Winter wheat yield prediction method based on unmanned aerial vehicle imaging hyperspectral remote sensing

A technology for hyperspectral remote sensing and yield prediction, applied in color/spectral characteristic measurement, measuring devices, material analysis through optical means, etc., can solve problems such as model difference and complexity, and achieve accurate results, simple operation, and simple calculation Effect

Pending Publication Date: 2020-03-27
PEKING UNIV
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Problems solved by technology

[0005] Based on the above technical background, in order to overcome the deficiencies of the existing winter wheat remote sensing yield prediction methods, the inventors have carried out dedicated research and proposed a winter wheat yield prediction method based on UAV imaging hyperspectral remote sensing. Wheat growth information obtained by UAV hyperspectral remote sensing, c

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  • Winter wheat yield prediction method based on unmanned aerial vehicle imaging hyperspectral remote sensing
  • Winter wheat yield prediction method based on unmanned aerial vehicle imaging hyperspectral remote sensing
  • Winter wheat yield prediction method based on unmanned aerial vehicle imaging hyperspectral remote sensing

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Embodiment approach

[0063] According to a preferred embodiment of the present invention, the training samples of the yield prediction model come from the simulation results of the CERES-Wheat winter wheat growth model. The CERES-Wheat model is currently one of the most widely used crop growth model systems, which can simulate basic physiological and ecological processes such as crop vegetative growth and reproductive growth and development, crop photosynthesis, respiration, dry matter distribution, plant growth, and aging. Finally, the simulation of crop yield is realized.

[0064] The CERES-Wheat model input parameters of the present invention include meteorological parameters, soil data, variety information and field management data. Among them, the meteorological data include the highest temperature, the lowest temperature, and precipitation, etc., and the soil data include soil texture, capacity, PH value, and soil moisture characteristics. Management data includes irrigation information, fe...

Embodiment

[0081] The present invention is further described below through specific examples, and these embodiments are only limited to illustrate the present invention, and are not used to limit the scope of the present invention.

[0082] Take the national high-quality wheat production base in Yancheng District, Luohe City, Henan Province in 2019 as an example. The DJI M600 Pro drone platform is used, and the sensor Pika L hyperspectral imager equipped with it has 300 bands and a band range of 400nm to 1000nm. The sensor adopts push-broom imaging. The flying height of the UAV is set to 100m, and the flying speed is 3m / s. A standard whiteboard and four 1.2m×1.2m standard reflectivity targets with reflectivity of 5%, 20%, 40% and 60% are arranged on the ground. Use Resonon software to perform radiometric calibration and rough geometric correction processing on the original hyperspectral image of the UAV to generate intermediate products, use Agisoft Photoscan software to perform short t...

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Abstract

The invention provides a winter wheat yield prediction method based on unmanned aerial vehicle imaging hyperspectral remote sensing, and the method comprises the following steps: hyperspectral image processing of an unmanned aerial vehicle, growth parameter inversion of crops, construction of a winter wheat yield prediction model, and verification of yield prediction precision. According to the prediction method provided by the invention, wheat growth vigor information obtained through hyperspectral remote sensing of the unmanned aerial vehicle in multiple growth periods is comprehensively considered; meanwhile, crop growth priori knowledge provided by a crop growth model is introduced to predict the wheat yield, the method is simple in calculation and accurate in result, has universalitystarting from a remote sensing mechanism, and provides a new thought and a new method for accurately predicting the crop yield.

Description

technical field [0001] The invention relates to the technical field of farmland quantitative remote sensing monitoring, in particular to a method for predicting crop yields using hyperspectral remote sensing technology. Background technique [0002] Grain is an important strategic material related to the national economy, people's livelihood and national economic security. Food security is closely related to economic development and social harmony. The shortage of water resources, land degradation, frequent natural disasters, and increasingly serious agricultural environmental pollution have seriously affected the stable development and quality improvement of food production. Winter wheat is one of the main grains in my country. Timely and accurate prediction of its yield can provide strong support for agricultural decision-making and management. It is an urgent need for the development of precision agriculture and sustainable development. [0003] Satellite remote sensing ...

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Application Information

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IPC IPC(8): G01N21/31G01N21/3563G01N21/359
CPCG01N21/31G01N21/3563G01N21/359
Inventor 范闻捷杨斯棋
Owner PEKING UNIV
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