Crop disease monitoring method and system based on UAV multi-source image fusion

Abstract

The invention discloses a crop disease monitoring method and system based on UAV multi-source image fusion and belongs to the technical field of agricultural information monitoring. The system comprises a UAV equipped with an image capture device and a processor used for processing images and detecting disease distribution. The UAV flies according to a determined capture route and captures the hyperspectral image, the RGB image and the thermal infrared image of farm crops. The processor comprises an image processing unit, a modeling unit and a wireless remote control unit. The captured hyperspectral image, RGB image and thermal infrared image are separately spliced, a hyperspectral spliced image and the RGB spliced image are merged, and a thermal infrared spliced image and the RGB splicedimage are merged. Thus, the advantages of respective images can be integrated, the complementarity of different types of remote sensing images can be achieved, image data sets conducive to human interpretation and post-processing are available, and a possibility can be provided for accurate crop disease monitoring.

Description

technical field [0001] The invention relates to the technical field of agricultural information monitoring, in particular to a crop disease monitoring method and system based on multi-source image fusion of drones. Background technique [0002] Crop diseases are one of the main agricultural disasters in my country. They have the characteristics of various types, large impacts, and easy outbreaks, which seriously affect the yield of crops and even cause crop failure. Take rapeseed sclerotinia as an example, it is a worldwide disease, and the incidence is most serious in the Yangtze River Basin in my country. According to statistics, Sclerotinia sclerotiorum occurs in all rape producing areas in my country, the incidence rate is generally 10% to 80%, and the annual yield loss can reach up to 30%. [0003] Growing in the natural environment of farmland, crops are easily affected by the environment, soil and varieties, and the period and degree of disease infestation of crops a...

AI Technical Summary

Problems solved by technology

At present, the monitoring of crop diseases can only determine the type and degree of disease infection by manual visual inspection and field sampling according to the approximate period of disease occurrence. These methods are time-consuming, laborious, subjective and not representative.

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