Abstract

Wetland vegetation classification often treated the saltmarsh as a single type of land-cover (LCT). Mapping the dynamic and spatially complex coastal zones using optical remote sensing is still challenging. This study firstly analyzed the spectral properties of target objects generated by Landsat 8 (OLI), formulated new spectral indices and then proposes a rule-based approach to mapping five vegetated (saltmarsh, seagrass, mangrove, non-mangrove forest, and agricultural land) and three non-vegetated (wet sand, saltpan, and built-up areas) LCT in the study area, that is, large coasts located in the south-eastern coasts of Bangladesh. The thresholds of spectral indices were selected from the newly introduced spectral indices over the method development site (Bakkhali estuary). The rule-based LCT classification process followed a set of cascade rules of image thresholding and masking, based on a hierarchical tree in order to generate detailed thematic maps of saltmarsh land-cover. Overall accuracy (OA) and Kappa coefficient (K) of rule-based approach were 84.6% and 0.821, respectively. The reliability and robustness of the approach was tested over two independent external validation test sites: Karnaphuli river estuary and Teknaf peninsula and consistent accuracy results achieved: OA = 81.7% (K = 0.787) and OA = 84.6% (K = 0.821) respectively.

摘要

湿地植被分类通常将盐沼视为单一类型的土地覆盖 (LCT)。使用光学遥感绘制动态和空间复杂的海岸带仍然具有挑战性。本研究首先分析了 Landsat 8 (OLI) 生成的目标物体的光谱特性，制定了新的光谱指数，然后提出了一种基于规则的方法来绘制五种植被（盐沼、海草、红树林、非红树林和农田）研究区的三个无植被（湿沙、盐田和建成区）LCT，即位于孟加拉国东南沿海的大海岸。光谱指数的阈值是从方法开发现场（Bakkhali 河口）上新引入的光谱指数中选择的。基于规则的 LCT 分类过程遵循一组基于分层树的图像阈值化和掩蔽级联规则，以生成盐沼土地覆盖的详细专题图。基于规则的方法的总体准确率 (OA) 和 Kappa 系数 (K) 分别为 84.6% 和 0.821。该方法的可靠性和稳健性在两个独立的外部验证测试站点进行了测试：Karnaphuli 河口和 Teknaf 半岛，并获得了一致的准确度结果：OA = 81.7% (K  = 0.787) 和 OA = 84.6% ( K  = 0.821)。