Paper
3 November 2008 The study on atmospheric correction of TM image data in GuangZhou
Jianbo Xu, Zhenhua Liu, Wen Ya
Author Affiliations +
Proceedings Volume 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments; 71451H (2008) https://doi.org/10.1117/12.813032
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China
Abstract
To extract accurately quantitative information from remote sensing image, Atmospheric Correction is a necessary step. The quantitative analysis of Atmospheric Correction is still one among the important issues in application of remote sensing images. Based on the characteristics of the MODTRAN(transfer model) and the dark-object method, they are combined to remove atmospheric effects of remote sensing image in this study. In order to improve the speed of Atmospheric Correction by MODTRAN model, the dark-object method is used to acquire Path Radiance, which is one of main parameters in MODTRAN model. The new method is applied to TM image in the working area of GuangZhou. The result of the above study shows that the atmospheric correction model combining MODTRAN with the dark-object method appears to be a very hopeful approach. Compared with the MODTRAN model, the new model advances surface-atmospheric coupled efficiency. But contrasted with the dark-object method, the precision of atmospheric correction is advanced.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianbo Xu, Zhenhua Liu, and Wen Ya "The study on atmospheric correction of TM image data in GuangZhou", Proc. SPIE 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments, 71451H (3 November 2008); https://doi.org/10.1117/12.813032
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KEYWORDS
Atmospheric corrections

Atmospheric modeling

Reflectivity

Atmospheric particles

Remote sensing

Sensors

Atmospheric sensing

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