Exploration of Landslide Geomorphology and Inventory Construction in Minhe County, Qinghai, China, Based on Google Earth Remote Sensing Imagery
Qinxia Wang, Chong Bang Xu, Jixiang Xu
National Institute of Natural Hazards Ministry of Emergency Management of the People's Republic of China Institute of Geology, China Earthquake Administration
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摘要与影响
The upper reaches of the Yellow River, located at the northeastern edge of the Qinghai‐Tibet Plateau in China, are characterized by intense tectonic activity and widespread landslide geomorphology. Creating a detailed and objective map of landslide geomorphology in this region is crucial for understanding the development of landslides. However, the availability of high‐quality landslide inventories in this area is limited, hindering a comprehensive understanding of landslide development and scientific landslide disaster prevention efforts. This study utilized multi‐temporal high‐resolution remote sensing imagery provided by the Google Earth platform to conduct a thorough landslide geomorphology survey and inventory construction in Minhe County, located in the upper Yellow River. The results show that within the study area of 1890.82 km 2 , at least 5517 landslide geomorphologies were identified, covering an area of 434.43 km 2 , with landslide‐affected areas accounting for approximately 22.98% of the total area. The largest single landslide area is 1.62 × 10 6 m 2 , while the smallest single landslide area is 880.22 m 2 , with an average landslide area of 78743.04 m 2 . The highest landslide point density reached 11.5 km −2 . More than 80% of the landslides were distributed in the townships of Qianhe, Zhongchuan, Guanting, and Bazhou. Landslides were predominantly distributed along the tributaries of the Huangshui and Yellow Rivers, with denser occurrences at river bends. In addition, some landslide geomorphologies are located in densely populated village areas, posing significant safety risks. These results provide valuable data support for further analysis of landslide spatial distribution in Minhe County, landslide risk assessment, and other related research.
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