurate phenological period is also an important input for accurate crop yield prediction models; in addition, phenological period is also an important basis for remote sensing crop identification. ...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems existing in the background technology, the present invention proposes a large-scale crop phenology extraction method based on the morphological model method, using satellite remote sensing data to establish a vegetation index time series curve, using the morphological model method to perform curve fitting, and combining ground observation data , calculate the phenology extraction value according to the optimal fitting scaling parameters, which solves the limitations of the current remote sensing crop phenology extraction application scale, low accuracy, and poor versatility

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