Vegetation information extraction in urban area based on high resolution remote sensing images

Yu Wang; Xiaoyong Wang; Hongyan He; Guoliang Tian

doi:10.1117/12.2547659

18 December 2019 Vegetation information extraction in urban area based on high resolution remote sensing images

Yu Wang, Xiaoyong Wang, Hongyan He, Guoliang Tian

Proceedings Volume 11341, AOPC 2019: Space Optics, Telescopes, and Instrumentation; 113411Q (2019) https://doi.org/10.1117/12.2547659
Event: Applied Optics and Photonics China (AOPC2019), 2019, Beijing, China

Abstract

The spatial information of high-resolution remote sensing images is more abundant, and the expression of ground object information in detail is clearer. Vegetation is a component of the environment and the most important component of terrestrial ecosystems. Therefore, vegetation information extraction from remote sensing images is particularly significant. This paper takes Shanghai Pudong New Area as the research area, adopts threshold classification method and membership function classification method to extract vegetation information, and introduces normalized vegetation index as feature to extract vegetation information from WorldView-3 satellite remote sensing image. The results show that the accuracy of vegetation information extraction based on membership function classification method is higher. The classification accuracy of typical vegetation area is higher than 90%, and the Kappa coefficient is higher than 0.86, which can significantly reduce the fragmentation caused by classification. At the same time, high-resolution remote sensing images show great potential for the extraction of vegetation information in urban areas.

Citation Download Citation

Yu Wang, Xiaoyong Wang, Hongyan He, and Guoliang Tian "Vegetation information extraction in urban area based on high resolution remote sensing images", Proc. SPIE 11341, AOPC 2019: Space Optics, Telescopes, and Instrumentation, 113411Q (18 December 2019); https://doi.org/10.1117/12.2547659

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