The object-based against pixel-based image analysis approaches were assessed for lithological mapping in a geologically complex terrain using Visible Near Infrared (VNIR) bands of WorldView-3 (WV-3) satellite imagery. The study area is Hormuz Island, southern Iran, a salt dome composed of dominant sedimentary and igneous rocks. When performing the object-based image analysis (OBIA) approach, the textural and spectral characteristics of lithological features were analyzed by the use of support vector machine (SVM) algorithm. However, in the pixel-based image analysis (PBIA), the spectra of lithological end-members, extracted from imagery, were used through the spectral angle mapper (SAM) method. Several test samples were used in a confusion matrix to assess the accuracy of classification methods quantitatively. Results showed that OBIA was capable of lithological mapping with an overall accuracy of 86.54% which was 19.33% greater than the accuracy of PBIA. OBIA also reduced the salt-and-pepper artifact pixels and produced a more realistic map with sharper lithological borders. This research showed limitations of pixel-based method due to relying merely on the spectral characteristics of rock types when applied to high-spatial-resolution VNIR bands of WorldView-3 imagery. It is concluded that the application of an object-based image analysis approach obtains a more accurate lithological classification when compared to a pixel-based image analysis algorithm.

使用WorldView-3（WV-3）卫星图像的可见近红外（VNIR）波段，评估了基于对象与基于像素的图像分析方法在地质复杂地形中的岩性作图。研究区域是伊朗南部的霍尔木兹岛，它是由主要的沉积岩和火成岩组成的盐丘。在执行基于对象的图像分析（OBIA）方法时，使用支持向量机（SVM）算法分析了岩性特征的质地和光谱特征。但是，在基于像素的图像分析（PBIA）中，通过光谱角度映射器（SAM）方法使用了从图像中提取的岩性末端成员的光谱。在混淆矩阵中使用了几个测试样本，以定量评估分类方法的准确性。结果表明，OBIA能够进行岩性制图，其总精度为86.54％，比PBIA的精度高19.33％。OBIA还减少了盐和胡椒的伪像像素，并生成了更真实的地图，具有更清晰的岩性边界。这项研究表明，在将像素应用于WorldView-3影像的高空间分辨率VNIR波段时，由于仅依赖岩石类型的光谱特征，因此基于像素的方法存在局限性。结论是，与基于像素的图像分析算法相比，基于对象的图像分析方法的应用获得了更准确的岩性分类。OBIA还减少了盐和胡椒的伪像像素，并生成了更真实的地图，具有更清晰的岩性边界。这项研究表明，在将像素应用于WorldView-3影像的高空间分辨率VNIR波段时，由于仅依赖岩石类型的光谱特征，因此基于像素的方法存在局限性。结论是，与基于像素的图像分析算法相比，基于对象的图像分析方法的应用获得了更准确的岩性分类。OBIA还减少了盐和胡椒的伪像像素，并生成了更真实的地图，具有更清晰的岩性边界。这项研究表明，在将像素应用于WorldView-3影像的高空间分辨率VNIR波段时，由于仅依赖岩石类型的光谱特征，因此基于像素的方法存在局限性。结论是，与基于像素的图像分析算法相比，基于对象的图像分析方法的应用获得了更准确的岩性分类。