Automatic roadside tree extraction method based on geographical national condition data and image classification

Abstract

The invention discloses a roadside tree automatic extraction method based on geographic national condition data and image classification, and the method is characterized in that the method comprises the following steps: exporting road network data from a geographic national condition database, constructing a road surface according to the road network data, and constructing a road recognition region according to the road surface; the geographic national condition database derives forest map spots, and the forest map spots and the road recognition area are combined to determine a first area and/or a to-be-supplemented area; obtaining a roadside tree area from the first area according to the roadside tree judgment step, and/or obtaining a supplementary roadside tree area from the to-be-supplemented area according to the roadside tree judgment step; performing information extraction on the reserved roadside tree area and/or the supplementary roadside tree area; the method has the advantages that the situations of effective information loss and data redundancy are prevented, the roadside tree area can be rapidly extracted in forest coverage rate calculation through combination of geographic national condition data and various images, the statistical time and the information extraction time are shortened, and the calculation cost is reduced.

Description

technical field [0001] The invention belongs to the field of remote sensing image data processing and information extraction, and in particular relates to an automatic extraction method for roadside trees based on geographic national conditions data and image classification. Background technique [0002] Side trees (also known as roadside trees) refer to all kinds of bamboo and wood planted in houses, villages, roads, water systems, etc. with an area of ​​less than 0.067 hectares. As an important part of forest coverage and forest area, surrounding trees can not only increase forest carbon sequestration and develop a low-carbon economy, but also ensure the healthy development of forest resources and enhance the potential of carbon sinks. They play an important role in environmental regulation. and social service functions. And with the increase of urban area and population density, Bush and DzifaAdimle Puplampu and others believe that urban green space composed of trees all...

AI Technical Summary

Problems solved by technology

[0005] 1. Less consideration is given to the selection method of remote sensing image bands, and there are problems of losing effective information and data redundancy

[0006] 2. In the calculation of

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