Abstract: The Karakoram Highway passes through the preglacial area of Kongur Mountain along the northeastern edge of the Pamirs Plateau. On both sides of the highway along the Gaizi River valley, collapse and secondary disaster stone-slide frequented, and sands and stones are thrust by powerful external forces to clog traffic. While stone-slide investigations have been made on the Karakoram Highway (domestic section), evaluation or simulation is rare, and no stone-slide distribution data are formed. In this study, principles and technologies of data mining are introduced to integrate, code and convert environmental factors of disaster, through which a feature matrix is constructed for the easy onset modeling of stone-slide. The spatial distribution of the stone-slide in a 2 km range of both sides along Gaiz Valley is conducted, with a total data accuracy of up to 80%. This data set consists of vector data of investigation points and grid data of stone-slide spatial distribution. The investigation data records GPS longitudes and latitudes of the investigation point, which is a valuable ground data, while the stone-slide spatial distribution data also have important significance for research and engineering application.
Keywords: Karakoram Highway; Gaizi River valley; stone-slide; susceptibility analysis; machine learning