Benthic cover map of Heron Reef derived from a high-spatial-resolution multi-spectral satellite image using object based image analysis

Providing accurate maps of coral reefs where the spatial scale and labels of the mapped features correspond to map units appropriate for examining biological and geomorphic structures and processes is a major challenge for remote sensing. The objective of this work is to assess the accuracy and relevance of the process used to derive geomorphic zone and benthic community zone maps for three western Pacific coral reefs produced from multi-scale, object-based image analysis (OBIA) of high-spatial-resolution multi-spectral images, guided by field survey data. Three Quickbird-2 multi-spectral data sets from reefs in Australia, Palau and Fiji and georeferenced field photographs were used in a multi-scale segmentation and object-based image classification to map geomorphic zones and benthic community zones. A per-pixel approach was also tested for mapping benthic community zones. Validation of the maps and comparison to past approaches indicated the multi-scale OBIA process enabled field data, operator field experience and a conceptual hierarchical model of the coral reef environment to be linked to provide output maps at geomorphic zone and benthic community scales on coral reefs. The OBIA mapping accuracies were comparable with previously published work using other methods; however, the classes mapped were matched to a predetermined set of features on the reef.精准绘制珊瑚礁地图，且制图要素的空间尺度与标注需匹配适用于生物与地貌结构及过程研究的制图单元，是遥感领域面临的重大挑战。本研究旨在评估：依托野外调查数据指导，通过对高空间分辨率多光谱影像开展多尺度面向对象影像分析（Object-Based Image Analysis, OBIA），生成西太平洋三处珊瑚礁的地貌区与底栖生物群落区地图的流程，其准确性与应用相关性。本研究使用了取自澳大利亚、帕劳与斐济珊瑚礁的三期QuickBird-2多光谱数据集，以及经地理配准的野外实拍照片，通过多尺度分割与面向对象影像分类，完成了地貌区与底栖生物群落区的制图。同时，本研究还针对底栖生物群落区制图，测试了逐像素分类方法。对制图结果的验证以及与既往研究方法的对比表明，多尺度面向对象影像分析流程可整合野外调查数据、作业人员的野外经验，以及珊瑚礁环境的概念层级模型，从而生成适配珊瑚礁地貌区与底栖生物群落区尺度的输出地图。本研究中面向对象影像分析的制图精度与既往采用其他方法发表的研究结果相当，但本研究的制图类别与珊瑚礁上预先设定的特征集相匹配。