Wheat lodging region identification method based on spectral texture features and support vector machine

Abstract

The invention relates to a wheat lodging area identification method based on spectral texture features and a support vector machine, and the method comprises the steps: assembling a multispectral sensor on an unmanned plane platform, and monitoring a farmland; superposing the single-channel remote sensing images of several wavebands based on the geographic coordinate information of each pixel according to the unmanned aerial vehicle image to generate a plurality of multispectral remote sensing images containing a plurality of channels; through a visual estimation mode, according to lodging and non-lodging types, generating an image with only a lodging area or a non-lodging area in a view field as an original data set; based on a principal component analysis method, calculating texture features of the first two principal components of all the images in the original data set and spectral reflectivity of each pixel in each wave band; constructing a support vector ting machine model and training, presetting the window size, and calling the support vector machine model to judge the type of each window; and counting the number of pixels of all the lodging regions, and further solving the area of the lodging regions.

Description

technical field [0001] The invention relates to the fields of agricultural remote sensing and agricultural disaster assessment, in particular to a method for identifying lodging areas of wheat based on spectral texture features and support vector machines. Background technique [0002] Technical solution of prior art one [0003] The current method for relevant departments to obtain geographical information of the lodging area is: dispatch staff to the affected area; use nylon rope or chalk lime to determine the boundary of the lodging area, outline the boundary of the lodging area, and then use a total station or GPS locator and other tools to determine the geographic coordinates of the corner points, and then use tools such as a tape measure to measure the length of the outline and other information. [0004] The shortcoming of prior art one [0005] This method is time-consuming and labor-intensive, affected by human subjective factors, and the measurement results are c...

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Problems solved by technology

[0009] However, this method is limited by low resolution, unscheduled visit time, and being easily affected by weather factors. Currently, the technology of using space remote sensing to extract crop lodging areas is extremely immature

The accuracy of existing technologies is not very ideal

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