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Detection of Seagrass Distribution Changes from 1991 to 2006 in Xincun Bay Hainan with Satellite Remote Sensing

机译:卫星遥感监测海南新村湾海草分布1991-2006年变化

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摘要

Seagrass distribution is a very important index for costal management and protection. Seagrass distribution changes can be used as indexes to analyze the reasons for the changes. In this paper, in situ hyperspectral observation and satellite images of QuickBird, CBERS (China Brazil Earth Resources Satellite data) and Landsat data were used to retrieve bio-optical models and seagrass (Enhalus acoroides, Thalassia hemperichii) distribution in Xincun Bay, Hainan province, and seagrass distribution changes from 1991 to 2006 were analyzed. Hyperspectral results showed that the spectral bands at 555, 635, 650 and 675 nm are sensitive to leaf area index (LAI). Seagrass detection with QuickBird was more accurate than that with Landsat TM and CBERS; five classes could be classified clearly and used as correction for seagrass remote sensing data from Landsat TM and CBERS. In order to better describe seagrass distribution changes, the seagrass distribution area was divided as three regions: region A connected with region B in 1991, however it separated in 1999 and was wholly separated in 2001; seagrass in region C shrank gradually and could not be detected in 2006. Analysis of the reasons for seagrass reduction indicated it was mainly affected by aquaculture and typhoons and in recent years, by land use changes.
机译:海草分布是海岸管理和保护的重要指标。海草分布变化可以用作分析变化原因的指标。本文利用QuickBird的原位高光谱观测和卫星图像,CBERS(中国巴西地球资源卫星数据)和Landsat数据,检索了海南省新村湾的生物光学模型和海草(钩形棘,拟南半球藻)。 ,并分析了1991年至2006年海草的分布变化。高光谱结果表明,在555、635、650和675 nm处的光谱带对叶面积指数(LAI)敏感。使用QuickBird进行海草检测比使用Landsat TM和CBERS进行检测更为准确。可以清楚地将5类分类为Landsat TM和CBERS的海草遥感数据校正。为了更好地描述海草的分布变化,将海草的分布区域划分为三个区域:1991年A区与B区相连,但1999年分离,2001年完全分离。 C区海草逐渐萎缩,2006年无法检测到。对海草减少的原因的分析表明,海草的减少主要受到水产养殖和台风的影响,近年来受到土地用途变化的影响。

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