Study on optical remote sensing identification of high-location and long-runout landslide in the upper reaches of Jinsha River
Heng ZHAO , Tianbin YU , Meng WANG , Xichao HUANG , Jun WANG , Wen LIU , Ban SONG
Water Resources and Hydropower Engineering ›› 2025, Vol. 56 ›› Issue (S1) : 626 -633.
The geological conditions of the upper boundbelt of Jinsha River are extremely complex.The high position and long-runout geological disasters are the epitome of the geologica levolution in this area, which have for med many chain disasters similar to Baige landslide.High position and long-runout landslide has the characteristics of strong concealment, largescale, high suddenness and great destructive power.It is difficult to detect early due to the limitation of ground survey methods.Based on multi-optical remote sensing technology to carry out the Jinsha River upstream binding zone high remote landslide identification research, starting from the formation condition sand evolution process of high position and long-runout landslide, the comprehensive identification method of comprehensive remote sensing interpretation and halo disaster geological environment conditionanaly is adopted.Fourearly identification indexes of high position and long-runout landslide are stablished, which are image mark, topography mark, geological condition mark and human engineering activity mark.84 high position and long-runout landslides were identified int hestudy area.Through the identification results, the early identification indicators are further summarized, and the indicators are divided into three levels: basic conditions important conditions and auxiliary identification conditions.The research results provide the basis for the prevention and control of geological disasters and major engineering construction in the upper Jinsha River region, and also provide references for the early identification of high position and long-runout landslides in similaral pine valleyareas.
the upper reaches of Jinsha River / high-location and long-runout landslide / optical remote sensing recognition
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