Automatic meteorological observation method and system for crops
An observation system and crop technology, applied in the field of agricultural informatization, can solve problems such as lack of meteorological observation capabilities, and achieve the effects of improving timeliness, pertinence, and work efficiency
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Embodiment 1
[0050] The present embodiment provides a kind of meteorological automatic observation system of crops, such as Figure 2-6 Shown, comprise crop meteorological automatic observation station 10, provincial central station 40 and national comprehensive meteorological information sharing platform 30, the signal end of crop meteorological automatic observation station 10 is connected with the signal end of provincial central station 40, and provincial central station 40 The signal end of the national comprehensive meteorological information sharing platform 30 is connected to the signal end; the crop meteorological automatic observation station 10 includes an image sensor 102, an image collector 101 and peripheral equipment 104, and the image sensor 102 is connected with the image collector 101, and the image collector 101 Also connected to peripheral device 104 .
[0051] As a preferred embodiment, the crop weather observation station 10 also includes a video sensor 103 .
[0052...
Embodiment 2
[0064] The present embodiment provides the automatic meteorological observation method for crops, such as figure 1 As shown, the method includes:
[0065] Collect crop images, identify crop types according to the crop images, and the crop types include rice, wheat, corn, cotton, rapeseed, soybean and sugarcane;
[0066] Continuously acquire image information of crops, analyze the image information acquired at different time nodes, and judge the characteristic types of crops respectively, which include crop development period, coverage, density, canopy height, growth status evaluation, leaf Area index and dry matter weight;
[0067] Analyze and compare each feature type to determine whether the feature type is in a normal state.
[0068] Further, when judging the crop development period of the crop, first judge the type of the crop according to the image of the crop;
[0069] When the crop type is rice, the development period of the crop includes the transplanting period, th...
Embodiment 3
[0092]In this embodiment, on the basis of Embodiment 1 and Embodiment 2, the image information or video information collected by the image collector 101 of the present embodiment is transmitted to the provincial central station 40 and the national comprehensive weather information sharing platform 30 through the network for analysis judge. This embodiment can automatically identify agricultural meteorological disasters based on image data, meteorological data and artificially assisted observation data. Agricultural meteorological disasters are divided into dominant disasters with obvious symptoms of crop damage and can be identified through image analysis, and hidden disasters with no obvious symptoms of crop damage and difficult image recognition. Dominant disasters mainly include: drought, windy lodging, hail disaster; hidden disasters mainly include: waterlogging, continuous rain, low temperature and chilling damage, frost, freezing damage, snow disaster, high temperature h...
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