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Method and device for detecting growth vigor of rice after disaster

A detection method and rice technology, applied in the field of agricultural remote sensing, can solve the problems of large fluctuation of scattering intensity and unfavorable crop analysis, and achieve the effects of accurate detection, guaranteed availability, and easy loss determination.

Pending Publication Date: 2022-07-29
杭州领见数字农业科技有限公司
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a post-disaster growth detection method and device for rice, aiming to solve the above-mentioned delay in the acquisition of optical images after flood disasters and the large fluctuation of backscattering intensity after precipitation, which is not conducive to the follow-up analysis of crops question

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  • Method and device for detecting growth vigor of rice after disaster
  • Method and device for detecting growth vigor of rice after disaster
  • Method and device for detecting growth vigor of rice after disaster

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Experimental program
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Embodiment 1

[0057] like figure 1 As shown in the figure, a method for detecting post-disaster growth of rice includes the following steps:

[0058] S11. Determine the disaster-affected research area and obtain the SAR image data of the research area. After performing terrain correction, radiometric calibration, and filtering on the SAR image data, the normalized backscattering cross-section intensity is obtained. The backscattering cross-section intensity includes the backscattering cross-section intensity of VH polarization and the backscattering cross-section intensity of VV polarization;

[0059] S12. Bring the backscattering cross-section intensity of the VH polarization and the backscattering cross-section intensity of the VV polarization into the formula Calculated in , to get the normalized difference index, where NDBI is the normalized difference index, σ VH is the backscattering cross-section intensity of VH polarization, σ VV is the backscattering cross-section intensity of ...

Embodiment 2

[0073] A method for NDVI and NDBI relationship establishment, including:

[0074] Taking Jiangsu rice as an example, the typical crop phenological characteristics of the sample area: Jiangsu rice is mainly medium rice, which is sown and germinated in May, and the seedlings turn green in June. The wheat sowing time is mid-to-late October, jointing from late March to early April of the following year, heading from late April to early May, and mature and harvested from late May to early June;

[0075] After analysis, from June 2020 to July 2021, the VV and VH backscattering characteristics of SAR images are as follows: Figure 9 Then, the normalized difference index is calculated, and time series fitting is performed to obtain the typical crop time series fitting characteristics as follows Figure 10 At the same time, combined with the optical image to filter the cloud-less data in the corresponding area, the NDVI time series and fitting results are as follows Figure 11 shown,...

Embodiment 3

[0079] like Figure 12 As shown, a post-disaster growth detection device for rice includes:

[0080] Image data preprocessing module 10: used to determine the disaster-affected research area and obtain the SAR image data of the research area, perform terrain correction, radiometric calibration, and filtering on the SAR image data to obtain a normalized backscattering cross section Intensity, the normalized backscattering cross-section intensity includes the backscattering cross-section intensity of VH polarization and the backscattering cross-section intensity of VV polarization;

[0081] Normalized difference index calculation module 20: used to bring the backscattering cross-section intensity of the VH polarization and the backscattering cross-section intensity of the VV polarization into a formula Calculated in , to get the normalized difference index, where NDBI is the normalized difference index, σ VH is the backscattering cross-section intensity of VH polarization, σ ...

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Abstract

The invention provides a rice after-disaster growth vigor detection method and device, and belongs to the technical field of agricultural remote sensing, and the method comprises the steps: determining a disaster research region, obtaining the SAR image data of the research region, carrying out the topographic correction, radiometric calibration and filtering of the SAR image data, and obtaining the normalized backscattering cross section intensity; substituting the backscattering cross section intensity of the VH polarization and the backscattering cross section intensity of the VV polarization into a formula for calculation to obtain a normalized difference index; and substituting the normalized difference index into a formula NDVI = a * NDBI + b for calculation to obtain a normalized vegetation index, and performing inversion to obtain the growth vigor of the rice. According to the technical scheme, the growth vigor of the rice crops is detected based on the SAR image, the rice disaster situation is detected by utilizing the characteristics that imaging of the SAR image is not influenced by weather factors and is timely, the problem that optical images are not suitable for detection after flood disasters is solved, and the accessibility, timeliness and accuracy of data are guaranteed.

Description

technical field [0001] The invention belongs to the technical field of agricultural remote sensing, and in particular relates to a method and device for detecting post-disaster growth of rice. Background technique [0002] In recent years, extreme weather has become more and more frequent. In the first three quarters of 2021, a total of 39 heavy rainfall events occurred in my country, and the national surface precipitation was 582 mm, an increase of 4% over the same period of the previous year. Among them, from July to August 2021, Henan, Sichuan, Shanxi, Hebei and other places in my country were affected by severe rainstorms and floods and suffered serious damage. In terms of crop production, floods caused by continuous rainfall inundate farmland, which in turn affects the growth of crops. The continuous cloudy and rainy weather makes it difficult to obtain optical remote sensing images, especially in the cloudy and rainy conditions in the south, which prolongs the effecti...

Claims

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Application Information

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IPC IPC(8): G06V20/10G06V10/25G06V10/44
Inventor 周祖煜林波颜芳陈煜人白博文莫志敏张浩张澎彬李天齐刘俊
Owner 杭州领见数字农业科技有限公司
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