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Planting plot grain and oil crop type step-by-step identification method

A technology of grain and oil crops and identification methods, which is applied in the direction of neural learning methods, character and pattern recognition, biological neural network models, etc., can solve the problems of high consumption and low recognition accuracy, eliminate time-consuming and labor-intensive work, and facilitate management Effect

Pending Publication Date: 2021-12-17
苏州中科蓝迪软件技术有限公司 +1
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Problems solved by technology

However, the classification of large-scale crops is affected by different phenology, resulting in low recognition accuracy, so it takes a lot of manpower and material resources to make samples

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  • Planting plot grain and oil crop type step-by-step identification method
  • Planting plot grain and oil crop type step-by-step identification method
  • Planting plot grain and oil crop type step-by-step identification method

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Embodiment Construction

[0054] The technical solutions of the present invention will be further described in detail below in conjunction with specific embodiments.

[0055] see figure 1 , a method for step-by-step identification of types of grain and oil crops in planting plots, comprising the following steps:

[0056] S1. Extracting cultivated land plots based on high-resolution remote sensing images;

[0057] S2. Generate a pop-up library based on the generated time-series remote sensing images;

[0058] S3, using transfer learning to extract crop types;

[0059] S4. Iteratively optimize the model accuracy.

[0060] Specifically, in this embodiment, the advantages of clear boundaries of optical images and transfer learning will be combined to make up for the shortcomings of traditional crop classification and a land-level crop classification method will be proposed, using high-resolution remote sensing images to generate cultivated land. Block vector, and then generate a spectral library based on...

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Abstract

The invention discloses a planting plot grain and oil crop type step-by-step identification method, and relates to the technical field of remote sensing agricultural monitoring equipment, and the method comprises the following steps: S1, extracting a cultivated land plot based on a high-resolution remote sensing image; S2, generating a spectrum library based on the generated time sequence remote sensing image; S3, carrying out crop type extraction by utilizing transfer learning; S4, iteratively optimizing the model precision, extracting the planting types of the crops in the land parcels on the basis of different spectral values of different types of crops in different time phases so as to classify the types of the crops in the land parcels, generating pure samples on the basis of the time phase of each image of a target area by constructing a spectrum library in planting structure transfer learning. through the method for screening the samples, the training samples can be screened out with relatively high precision. The process is a process of transferring from a spectrum library to a local part, and through the method, time-consuming and labor-consuming work of manual sample selection in a traditional method and regional limitation of a traditional classification method can be eliminated.

Description

technical field [0001] The invention relates to the technical field of remote sensing agricultural monitoring equipment, in particular to a step-by-step identification method for grain and oil crop types in planting plots. Background technique [0002] Real-time and accurate crop monitoring is of great significance for assisting crop management and suitability evaluation, crop yield estimation, crop disaster early warning, and crop planting model planning. Accurate crop mapping at the regional scale can provide new data support for government macro-control. The traditional field survey and monitoring of crops is time-consuming and labor-intensive, and cannot meet the needs of large-scale, fast and timely agricultural monitoring. With the development of remote sensing satellite technology and the improvement of intelligent processing technology, with the periodicity, macroscopicity, timeliness and economy of remote sensing technology to obtain surface information, agricultur...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/047G06N3/044G06F18/2415G06F18/214
Inventor 胡晓东马士杰李昕董文张明杰张新石含宁郜丽静韩小妹骆剑承罗露花
Owner 苏州中科蓝迪软件技术有限公司
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