A detection method of yin and yang leaves in vegetation canopy based on fluorescence remote sensing

Abstract

The invention discloses a method for detecting yin and yang leaves of a vegetation canopy based on fluorescence remote sensing, which includes: performing precise geometric correction and radiation calibration on the target remote sensing image; constructing and calculating the fluorescence remote sensing vegetation recognition index; using the K-Means method to calculate and obtain Vegetation spatial distribution map; use spatial algorithm to obtain remote sensing image map containing only vegetation information; construct and calculate vegetation yin and yang leaf fluorescence index; use remote sensing unsupervised classification method to extract vegetation canopy yin and yang leaf information, and obtain a vegetation yin and yang leaf space Distribution. The present invention eliminates the influence of non-vegetation background information on the detection results of yin and yang leaves in the vegetation canopy to the greatest extent, improves the accuracy and reliability of the detection of yin and yang leaves; High precision, simple and flexible operation process, unlimited vegetation type, less manual intervention, high degree of automation, strong universality, easy to popularize and apply.

Description

technical field [0001] The invention relates to a method for detecting yin and yang leaves of a vegetation canopy based on fluorescence remote sensing, which belongs to the application fields of ecological agriculture, ecological construction, ecological environment protection, disaster monitoring and the like. Background technique [0002] Under natural light conditions, due to the difference in the location of the leaves and the surrounding environment, the leaf part in the vegetation canopy that is directly exposed to sunlight is often called "sun leaf", and the leaf part that is not directly exposed to sunlight is called "shade leaf". leaf". The acquisition of shady and sunny leaf information of vegetation canopy is an important index parameter for effectively measuring the light energy use efficiency of vegetation, accurately monitoring the physiological and ecological status of vegetation and crop growth, and can be used for the study of vegetation photosynthesis, the ...

AI Technical Summary

Problems solved by technology

The first type of traditional photographic method is to use a camera to shoot the target quadrat, and then use image processing technology and related algorithms to detect and distinguish the yin and yang leaves. Even if the same type of vegetation is very close, the proportion of yin and yang leaves in the canopy is also different. The data results of one quadrat or several quadrats are not representative in a wide range, and require a lot of manual operation, which is poor in operability and difficult to obtain. Promote application

Another type of estimation method based on remote sensing. There are very few existing studies on this type of method. In the existing methods, there are many manual interventions, large uncertainties, and certain restrictions on vegetation types. The application range is narrow and universal. Poor sex

In practical applications, the first type of traditional method is still used, using a fixed value to represent the yin and yang leaf information of a vegetation type, or using an average value to represent the entire vegetation canopy under certain assumptions, and then substituted into the model or used as A parameter information is used to participate in calculation and analysis applications, resulting in a significant reduction in the accuracy of specific analysis results

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