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Leaf area index acquisition method and system

A leaf area index and acquisition method technology, applied in image data processing, measuring devices, instruments, etc., can solve problems such as low accuracy of SAR inversion, many interference factors, complex interaction mechanism between electromagnetic waves and crops, etc.

Active Publication Date: 2018-07-20
SUZHOU ACADEMY OF AGRI SCI
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Problems solved by technology

[0006] Compared with optical remote sensing, SAR retrieval of crop LAI is subject to more interference factors. In addition to the radar's own system parameters, there are also crop structure, coverage, water content, and the water content and roughness of the underlying soil. , the interaction mechanism between electromagnetic waves and crops is more complicated, so the SAR inversion accuracy of various biological parameters of crops using the water cloud model is relatively low

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  • Leaf area index acquisition method and system
  • Leaf area index acquisition method and system

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Embodiment Construction

[0065] The object of the present invention is to provide a method and system for obtaining leaf area index, in order to improve the accuracy of inversion of vegetation biological parameters by water cloud model.

[0066] In order to make the above objects, features and advantages of the present invention more comprehensible, the invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0067] Specifically, the specific meanings of the technical terms involved in the present invention are:

[0068] Synthetic aperture radar: synthetic aperture radar, SAR. A small antenna is used to move at a constant speed along the track of a long linear array and radiate coherent signals, and coherently process the echoes received at different positions to obtain a higher-resolution imaging radar.

[0069] Multi-view processing: the entire effective synthetic aperture length is divided into multiple segments to image the same...

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Abstract

The invention discloses a leaf area index acquisition method and a system. The method comprises the following steps of firstly, acquiring the SAR images and the optical images of crops to be tested, carrying out ground control point registration on the SAR images and the optical images and acquiring image data; according to the image data, a vegetation water content measured actually, surface soilmoisture and a roughness parameter, determining an attenuation coefficient in an improved water cloud model and a radar backscattering coefficient when a crop canopy is closed and acquiring a crop total backscattering coefficient model; and then, according to the image data and the crop total backscattering coefficient model, inverting so as to obtain the vegetation water content, and then estimating the leaf area index of the crops to be tested. In the invention, radar remote sensing and optics are combined and are applied to the improved water cloud model; the advantages of the radar remotesensing and the optics are fully used to invert crop biological parameters; and vegetation coverage and effects of bare soil on radar signals are separated and inversion precision is increased.

Description

technical field [0001] The invention relates to the field of vegetation monitoring, in particular to a method and system for obtaining a leaf area index. Background technique [0002] Rice leaf area index (LAI) describes the relationship between rice leaf growth and leaf density. It is one of the important parameters to characterize the growth and development of rice. The traditional LAI measurement method is time-consuming and labor-intensive, and it is a destructive sampling method, and it is difficult to monitor a large-scale LAI. As a non-invasive method, remote sensing technology has the advantages of large-scale, multi-scale, multi-spectrum, and periodicity. , plays an important role in crop LAI monitoring from regional to global scales. [0003] At present, the means of remote sensing inversion of rice LAI is mainly optical remote sensing. Usually, the vegetation index is calculated by using the remote sensing surface reflectance, and the LAI is estimated by establis...

Claims

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Application Information

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IPC IPC(8): G01B11/28G06T7/11G06T7/30
CPCG01B11/28G06T7/11G06T7/30G06T2207/10044G06T2207/20132
Inventor 陈妮张青张海东田婷
Owner SUZHOU ACADEMY OF AGRI SCI
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