首页> 外文会议>Asian conference on remote sensingACRS >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,斯里兰卡海湾海湾海湾分布的遥感映射

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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:本研究包括现场观测和高空间分辨率WV-2图像处理技术,以评估斯里兰卡北方海岸Palk海湾的浅沿海海洋海草床。本研究的主要目的是影响斯里兰卡的决策和沿海规划,随着儒艮守恒的特别参考,对PALK Bay的海草栖息地增加了知识。田间观察在2015年至2016年期间每月一次进行,方法包括自由潜水,监测横向线,量化四浆,以及水下拍摄技术。研究区遇到的常见物种是Enhalus毒性,Cymodea rotundata,Cymodocea Serrulata和Halodule Pinifolia。 2015年6月15〜(Th)的云WV-2卫星成像仪于2016年2月至11〜(Th)被选为遥感数据来源。在图像预处理之后,使用最大似然,到尺寸的最小距离和光谱角映射器方法进行监督图像分类,以比较映射海草覆盖的相对精度。最大似然分类产生了94%的最高总精度。由于水柱光学性质对海草和沙底的表观光谱特性,光谱角映射器产生最低精度。通过我们的分类方法实现的结果验证了视觉解释和现场数据。原位数据和三种分类方法的组合导致了高度准确的分类结果,显示了研究区域的海草的分布模式。基于结果,我们得出结论,八频高分辨率多光谱WV-2卫星图像具有巨大的潜力,可在大规模覆盖范围内在浅沿海水域中进行浅沿海地。因此,本研究的主要结果提供了用于海洋保护战略规划所必需的有用的基线信息,该计划纳入斯里兰卡西北海岸南北海岸的儒艮饲养场。

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