DOI QR코드

DOI QR Code

A Study on Urban Change Detection Using D-DSM from Stereo Satellite Data

  • Received : 2019.10.06
  • Accepted : 2019.10.17
  • Published : 2019.10.31

Abstract

Unlike aerial images covering small region, satellite data show high potential to detect urban scale geospatial changes. The change detection using satellite images can be carried out using single image or stereo images. The single image approach is based on radiometric differences between two images of different times. It has limitations to detect building level changes when the significant occlusion and relief displacement appear in the images. In contrast, stereo satellite data can be used to generate DSM (Digital Surface Model) that contain information of relief-corrected objects. Therefore, they have high potential for the object change detection. Therefore, we carried out a study for the change detection over an urban area using stereo satellite data of two different times. First, the RPC correction was performed for two DSMs generation via stereo image matching. Then, D-DSM (Differential DSM) was generated by differentiating two DSMs. The D-DSM was used for the topographic change detection and the performance was checked by applying different height thresholds to D-DSM.

Keywords

References

  1. Bris, A.L. and Chehata, N. (2011), Change detection in a topographic building database using submetric satellite images, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 5-7 Oct, Munich, Germany, Vol. XXXVIII-3/W22, pp.25-30.
  2. Choi, K.A. and Lee, I.P. (2008), Automatic change detection of urban areas using LIDAR data, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 26, No. 4, pp. 341-350. (in Korean with English abstract)
  3. Dini, G.R., Jacobsen, K., Rottensteiner, F., Rajhi, M., and Heipke, C. (2012), 3D building change detection using high resolution stereo images and a GIS database, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 25 Aug-01 Sep, Melbourne, Australia, Vol. XXXIX-B7, pp.299-303.
  4. Du, S., Zhang, Y., Qin, R., Yang, Z., Zou, Z., Tang, Y., and Fan, C. (2016), Building change detection using old aerial images and new LiDAR data, Remote Sensing, Vol. 8, No. 1030, pp. 1-20.
  5. Kang, G.S., Shin, S.C., and Cho, K.J. (2003), Change detection using the IKONOS satellite images, Journal of the Korean Society for Geospatial Information System, Vol. 11, No. 2, pp. 61-66. (in Korean with English abstract)
  6. KrauB, T., Angelo, P., Tian, J., and Reinartz, P. (2013), Automatic DEM generation and 3D change detection from satellite imagery, ESA Living Planet Symposium 2013, Edinburgh, UK, 9-13 Sep, ESA SP-722.
  7. Kwon, O.S., Kim, S.S., and Lee, D.H. (2011), A study on urban change detection using the DSM from the aerial images, Proceedings of Korean Society for Geospatial Information Science, 28 Oct, Ilsan, pp. 33-37. (in Korean)
  8. Meszaros, M., Szatmari, J., Tobak, Z., and Mucsi, L. (2012), Extraction of digital surface models from corona satellite stereo images, Journal of Env. Geogr., Vol. I, No. 1-2, pp. 5-10.
  9. Oh, J.H. and Lee, C.N. (2018), Relative RPCs biascompensation for satellite stereo images processing, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 36, No. 4, pp. 287-293. https://doi.org/10.7848/KSGPC.2018.36.4.287
  10. Tian, J., Cui, S., and Reinartz, P. (2014), Building change detection based on satellite stereo imagery and digital surface models, IEEE Transactions On Geoscience And Remote Sensing, Vol. 52, No. 1, pp. 406-417. https://doi.org/10.1109/TGRS.2013.2240692
  11. Varade, D. (2011), Change Detection of Buildings Using Satellite Image and DSMs, Master's thesis, Technical University of Munich, Munich, Germany, 81p.

Cited by

  1. 기계학습 기법에 따른 KOMPSAT-3A 시가화 영상 분류 - 서울시 양재 지역을 중심으로 - vol.36, pp.6, 2020, https://doi.org/10.7780/kjrs.2020.36.6.2.7