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首页> 外文会议>Asian conference on remote sensing;ACRS >REMOTE-SENSED MAPPING OF SEAGRASS DISTRIBUTION IN PALK BAY, SRI LANKA, USING HIGH SPATIAL RESOLUTION WORLDVIEW-2 SATELLITE DATA
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REMOTE-SENSED MAPPING OF SEAGRASS DISTRIBUTION IN PALK BAY, SRI LANKA, USING HIGH SPATIAL RESOLUTION WORLDVIEW-2 SATELLITE DATA

机译：使用高空间分辨率WORLDVIEW-2卫星数据对斯里兰卡帕尔克湾海域分布进行遥感制图

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This study incorporates field observations and high spatial resolution WV-2 imagery processing techniques to provide an assessment of shallow coastal marine seagrass beds in Palk Bay, North-Westem coast of Sri Lanka. The main objective of this study is to influence decision making and coastal planning in Sri Lanka with the increased knowledge on the seagrass habitats in Palk Bay with special reference to Dugong conservation. Field observation were conducted in once a month during 2015 to 2016 and methods included free diving, monitoring transect lines, quantify quadrats, and underwater photography techniques. Common species encountered in study areas were Enhalus acoroides, Cymodocea rotundata, Cymodocea serrulata and Halodule pinifolia. Cloud free WV-2 satellite imageries of 15~(th) June 2015 and 11~(th) February 2016 were selected as remote sensing data sources. After image pre-processing, supervised image classifications were performed using maximum likelihood, minimum distance to means, and spectral angle mapper methods to compare relative accuracies in mapping seagrass coverage. The maximum likelihood classification produced the highest overall accuracy of 94%. The spectral angle mapper yielded the lowest accuracy due to the predominant influence of water-column optical properties on the apparent spectral characteristics of seagrass and sand bottom. The results achieved by our classification methodology were validated with visual interpretation and field data. The combination of in-situ data and three classification methods resulted in highly accurate classification outcomes that showed the distribution patterns of seagrass of the study area. Based on the results, we conclude that eight-band high resolution multispectral WV-2 satellite imagery has great potential for mapping and monitoring seagrass beds in shallow coastal waters with large-scale coverage. Thus, the primary results of this study provide useful baseline information that is necessary for marine-conservation strategic planning incorporated to protecting feeding grounds of dugongs around the North-Western coast of Sri Lanka.
机译：这项研究结合了野外观察和高空间分辨率WV-2影像处理技术，以评估斯里兰卡西北海岸Palk湾的浅海海洋海草床。这项研究的主要目的是通过增加对Palk湾海草生境的了解，特别是对儒艮的保护，来影响斯里兰卡的决策和海岸计划。在2015年至2016年期间，每月进行一次野外观察，方法包括自由潜水，监测样线，量化四边形和水下摄影技术。在研究区域遇到的常见物种是En虫（Enhalus acoroides），圆环夜蛾（Cymodocea rotundata），细夜蛾（Cymodocea serrulata）和羽梭（Halodule pinifolia）。选择2015年6月15日至2016年2月11日的无云WV-2卫星图像作为遥感数据源。在图像预处理之后，使用最大似然，最小距离均值和光谱角度映射器方法对有监督的图像进行分类，以比较绘制海草覆盖度的相对精度。最大似然分类产生了94％的最高总体准确性。由于水柱光学特性对海草和沙底的表观光谱特性有主要影响，因此光谱角映射器产生的精度最低。通过我们的分类方法获得的结果已通过视觉解释和现场数据进行了验证。现场数据和三种分类方法的结合产生了高度准确的分类结果，显示了研究区域海草的分布模式。根据结果​​，我们得出结论，八波段高分辨率多光谱WV-2卫星图像具有很大的潜力，可用于在大范围覆盖的浅海沿海水域绘制和监测海草床。因此，这项研究的主要结果提供了有用的基线信息，这对于保护斯里兰卡西北海岸儒艮的觅食地的海洋保护战略规划是必不可少的。

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