Fine method for global vegetation classification based on multi-temporal remote sensing data and spectroscopic data

Abstract

Provided is a fine method for global vegetation classification. The method comprises: firstly, obtaining spectroscopic data and remote sensing data of vegetation with a first main component; secondly, obtaining an area where land classification changes through the remarkable statistical test of average values; thirdly, performing minimum range monitoring classification of the area where land classification changes by taking an area where land classification doesn't change as a monitoring classification sample; fourthly, performing minimum range monitoring classification of a vegetation part of obtained data of new land classification data by utilizing spectroscopic data to obtain fine vegetation classification data; and finally, combining the obtained fine vegetation classification data with the non-vegetation data to obtain a fine vegetation classification result map. The method is applicable to departments of territorial resources, agriculture, forestry, and the like for fast updating a huge amount of land and vegetation classification data, and for fast accurately monitoring condition of vegetation growth and situation of change of land use.

Description

technical field [0001] A global fine vegetation classification method based on multi-temporal remote sensing data and spectral data belongs to the field of digital image processing, and particularly relates to vegetation coverage type change detection technology and digital image processing technology. Background technique [0002] Vegetation coverage type refers to the surface vegetation coverage formed due to the natural attributes of the land or affected by human activities, such as forests, grasslands, crops, bare land, etc. Fine vegetation classification is a more detailed description of vegetation coverage types, such as subdividing forest coverage types into deciduous broad-leaved forests and evergreen coniferous forests, and subdividing crop types into rice, wheat, corn, etc. . Fine vegetation classification is an important part of land classification research. Changes in vegetation types largely affect changes in other properties of the earth system, such as ecosys...

AI Technical Summary

Problems solved by technology

[0010] The invention provides a global fine vegetation classification method based on multi-temporal remote sensing data and spectral data, which is used to solve the problem of poor universality of classification algorithms in different regions of the world caused by the existing vegetation classification technology relying only on remote sensing images as a data source, and the existing vegetation classification The time resolution of classification products is low, and it is impossible to quickly and on-demand obtain fine vegetation classification products in any region of the world

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