Local similarity measure for landslide detection and identification in comparison with the image differencing method

In this article, a new simple method of landslide detection and identification is proposed. It is based on the use of local mutual information and image thresholding. A binary change image is then produced. Connected component analysis is used to identify the connected regions. Landslides are identified as the largest connected regions in this image. Mathematical morphology is used to approximate the landslide region. This method is simple and suitable for the detection of large changed regions where the ratio of the unchanged to changed pixels in the image is approximately one to a few tens. Compared to the image differencing method, this method gives more reliable results.

[1]  Pi-Hui Huang,et al.  Vegetation recovery monitoring and assessment at landslides caused by earthquake in Central Taiwan , 2005 .

[2]  Stanislav Kovacic,et al.  Point Similarity Measure Based on Mutual Information , 2003, WBIR.

[3]  T. Kamai,et al.  Detection of a landslide movement as geometric misregistration in image matching of SPOT HRV data of two different dates , 2003 .

[4]  J. Nichol,et al.  Satellite remote sensing for detailed landslide inventories using change detection and image fusion , 2005 .

[5]  M. Wong,et al.  Detection and interpretation of landslides using satellite images , 2005 .

[6]  W. Murphy,et al.  Airborne remote sensing for landslide hazard assessment: a case study on the Jurassic escarpment slopes of Worcestershire, UK , 2005, Quarterly Journal of Engineering Geology and Hydrogeology.

[7]  Chiang Wei,et al.  Locating landslides using multi-temporal satellite images , 2004 .

[8]  Paul L. Rosin,et al.  Monitoring landslides from optical remotely sensed imagery: the case history of Tessina landslide, Italy , 2003 .

[9]  Hazard and risk assessment of rainfall – induced landsliding along a railway line , 2005, Quarterly Journal of Engineering Geology and Hydrogeology.

[10]  James C. Gee,et al.  Point similarity measures for non-rigid registration of multi-modal data , 2003, Comput. Vis. Image Underst..

[11]  Krištof Oštir,et al.  Application of satellite remote sensing in natural hazard management: The Mount Mangart landslide case study , 2003 .

[12]  M. Petrou Image Registration: An Overview , 2004 .

[13]  Paul L. Rosin,et al.  Remote sensing image thresholding methods for determining landslide activity , 2005 .