Characteristics of the gravel size and potassium in the Ejin Alluvial Fan from remote sensing images and stratigraphic section

35th International Symposium on Remote Sensing of Environment

地球科学;生态环境科学

Zhang, Lu^1 ; Guo, Huadong^1 ; Wang, Qinjun^1

Key Laboratory of Digital Earth, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, China^1

关键词: Geological information;    Paleoenvironmental change;    Qinghai Tibet plateau;    Remote sensing data;    Remote sensing images;    Spatial observation;    Surface distributions;    Surface information;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/17/1/012216/pdf
DOI  :  10.1088/1755-1315/17/1/012216

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The Ejin Alluvial Fan (EAF), located in the north-west of China, is an important recorder of both paleoclimatic and tectonic information of the north margin of the Qinghai-Tibet Plateau. Remote sensing technics, including optical and microwave sensors, have been the key spatial observation tools to extract the surface information related to the paleoenvironment. In this paper, the gravel size and chemical element potassium K distributions of the EAF were obtained from RadarSat-2 Synthetic Aperture Radar (SAR) data and LandSat TM optical data, respectively. In addition, the stratigraphic section of the EAF was established and the corresponding geological information in the vertical direction with different periods was obtained. Combining the geological survey information and surface distribution information, it can be concluded as follows. 1) The EAF covers an area of above 30,000 km2and may be the largest arid and semi-arid alluvial fan in the world based on the remote sensing survey. 2) Some surface parameters which are related to the paleoenvironmental change can be obtained from remote sensing data, such as the gravel size and potassium K parameters. 3) The forming process of the EAF and the corresponding environments will be understood deeply, combining the paleoenvironmental related parameters derived from remote sensing data and the geologic survey data.