Abstract: In order to solve the shortcomings of the existing methods in the deformation monitoring of large scale open-pit slope,a method for monitoring landslide displacement is proposed based on ASIFT (Affine scale invariant feature transform) image feature matching algorithm is proposed.Firstly,the landslide physical model is designed based on the real terrain spatial distribution of open-pit mine landslide,and the sequence images of the model sliding process is obtained through high-resolution digital camera;then,the feature points of the optical photos of landslide in different stages are extracted and matched by using ASIFT feature matching algorithm,and the error matched points are dropped by using RANSAC random sampling algorithm;finally,the spatial displacement vectors of feature points are calculated by adopting the landslide motion feature vector set model,so the landslide displacement field is calibrated and the landslide range is determined.The study results show that：it is very difficult to monitor the landslide displacement in creep deformation stage by using ASIFT image feature matching algorithm,but it could be effectively applied to monitor the obvious landslide displacement in slowly moving stage,sliding stage and slowly crawling stage,the feature points matching number and matching accuracy of the ASIFT algorithm are both superior to the ones of SIFT (Scale invariant feature transform) algorithm,to be specific,the the number of correct matching feature points of ASIFT algorithm is 3~5 times to the one of SIFT algorithm,and the matching accuracy is increased from 75% to 97%,besides that,the calibration precision of displacement vectors is also improved obviously.The above analysis results further that the method proposed in this paper is suitable for the displacement monitoring of large deformation in late stage of large scale landslide.

Key words: Open-pit mine, ASIFT algorithm, SIFT algorithm, Landslide displacement monitoring, Landslide physical model, Spatial displacement vector