The study of water bodies such as rivers is an important problem in the remote sensing community. A meaningful set of quantitative features reflecting the geophysical properties help us better understand the formation and evolution of rivers. Typically, river sub-basins are analysed using Cartosat Digital Elevation Models (DEMs), obtained at regular time epochs. One of the useful geophysical features of a river sub-basin is that of a roughness measure on DEMs. However, to the best of our knowledge, there is not much literature available on theoretical analysis of roughness measures. In this article, we revisit the roughness measure on DEM data adapted from multiscale granulometries in mathematical morphology, namely multiscale directional granulometric index (MDGI). This measure was classically used to obtain shape-size analysis in greyscale images. In earlier works, MDGIs were introduced to capture the characteristic surficial roughness of a river sub-basin along specific directions. Also, MDGIs can be efficiently computed and are known to be useful features for classification of river sub-basins. In this article, we provide a theoretical analysis of a MDGI. In particular, we characterize non-trivial sufficient conditions on the structure of DEMs under which MDGIs are invariant. These properties are illustrated with some fictitious DEMs. We also provide connections to a discrete derivative of volume of a DEM. Based on these connections, we provide intuition as to why a MDGI is considered a roughness measure. Further, we experimentally illustrate on Lower-Indus, Wardha, and Barmer river sub-basins that the proposed features capture the characteristics of the river sub-basin.
翻译:对河流等水体的研究是遥感界的一个重要问题。一系列有意义的反映地球物理特性的量化特征有助于我们更好地了解河流的形成和演变。通常,河流次流域使用定期时代获得的Cartosat数字升降模型(DEMs)进行分析。河流次流域的有用地球物理特征之一是对DEMs进行粗糙测量。然而,据我们所知,在粗糙度测量的理论分析方面,没有太多文献资料。在文章中,我们重新审视了从数学形态学的多尺度颗粒特征中调整的DEM数据的粗糙度测量。在数学形态学中,即多尺度方向悬浮指数(MDGI)中,对河流次流域进行了典型分析,以获得灰度图像的形状大小分析。在早先的著作中,引入了MDGIS的物理特征是沿具体方向测量河流次流域的粗糙度。此外,MDGIS可以高效地进行计算,而且已知是用于河流次盆地分类的有用特征。在本文章中,我们从数学角度分析了多层次的磁度,我们从DGDFDF的离系的深度关系中了解到,我们用了一些底层数据结构。我们从DFDDFDF的模型中了解到了这些底系的底系。我们不具有充分的。我们从DFDDFDFDF值结构。我们从DFDFDFDF的底。我们不具有充分的。