Over-winter crop identification method and device

An identification method and crop technology, applied in the field of agricultural remote sensing, can solve problems such as high data quantity and quality requirements, human factor interference, and crop identification misclassification, and achieve the effect of improving accuracy, reducing misclassification and accurate extraction.

Pending Publication Date: 2022-04-12
杭州领见数字农业科技有限公司
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] This application provides an identification method and device for overwintering crops, aiming to solve the problems of low classification accuracy, low identification accuracy, misclassification of crop identification, high data quantity and quality requirements and human factor interference in the above-mentioned prior art The problem

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  • Over-winter crop identification method and device

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Effect test

Embodiment 1

[0052] Such as figure 1 Shown, a kind of identification method of overwintering crops, comprises the following steps:

[0053] S11. Obtain remote sensing image data of the research area, and perform preprocessing to obtain time-series image data;

[0054] S12. Calculate the time-series image data according to the NDVI calculation formula to obtain the time-series NDVI;

[0055] S13. Obtain the data of the field quadrat plots, and establish an interpretation flag, and select samples according to the interpretation flags. The field quadrat plot data is not limited to wheat and rapeseed, and the samples are not limited to wheat samples and rapeseed sample;

[0056] S14. Extract the NDVI values ​​of the wheat sample and the rape sample according to the time series NDVI, summarize and draw the NDVI curve, analyze the NDVI curve and the overwintering crop phenology according to the comparative analysis method, and obtain the overwintering crop phenology critical phases of the cro...

Embodiment 2

[0060] Such as figure 2 As shown, a method for determining the critical phase of overwintering crops includes the following steps:

[0061] S21. Extract the NDVI values ​​of the wheat sample and the rape sample according to the time series NDVI, summarize and draw the NDVI curve;

[0062] S22, analyze described NDVI curve and described surviving crop phenology according to comparative analysis method, obtain the key phase of described surviving crop.

[0063] In this example, wheat crop samples and rapeseed crop samples from November 2018 to June 2019, November 2019 to June 2020, and November 2020 to June 2021 were extracted according to the time series NDVI of the time series image data The NDVI values ​​​​in the three growth periods are combined and summarized within one year, and then the NDVI curves of wheat and rapeseed are drawn, and the two curves are drawn in the same drawing, as shown in image 3 As shown, a represents the NDVI of wheat, and b represents the NDVI ...

Embodiment 3

[0079] Such as Figure 5 As shown, a method of processing according to a preset method to obtain a final recognition result includes the following steps:

[0080] S31. Extract the cultivated land range of the research area through the global 10-meter resolution land cover dataset, and record it as the Cropland layer, perform statistical synthesis according to the time series NDVI, obtain the NDVI_max layer, and perform non-vegetation on the NDVI_max layer Remove the area, and superimpose it with the Cropland layer, take the intersection to get the range of cultivated land;

[0081] S32. According to the multi-temporal NDVI change, the range of the cultivated land is removed to obtain the range of the overwintering crops;

[0082] S33, combining not limited to one key phase and the NDVI curve to analyze, obtain NDVI rape / NDVI wheat>1 during the first period, and NDVI rape / NDVI wheat<1 during the second period;

[0083] S34. According to the characteristics of the first period a...

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Abstract

The invention provides a method and a device for identifying overwinter crops, which are applied to the technical field of agricultural remote sensing, and the method comprises the steps: obtaining remote sensing image data of a research area, and carrying out the preprocessing to obtain time sequence image data; calculating the time sequence image data according to an NDVI calculation formula to obtain a time sequence NDVI; acquiring field quadrat plot data, establishing an interpretation mark, and selecting according to the interpretation mark to obtain a sample; extracting sample NDVI values according to a time sequence NDVI, summarizing and drawing to obtain an NDVI curve, and analyzing the NDVI curve and the off-winter crop phenology according to a comparative analysis method to obtain a key time phase; and calculating the time sequence image data according to a preset processing mode to obtain a cross-winter crop range, and identifying the cross-winter crop range through a random forest classification algorithm according to the key time phase to obtain a cross-winter crop identification result. Classification precision and identification precision are improved, crop identification error classification and human factor interference are avoided, and data quantity and quality requirements are reduced.

Description

technical field [0001] The present application relates to the technical field of agricultural remote sensing, in particular to a method and device for identifying overwintering crops. Background technique [0002] Remote sensing crop identification technology can quickly and accurately acquire crop spatial distribution information in a wide range of areas, thereby providing basic information support for digital agricultural technology and services, and helping to realize intelligent perception of agricultural status and digital support for production management. [0003] The existing technical schemes rarely consider crop phenology information, and mostly classify crops based on single-period image data or full time-series image data. This method will lose or blur key phenological information of crops, so the classification accuracy is not high; the prior art The scheme seldom considers the growth characteristics of crops, but mostly based on spectral characteristics, and us...

Claims

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Application Information

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IPC IPC(8): G06V20/10G06K9/62G06V10/774G06V10/764
Inventor 周祖煜张澎彬王俊霞周斌陈煜人白博文莫志敏张浩李天齐刘俊
Owner 杭州领见数字农业科技有限公司
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