Korean Journal of Remote Sensing (대한원격탐사학회지)

Korean Society of Remote Sensing (대한원격탐사학회)
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Accuracy Evaluation of DEM generated from Satellite Images Using Automated Geo-positioning Approach

  • Oh, Kwan-Young (Department of Geoinformatics, The University of Seoul) ;
  • Jung, Hyung-Sup (Department of Geoinformatics, The University of Seoul) ;
  • Lee, Moung-Jin (Environmental Assessment Group/Center for Environmental Assessment Monitoring, Korea Environment Institute)
  • Received : 2017.02.10
  • Accepted : 2017.02.20
  • Published : 2017.02.28
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Abstract

S The need for an automated geo-positioning approach for near real-time results and to boost cost-effectiveness has become increasingly urgent. Following this trend, a new approach to automatically compensate for the bias of the rational function model (RFM) was proposed. The core idea of this approach is to remove the bias of RFM only using tie points, which are corrected by matching with the digital elevation model (DEM) without any additional ground control points (GCPs). However, there has to be a additional evaluation according to the quality of DEM because DEM is used as a core element in this approach. To address this issue, this paper compared the quality effects of DEM in the conduct of the this approach using the Shuttle Radar Topographic Mission (SRTM) DEM with the spatial resolution of 90m. and the National Geographic Information Institute (NGII) DEM with the spatial resolution of 5m. One KOMPSAT-2 stereo-pair image acquired at Busan, Korea was used as experimental data. The accuracy was compared to 29 check points acquired by GPS surveying. After bias-compensation using the two DEMs, the Root Mean Square (RMS) errors were less than 6 m in all coordinate components. When SRTM DEM was used, the RMSE vector was about 11.2m. On the other hand, when NGII DEM was used, the RMSE vector was about 7.8 m. The experimental results showed that automated geo-positioning approach can be accomplished more effectively by using NGII DEM with higher resolution than SRTM DEM.

Keywords

References

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