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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Multi-site evaluation of IKONOS data for classification of tropical coral reef environments
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Multi-site evaluation of IKONOS data for classification of tropical coral reef environments

机译:IKONOS数据的多站点评估,以对热带珊瑚礁环境进行分类

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Ten IKONOS images of different coral reef sites distributed around the world were processed to assess the potential of 4-m resolution multispectral data for coral reef habitat mapping. Complexity of reef environments, established by field observation, ranged from 3 to 15 classes of benthic habitats containing various combinations of sediments, carbonate pavement, seagrass, algae, and corals in different geomorphologic zones (forereef, lagoon, patch reef, reef flats). Processing included corrections for sea surface roughness and bathymetry, unsupervised or supervised classification, and accuracy assessment based on ground-truth data. IKONOS classification results were compared with classified Landsat 7 imagery for simple to moderate complexity of reef habitats (5-11 classes). For both sensors, overall accuracies of the classifications show a general linear trend of decreasing accuracy with increasing habitat complexity. The IKONOS sensor performed better, with a 15-20% improvement in accuracy compared to Landsat. For IKONOS, overall accuracy was 77% for 4-5 classes, 71% for 7-8 classes, 65% in 9-11 classes, and 53% for more than 13 classes. The Landsat classification accuracy was systematically lower, with an average of 56% for 5-10 classes. Within this general trend, inter-site comparisons and specificities demonstrate the benefits of different approaches. Pre-segmentation of the different geomorphologic zones and depth correction provided different advantages in different environments. Our results help guide scientists and managers in applying IKONOS-class data for coral reef mapping applications.
机译:对分布在世界各地的不同珊瑚礁地点的十张IKONOS图像进行了处理,以评估4 m分辨率多光谱数据在珊瑚礁栖息地制图中的潜力。通过现场观察发现,礁石环境的复杂性介于3至15类底栖生境中,其中包含不同地貌区域(前礁,泻湖,斑块礁,礁滩)的沉积物,碳酸盐路面,海草,藻类和珊瑚的各种组合。处理包括对海面粗糙度和测深的更正,无监督或有监督的分类以及基于地面真实数据的准确性评估。将IKONOS分类结果与分类的Landsat 7影像进行比较,以比较简单地确定珊瑚礁栖息地的复杂程度(5-11类)。对于这两种传感器,分类的总体精度均显示出总体线性趋势,即随着栖息地复杂性的增加,精度降低。与Landsat相比,IKONOS传感器的性能更好,准确度提高了15-20%。对于IKONOS,4-5级的整体准确度为77%,7-8级的为71%,9-11级的为65%,13级以上的为53%。 Landsat的分类准确性系统地较低,5-10个类别的平均准确性为56%。在这种总体趋势下,站点间的比较和特异性证明了不同方法的好处。在不同的环境下,对不同地貌区域进行预分段和深度校正可提供不同的优势。我们的结果有助于指导科学家和管理人员将IKONOS级数据应用于珊瑚礁制图应用程序。

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