Method and system for classifying crops

Abstract

The invention discloses a crop classification method and system. The classification method includes: constructing historical crop marker samples according to the historical multi-temporal mid-segment images and historical crop phenology data; constructing high-precision small-area current crop marker samples according to the current multi-temporal high-resolution images and current crop phenology data; according to ResNet model and PSPNet model to establish the remote sensing network RSNet model; pre-train the remote sensing network RSNet model according to the historical training samples to establish the pre-trained remote sensing network RSNet model; fine-tune the pre-trained remote sensing network RSNet model according to the current training samples to establish a fine-tuned remote sensing network RSNet model; establishing an optimal pre-trained remote sensing network RSNet model and an optimal fine-tuning remote sensing network RSNet model; classifying the crops according to the optimal pre-training remote sensing network RSNet model and the optimal fine-tuning remote sensing network RSNet model. By adopting the classification method and system provided by the present invention, the workload of training sample selection can be reduced, and the classification efficiency can be improved.

Description

technical field [0001] The invention relates to the field of crop classification, in particular to a crop classification method and system. Background technique [0002] Real-time and accurate acquisition and mastery of crop planting area and its spatial distribution is of great significance for accurately estimating and predicting crop yield, monitoring agrometeorological disasters, and ensuring national food security. [0003] Remote sensing technology is currently the main technical means for crop area and spatial distribution monitoring. With the development of remote sensing technology, more and more high-time and high-spatial resolution remote sensing images can be obtained for free, which enriches the data sources for crop remote sensing identification. At the same time, it also increases the difficulty of remote sensing image information extraction methods. Crop remote sensing classification mainly includes: ground survey, determination of classification system, sel...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a crop classification method and system to solve the problems of heavy workload in training sample selection and low classification efficiency

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