Method for detecting landslip from remotely sensed image by adopting image classification technology

Abstract

The invention relates to a method for detecting a landslip from a remotely sensed image by adopting an image classification technology. The method comprises the following steps: firstly, partitioning the remotely sensed image after being pretreated according to an overlapping-based area averaging method, thereby obtaining square image blocks with the same areas; dividing the obtained image blocksinto two sets: a training set and a test set; extracting SIFT (Scale Invariant Feature Transform) features of all the image blocks in the training set and the test set; processing the SIFT features in the training set according to a k-means classifying method, thereby obtaining words and a dictionary; representing each image block in the training set and the test set by a BoVW model; and lastly, utilizing a pLSA model to extract the theme of each image block, and utilizing a KNN classifier to divide the image blocks in the test set into landslip type and non-landslip type image blocks, thereby realizing the landslip detection for the remotely sensed image. The method provided by the invention has the advantages of small calculation volume, high detecting efficiency and ultrahigh detectingaccuracy.

Description

technical field [0001] The invention relates to a method for detecting landslides from remote sensing images by using image classification technology, which can be applied to landslide detection of various remote sensing images. Background technique [0002] Landslides are a kind of extremely destructive geological disasters, which often cause huge losses to industrial and agricultural production as well as people's lives and property. Therefore, landslide research has been paid more and more attention by people. Early landslide detection mainly used the traditional ground survey method, which is very intensive in field work, especially in dangerous and harsh climate areas, and the work efficiency is very low. By the end of the 1990s, the interpretation of stereoscopic aerial photos combined with certain ground verification became the most commonly used method for landslide detection and mapping, and then the interpretation results were manually transferred to topographic m...

AI Technical Summary

Problems solved by technology

However, the object-based high-resolution remote sensing image landslide detection method requires multi-scale and multi-level segmentation of multi-period remote sensing images, and the detection effect directly depends on the results of image segmentation, and the overall detection rate is not high; The detection method can only divide the image into several simple types required for landslide interpretation, and the detection process still needs to rely on the professional remote sensing processing software ENVI, and the detection efficiency and detection accuracy need to be improved

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