首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Detection of shallow subtidal corals from IKONOS satellite and QTC View (50, 200 kHz) single-beam sonar data (Arabian Gulf; Dubai, UAE)
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Detection of shallow subtidal corals from IKONOS satellite and QTC View (50, 200 kHz) single-beam sonar data (Arabian Gulf; Dubai, UAE)

机译:通过IKONOS卫星和QTC View(50、200 kHz)单波束声纳数据(阿拉伯湾;阿联酋迪拜)检测浅层潮下珊瑚

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摘要

We compared the results of seafloor classifications with special emphasis on detecting coral versus non-coral areas that were obtained from a 401334-m pixel-resolution multispectral IKONOS satellite image and two acoustic surveys using a QTC View Series 5 system on 50 and 200 kHz signal frequency. A detailed radiative transfer model was obtained by in situ measurement of optical parameters that then allowed calibration of the IKONOS image against in situ optical measurements and a series of ground-truthing points. Eight benthic classes were distinguished optically with an overall accuracy of 69% and a Tau index T of 65. The classification of the IKONOS image allowed discrimination of three different coral assemblages (dense live, dense dead, sparse), which were confirmed by ground-truthing. Data evaluation of the acoustic surveys involved culling of datapoints with <90% confidence and <30% probability, two QTC-provided statistics, and the deletion of data classes without clear spatial patterns (visualized by single-class trackplots). The deletion of these ubiquitous classes was necessary in order to obtain any clearly interpretable spatial pattern of echo classes after the surveys were resampled to a regular grid and areas between the lines interpolated using a nearest neighbor algorithm. The 50 kHz acoustic seafloor classification was able to determine two classes (unconsolidated sand versus hardground) but was not able to determine corals. The 200 kHz survey determined high rugosity (=corals and sand ripples) versus low rugosity (=flat areas) but was not able to determine consolidated and unconsolidated sediments. Classes were extrapolated to the entire grid and polygons obtained from the two surveys were combined to provide maps containing four classes (rugose hardground=coral, flat hardground=rock, rugose softground=ripples and algae, flat softground=bare sand). Compared with the classification map derived from the IKONOS image, they were 66% accurate (7=59) when the most highly processed data (only selected classes, >90% accuracy and >30% probability) were used, and 60% accurate (T=53) when less processed data (selcted classes only, all data) were used. Accuracy against ground-truthing points of the most highly processed dataset was 56% (T=46). These results indicate that results from optical and acoustic surveys have some degree of commonality. Therefore, there is a potential to produce maps outlining coral areas from optical remote-sensing in shallow areas and acoustic methods in adjacent deeper areas beyond optical resolution with the limitation that acoustic maps will resolve fewer habitat classes and have lower accuracy.
机译:我们比较了海底分类的结果,特别着重于检测从401334-m像素分辨率多光谱IKONOS卫星图像获得的珊瑚与非珊瑚区域,以及两次使用QTC View Series 5系统对50和200 kHz信号进行的声学测量频率。通过对光学参数进行原位测量,可以获得详细的辐射传递模型,然后可以根据原位光学测量结果和一系列地面真点对IKONOS图像进行校准。光学区分了八个底栖类,总精度为69%,Tau指数T为65。IKONOS图像的分类可以区分三种不同的珊瑚组合(密集的活体,密集的死角,稀疏的),并通过地面确认。诚实。声学勘测的数据评估涉及以90%的置信度和<30%的概率收集数据点,两个QTC提供的统计数据以及删除没有清晰空间模式的数据类别(通过单类轨迹图可视化)。为了将回波类别重新采样到规则网格并使用最近邻算法内插线之间的区域后,为了获得回波类别的任何可清晰解释的空间模式,必须删除这些普遍存在的类别。 50 kHz的声学海底分类能够确定两个类别(未固结的沙子与硬土地基),但无法确定珊瑚。 200 kHz的测量确定了较高的皱纹度(=珊瑚和沙子波纹)与较低的皱纹度(=平坦区域),但无法确定固结和未固结的沉积物。将类别外推到整个网格,并结合两次调查获得的多边形,以提供包含四个类别的地图(崎hard的硬地=珊瑚,平坦的硬地=岩石,皱纹的软地=波纹和藻类,平坦的软地=裸砂)。与从IKONOS图像获得的分类图相比,使用最高处理的数据(仅选定的类别,准确度> 90%和概率> 30%)时,它们的准确度是66%(7 = 59),而准确度是60%(当使用较少处理的数据(仅选择的类,所有数据)时,T = 53)。最高处理数据集对地面真相的准确性为56%(T = 46)。这些结果表明,光学和声学调查的结果具有一定程度的共性。因此,除了光学分辨率外,还有可能绘制出从浅层区域的光学遥感中勾勒出珊瑚区域的轮廓图,以及在较深的区域中从声学方法中勾勒出珊瑚区的轮廓图,其局限性在于,其能够分辨出更少的栖息地类别,并且精度较低。

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