Automatic Monitoring of Linear Cultural Heritage Based on Multi-temporal DOM Images

被引:0
|
作者
Wang J. [1 ]
Cheng B. [1 ]
Lü Z. [1 ]
机构
[1] Suzhou Surveying & Mapping Institute Co. Ltd., Suzhou
关键词
Automatic monitoring; Linear cultural heritage; Multi-band difference method; Multi-temporal digital orthophoto map; Object-oriented classification;
D O I
10.13203/j.whugis20180440
中图分类号
学科分类号
摘要
In this paper, remote sensing technology is applied to the monitoring of the dynamic changes of cultural heritage. Based on multi-temporal digital orthophoto map(DOM) images, the multi-band difference method and the object-oriented post-classification change detection method are used to monitor the dynamic changes of the Precious Belt Bridge in Suzhou. Experimental results show that both methods can be applied to the dynamic change detection of cultural heritage, and the object-oriented post-classification change detection method is more effective for continuous and large-scale change of ground objects, while multi-band difference method is more sensitive to discrete ground object changes. The research results in this paper can provide ideas for the intelligent monitoring and protection of the cultural heritage in our country, which is have certain promotion value. © 2019, Research and Development Office of Wuhan University. All right reserved.
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页码:77 / 83
页数:6
相关论文
共 12 条
  • [1] Brozzone L., Prieto D.F., Automatic Analysis of the Difference Image for Unsupervised Change Detection, IEEE Transaction on Geoscience and Remote Sensing, 38, 3, pp. 1171-1182, (2000)
  • [2] Zhang L., Wu C., Advanced and Future Development of Change Detection for Multi-temporal Remote Sensing Imagery, Acta Geodaetica et Cartographica Sinica, 46, 10, pp. 1447-1459, (2017)
  • [3] Yin S., Wu C., Wang Q., Et al., Review of Change Detection Methods Using Multi-Temporal Remotely Sensed Images, Spectroscopy and Spectral Analysis, 33, 12, pp. 3339-3342, (2013)
  • [4] Sun Y., Wang H., Li F., Et al., Elastic Registration of Remote Sensing Image for Change Detection, Geomatics and Information Science of Wuhan University, 43, 1, pp. 53-59, (2018)
  • [5] Tong G., Li Y., Ding W., Et al., Review of Remote Sensing Image Change Detection, Journal of Image and Graphics, 20, 12, pp. 1561-1571, (2015)
  • [6] Sun X., Zhang J., Yan Q., Et al., A Summary on Current Techniques and Prospects of Remote Sensing Change Detection, Remote Sensing Information, 26, 1, pp. 119-123, (2011)
  • [7] Zhang Y., Li L., Jiang M., Et al., Change Detection Method for Buildings Based on Pixel-Level and Feature-Level, Computer Science, 40, 1, pp. 286-293, (2013)
  • [8] Zhang Y., Research on Change Detection Based on Unmanned Aerial Vehicles Serial Images, (2008)
  • [9] Xu Y., Shi J., An D., Change Detection Based on Segmentation and Matched Features Point for UAV Images, Geomatics and Information Science of Wuhan University, 41, 10, pp. 1286-1291, (2016)
  • [10] Wang T., Ren S., Xu M., Research on Hybrid Object Classification Method Based on eCognition, Bulletin of Surveying and Mapping, 3, pp. 137-138, (2014)