Wide-range crop phenology extraction method based on morphological model method

Abstract

The invention discloses a wide-range crop phenology extraction method based on a morphological model method. The method comprises the following steps of acquiring a multi-year vegetation index time sequence curve of a local geographic area; carrying out smooth fitting on the vegetation index time sequence curve by utilizing a dual logic function fitting mode; establishing a morphological model byusing the reference curve and the reference points of the agricultural gas station; performing morphological model fitting by utilizing transformation; and calculating by using the optimal scaling parameter to obtain a phenological period extraction value of the local geographic region. The macroscopic characteristics of the curve are utilized, the influence of local fluctuation and noise of the curve can be reduced, and the extraction precision is better; and each phenological period of the crops can be extracted at the same time, different measurement standards do not need to be set respectively, and the method can be applied to large-scale crop phenological extraction.

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 as they grow, which can reflect the impact of climate change on agricultural ecosystems. Crop phenology information can provide important decision-making information for crop irrigation scheduling and fertilization management; accurate phenological period is also an important input information for accurate crop yield prediction models; in addition, phenological period is also an important basis for remote sensing crop ...

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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