Method for rapidly extracting crop planting area and phenological information in large range

Abstract

The invention discloses a method for rapidly extracting the crop planting area and the phenological information in a large range. The method comprises the following steps of S1, selecting the cultivated land sample lattice points, and extracting the LAI time sequence data of each sample lattice point based on a low spatial resolution remote sensing product; S2, carrying out filtering processing onthe LAI time sequence data of the sample lattice points to obtain a filtered LAI characteristic curve; S3, extracting the key phenological periods of the sample lattice points; S4, calculating the root mean square errors (RMSE) of the key phenological periods of the sample grid points extracted by crops in the research area under different filtering methods and the phenological observation valuesof the corresponding agricultural gas stations, and determining an optimal filtering method according to an RMSE minimum principle; and S5, filtering the LAI time sequence data of each cultivated land lattice point in the research area according to the optimal filtering method, extracting the key phenological period of each crop in the whole growth season by utilizing the method in the step S3, and identifying the corresponding planting range and area of each crop according to the key phenological period.

Description

technical field [0001] The invention relates to the technical field of agricultural remote sensing, in particular to a method for rapidly extracting crop planting area and phenological information in a large area. Background technique [0002] Crop planting range, planting area and key phenological periods are the most basic and important agricultural information in the actual agricultural production status. The phenological period is a key indicator reflecting the growth and development stages of crops, and knowing the planting distribution of crops is also a necessary condition for large-scale agricultural monitoring. Currently available crop phenology data mainly come from the records of agricultural meteorological stations or experimental stations. These data are authoritative and authentic, but the number of stations nationwide is very limited. At the same time, the operation and maintenance costs of agricultural meteorological stations are high and cannot Comprehensiv...

AI Technical Summary

Problems solved by technology

This method overcomes the disadvantages of the existing extraction methods that are only applicable to small scales and requires a large amount of calculation. The results extracted by the new method can be well matched with the phenology recorded by the agricultural gas station and the planting area data in the county-level statistical yearbook.

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