关键词: R语言, SfM, 高精度地形数据, 米家山, 黄河阶地

Abstract: The generation, abandonment and preservation of terraces formed in active tectonic areas are important to the analysis of the role of the tectonics and climate along the temporal variations, so it appears significant as how to use the effective quantitative methods to extract and accurately depict these terraces. The increasingly convenient acquisition of high-precision topographic data has greatly promoted the advancement of quantitative research in geoscience, making it possible to analyze mid-micro-geomorphic features on a large scale, especially by studying the temporal and spatial evolution of tectonic deformation through accurate capture of micro-geomorphic features. Over the past decade, the rapid development of LiDAR(Light Detection and Ranging)technology has provided unprecedented opportunity to access high-precision topographic data(up to centimeter in vertical and horizontal directions). However, its relatively high cost and relatively complex data processing techniques limit its widespread application in the field of earth sciences. In recent years, with the continuous innovation and advancement of topographic measurement technology, the three-dimensional structure of motion reconstruction technology(Structure from Motion, SfM)has gradually been introduced into the field of digital topographic photogrammetry due to its rapid advantage in providing quick, convenient and cost-effective methods for obtaining high-density geospatial point data. This method thus shows great potential for providing high resolution topographic data with comparable resolution and precision. Therefore, with the acquisition of more and more high-resolution terrain data in recent years, it is an important development trend to explore automated or semi-automated quantitative geomorphological analysis methods. R language, as an excellent programming language, has not been used in the geology and geomorphology, although is widely applied in medicine and meteorology based on its powerful capability of statistician and graphic visualization. In this paper, we focus on the Yellow River multi-terraces formed to the east of the Mijia Shan, which belongs to the Jingtai-Hasi Shan segment of the Haiyuan Fault. With the analysis and visualization of the high-resolution topographic data collected from the SfM in the environment of the R language, we implement the semiautomatic classification and mapping of the Yellow River multi-terraces. The method identifies 20 terraces with different elevation. Our results also imply that the younger terraces have better continuity and elongation, and the older terraces have more deformation, which can be demonstrated from their gradually notable semi-parabolic shape. Besides this, it also suggests the diverse evolution stages of the Yellow River terraces. Our study indicates that R language is expected to become an efficient tool of statistics and visualization of the high-resolution topographic data.

Key words: R language, SfM, high-resolution topographic data, Mijia Shan, Yellow River multi-terraces