Multi-feature optimization and fusion method for crop planting structure extraction

Abstract

The invention discloses a multi-feature optimization and fusion method for crop planting structure extraction, and the method comprises the steps: collecting a time sequence satellite remote sensing data set which is not greater than the monthly scale, and completing the pre-obtaining of sample data in a research region; describing spectral and texture characteristics of various crops; calculatingexpressions of different samples on spectral information, vegetation indexes, texture characteristic quantities and the like, counting mean values and variances of the characteristic quantities, andcalculating distinguishable capabilities of the different samples on the characteristic quantities; establishing a multi-feature optimization formula, and determining feature quantities participatingin classification and proportions of the feature quantities in the classification process by utilizing the formula; constructing a new image; and performing fine identification on the crop type of theresearch area by utilizing a random forest classifier, generating a space-time distribution thematic map of the crops, and verifying the precision. According to the method, the problem that the timecomplexity and the computer running speed are increased due to the fact that screening of the classification characteristic quantity is ignored in a traditional remote sensing information extraction method is solved.

Description

technical field [0001] The invention relates to the field of remote sensing planting structure monitoring, in particular to a multi-feature optimization and fusion method for crop planting structure extraction. Background technique [0002] Crop planting structure refers to the compilation of information such as the spatial distribution of different types of crops in the region and the planting area of ​​each type, and finally presents the crop information intuitively in the form of maps. Planting structure information reflects people's allocation of land resources, is the basis for analyzing crop planting area and counting crop types, and is also the basis for rational adjustment and optimization of land resources. The traditional method of obtaining crop planting structure is to report layer by layer from bottom to top, which cannot provide accurate spatial distribution information of crop categories, and there is a certain lag in time. With the development of science and...

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Problems solved by technology

[0004] In order to solve the problems existing in the prior art, the present invention provides a multi-feature optimization and fusion method for crop planting structure extraction, which solves the problem that the traditional method of obtaining crop planting structure information ignores the screening of classification feature quantities, and in the fusion process The difference between the amount of feature information is ignored, which increases the time complexity and affects the classification accuracy and other issues.

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