Research on Linear Features Change Detection Based on Remote Sensing Image and Vector Data

2013 ◽  
Vol 679 ◽  
pp. 83-87
Author(s):  
Zuo Chang Zhang ◽  
Xin Peng ◽  
Tian Qi

To prompt the present situation and utilized values of fundamental geo-information, this paper focuses on a change detection method based on remote sensing image and GIS vector for linear features. Firstly unilateral vector was taken as original value of linear features; then edge points were picked up by pyramid decomposition and multi-scale template matching, and Ziplock Snake method was adopted to further improve the extraction results; finally buffer zone was constructed to distinguish the changed part. This change detection method proves to have higher degree of automation and more precise, so long as the registration of remote sensing image and vector map is accurate.

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 4673-4687
Author(s):  
Jixiang Zhao ◽  
Shanwei Liu ◽  
Jianhua Wan ◽  
Muhammad Yasir ◽  
Huayu Li

2019 ◽  
Vol 56 (12) ◽  
pp. 121003
Author(s):  
金秋含 Qiuhan Jin ◽  
王阳萍 Yangping Wang ◽  
杨景玉 Jingyu Yang

Author(s):  
Yonghong Jia ◽  
Mingting Zhou ◽  
Ye Jinshan

The change detection of remote sensing images means analysing the change information quantitatively and recognizing the change types of the surface coverage data in different time phases. With the appearance of high resolution remote sensing image, object-oriented change detection method arises at this historic moment. In this paper, we research multi-scale approach for high resolution images, which includes multi-scale segmentation, multi-scale feature selection and multi-scale classification. Experimental results show that this method has a stronger advantage than the traditional single-scale method of high resolution remote sensing image change detection.


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