Method and system for recognizing cotton area in Xinjiang on basis of satellite image data

Abstract

The invention discloses a method and a system for recognizing a cotton area in Xinjiang on the basis of satellite image data, belonging to the technical field of remote-sensing crop classification andrecognition. The invention solves the problem of low recognition accuracy of the cotton area in the prior art. The method for recognizing the cotton area in Xinjiang on the basis of the satellite image data comprises the following steps: acquiring the satellite image data of a seedling stage, a flowering and boll setting stage and a harvesting period of cotton, and respectively performing data pre-processing on the satellite image data of the seedling stage, the flowering and boll setting stage and the harvesting period of the cotton; performing normalized differential vegetation index calculation on the processed satellite image data so as to obtain a normalized vegetation index value NDVI; determining a vegetation area and a non-vegetation area according to the normalized vegetation index value NDVI, determining a crop area according to the difference in spectral reflectance between the crop area and a non-crop area in the vegetation area, and determining a cotton planting area according to the difference in the spectral reflectance difference values between the cotton area and the non-cotton area in the crop area. The method provided by the invention the recognition accuracy ofthe cotton area.

Description

technical field [0001] The invention relates to the technical field of remote sensing crop classification and recognition, in particular to a Xinjiang cotton region recognition method and system based on satellite image data. Background technique [0002] Cotton is one of the main sources of economic income for farmers in the Xinjiang Uygur Autonomous Region, and it is the pillar industry of large-scale agriculture in our region. Timely and accurate acquisition of spatial distribution information of cotton in Xinjiang is of great importance for guiding agricultural production, rationally allocating resources, and solving safety problems in the cotton industry. significance. [0003] At present, the extraction of cotton spatial distribution information in the industry is mainly based on the decision tree classification method, but the existing cotton decision tree classification method is too complicated, using too many parameters, it is difficult to understand, and requires ...

AI Technical Summary

Problems solved by technology

[0003] At present, the extraction of cotton spatial distribution information in the industry is mainly based on the decision tree classification method, but the existing cotton decision tree classification method is too complicated, using too many parameters, it is difficult to understand, and requires high knowledge of remote sensing and geosciences for classifiers. Leading to failure to promote and apply on a large scale

At the same time, it is difficult to obtain relevant data, and the accuracy of the data is difficult to guarantee

Part of the method process uses some empirical values, and a reasonable threshold cannot be set according to the regional characteristics. The accuracy of the result data is not high, which makes the recognition accuracy of the cotton area not high.

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