Wetland vegetation feature optimization and fusion method based on JM Relief F

Abstract

The invention discloses a wetland vegetation feature optimization and fusion method based on JM Relief F. The method comprises the following steps: collecting an unmanned aerial vehicle high-resolution remote sensing image in an experimental area, and meanwhile, obtaining field sample verification data; describing spectral information, texture features and spatial geometric features of various crops; calculating the expressions of different vegetations in spectral information, texture features and spatial geometric features, and counting the mean value and variance of each feature variable; establishing a JMRelief F multi-feature optimization formula, and determining the weights of the feature variables participating in classification and the separable degree of each feature variable by using the formula; and using a random forest classification algorithm to carry out fine identification on wetland vegetation in a research area, and carrying out precision verification through sample data collected in an experiment area. The method has the characteristics of wide identification range, high efficiency, low cost, short period, high precision and the like. The method can be used in the fields of protection and supervision of wetland vegetation, and can effectively improve the artificial recognition efficiency and precision.

Description

technical field [0001] The present invention designs the field of supervised classification of remote sensing images, and specifically relates to a method for selecting and merging wetland vegetation features based on JM Relief F. Background technique [0002] Wetland vegetation growth structure refers to the spatial distribution of different types of vegetation in the wetland and the growth area of ​​various types of vegetation. Vegetation growth structure reflects the health status of my country's wetlands, is the basis for analyzing wetland vegetation area and statistics of wetland vegetation types, and is also the basis for controlling and improving the wetland environment. The traditional method of obtaining wetland vegetation growth structure is to identify artificially on the spot, which cannot accurately provide the spatial distribution of various wetland vegetation, and the acquisition period is long and the efficiency is not high. With the continuous development o...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the problems existing in the prior art, the present invention provides a special optimization and fusion method for wetland vegetation based on JM Relief F, which solves the problem that the traditional method of obtaining wetland vegetation growth structure information ignores the screening of feature variables, and in the process of feature fusion The difference between the feature variables is ignored in the process, resulting in low classification accuracy

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