Urban light pollution identification method based on fusion of unmanned aerial vehicle image and satellite image

Through the fusion method of drone images and satellite remote sensing images, urban light pollution is identified, which solves the problem that traditional monitoring methods cannot obtain light environment data on a large scale, and achieves high-precision light pollution monitoring and evaluation.

CN119693692AActive Publication Date: 2025-03-25TIANJIN UNIV
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Patent Information

Application Number
CN202411744373.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-30
Publication Date
2025-03-25
Estimated Expiration
2044-11-30

AI Technical Summary

Technical Problem

Traditional methods of monitoring urban light pollution cannot obtain light environment data on a large scale, there are large errors, and it is impossible to easily obtain all light environment data within the visible range of the human eye, resulting in the incompleteness of the research.

Method used

The fusion method of drone images and satellite remote sensing images is used to identify urban light pollution through image analysis, brightness measurement, data calibration and determination of light pollution risk levels. Specific steps include the fusion of the drone image and the satellite remote sensing image, the analysis and calibration of image data, and the determination of the light pollution risk level based on the image brightness information.

Benefits of technology

It has achieved large-scale monitoring of urban light environment, improved the accuracy of data collection, reduced labor and time costs, and can objectively and accurately evaluate the degree of light pollution, providing strong data support for light pollution control and management.

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Abstract

The invention relates to the technical field of image processing, in particular to an unmanned aerial vehicle image and satellite image fused urban light pollution identification method, which comprises the following steps of S1, fusing an unmanned aerial vehicle image and a satellite remote sensing influence; s2, carrying out image analysis and brightness measurement on the obtained fused image; s3, calibrating image brightness information data measured by the fused image; and S4, judging and identifying a light pollution risk level according to the image brightness information. The method provides a method path for monitoring the urban light environment in a large range, satellite remote sensing images are fused through the unmanned aerial vehicle, the resolution of the images is enhanced, and the efficiency of monitoring the overall brightness and illumination data of the urban area is improved. The accuracy of data acquisition is improved, and the labor cost and the time cost are reduced.
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Citation Information

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