首页> 外文会议>SPIE Conference on Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications >Mangrove Recognition and Extraction Using Multispectral Remote Sensing Data in Beibu Gulf
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Mangrove Recognition and Extraction Using Multispectral Remote Sensing Data in Beibu Gulf

机译:红树林识别与北部海湾多光谱遥感数据的提取

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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.
机译:北武海湾是中国广西的主要红树林增长区。北武湾的Tiehan港被选为这项研究的研究领域。基于由HJ-1A卫星的多光谱遥感图像中的VI / NIR带形成的像素光谱反射角,提出了一种红带角植被指数(RAVI),这将有利于在陆地和水上分离植被。使用RAVI和像素带反射标准偏差(BSTDEV)的组合形成红树林判断标准。基于索引分析和生长区域的生成,建立了红树林提取模式,从而有效地将红树林空间分布从稀疏到密集的覆盖范围和沿北部海岸线的海岸线捕获。

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