Mangrove recognition and extraction using multispectral remote sensing data in Beibu Gulf

Qingjiu Tian; Shanshan Li

doi:10.1117/12.2324701

23 October 2018 Mangrove recognition and extraction using multispectral remote sensing data in Beibu Gulf

Qingjiu Tian, Shanshan Li

Author Affiliations +

Proceedings Volume 10780, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VII; 107800C (2018) https://doi.org/10.1117/12.2324701
Event: SPIE Asia-Pacific Remote Sensing, 2018, Honolulu, Hawaii, United States

Abstract

Beibu Gulf is the main mangrove growth district in Guangxi province of China. Tieshan Harbor in the Beibu Gulf was chosen as the study area for this research. Based on the pixel spectral reflectance angle formed by the VIS/NIR bands in the multispectral remote sensing images of HJ-1A satellite, a red band angle vegetation index (RAVI) was proposed, which would be beneficial for separating vegetation on land and water. The mangrove judging standard was formed using a combination of RAVI and pixel band reflectance standard deviation (BStdev). Based on the indices analysis and growth area generation, the mangrove extraction mode was established, which effectively captured the mangrove spatial distribution from sparse to dense coverage and in different shapes along the coastline of Beibu Gulf.

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Qingjiu Tian and Shanshan Li "Mangrove recognition and extraction using multispectral remote sensing data in Beibu Gulf", Proc. SPIE 10780, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications VII, 107800C (23 October 2018); https://doi.org/10.1117/12.2324701

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KEYWORDS

Vegetation

Reflectivity

Charge-coupled devices

Remote sensing

Data centers

Earth observing sensors

RGB color model

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