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Evaluation of SWIR bands utilization of Worldview-3 satellite imagery for mineral detection

광물탐지를 위한 Worldview-3 위성영상의 SWIR 밴드 활용성 평가

  • Kim, Sungbo (Department of Drone & Transportation Engineering, Youngsan University) ;
  • Park, Honglyun (Department of Drone & Transportation Engineering, Youngsan University)
  • Received : 2021.06.04
  • Accepted : 2021.06.24
  • Published : 2021.06.30

Abstract

With the recent development of satellite sensor technology, high-spatial-resolution imagery of various spectral wavelength bands have become possible. Worldview-3 satellite sensor provides panchromatic images with high-spatial-resolution and VNIR (Visible Near InfraRed) and SWIR (ShortWave InfraRed) bands with low-spatial-resolution, so it can be used in various fields such as defense, environment, and surveying. In this study, mineral detection was performed using Worldview-3 satellite imagery. In order to effectively utilize the VNIR and SWIR bands of the Worldview-3 satellite image, the sharpening technique was applied to the spatial resolution of the panchromatic image. To confirm the utility of SWIR bands for mineral detection, mineral detection using only VNIR bands was performed and comparatively evaluated. As the mineral detection technique, SAM (Spectral Angle Mapper), a representative similarity technique, was applied, and the pixels detected as minerals were selected by applying an empirical threshold to the analysis result. Quantitative evaluation was performed using reference data on the results of similarity analysis to evaluate the accuracy of mineral detection. As a result of the accuracy evaluation, the detection rate and false detection rate of mineral detecting using SWIR bands were calculated to be 0.882 and 0.011, respectively, and the results using only VNIR bands were 0.891 and 0.037, respectively. It was found that the detection rate when the SWIR bands were additionally used was lower than that when only the VNIR bands were used. However, it was found that the false detection rate was significantly reduced, and through this, it was possible to confirm the applicability of SWIR bands in mineral detection.

최근 위성센서 기술의 발전함에 따라 다양한 분광파장대의 고해상도 영상 취득이 가능해졌다. Worldview-3 위성센서는 높은 공간해상도를 지닌 panchromatic 영상과 함께 낮은 공간해상도를 지닌 VNIR (Visible Near InfraRed), SWIR (ShortWave InfraRed) 밴드들을 제공하고 있어, 국방, 환경, 측량 등 다양한 분야에서 활용이 가능하다. 본 연구에서는 Worldview-3 위성영상을 활용하여 광물탐지를 수행하였다. Worldview-3 위성영상의 VNIR, SWIR 밴드들을 효과적으로 활용하기 위해 융합기법을 적용을 통해 panchromatic 영상의 공간해상도로 융합하여 광물탐지에 이용하였다. 광물탐지에 SWIR 밴드들의 활용성을 확인하기 위해 VNIR 밴드들만을 활용한 광물탐지를 수행하여 비교평가하였다. 광물탐지 기법으로는 대표적인 유사도 기법인 SAM (Spectral Angle Mapper)을 적용하였으며, 분석 결과에 경험적 임계치를 적용하여 광물로 탐지되는 화소들을 선정하였다. 광물탐지의 정확도 평가를 위해 유사도 분석을 수행한 결과에 참조자료를 이용하여 정량적평가를 수행하였다. 정확도 평가 결과, SWIR 밴드들을 활용한 광물탐지 결과의 탐지율과 오탐지율이 각각 0.882, 0.011로 계산되었으며, VNIR 밴드들만을 활용한 결과는 각각 0.891, 0.037로 나타났다. SWIR 밴드를 추가적으로 활용한 경우의 탐지율이 VNIR 밴드만을 사용한 경우보다 다소 낮은 것으로 나타났지만, 오탐지율이 크게 감소한 것으로 나타나, 이를 통해 광물탐지에서의 SWIR 밴드들의 활용가능성을 확인할 수 있었다.

Keywords

Acknowledgement

이 논문은 2020학년도 영산대학교 교내연구비의 지원에 의하여 이루어진 것임

References

  1. Garzelli, A. (2015), Pansharpening of multispectral images based on nonlocal parameter optimization, IEEE Transactions on Geoscience and Remote Sensing, Vol. 53, No. 4, pp. 2096-2107. https://doi.org/10.1109/TGRS.2014.2354471
  2. Han, Y., Jung, S,. Park, H., and Choi, J. (2018), Effect analysis of Worldview-3 SWIR bands for wetland classification in Suncheon bay, South Korea, Journal of Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 36, No. 5, pp. 371-379. https://doi.org/10.7848/KSGPC.2018.36.5.371
  3. Hecker, C., Meijde, M., Werff, H., and Meer, F.D. (2008), Assessing the influence of reference spectra on synthetic SAM classification results, IEEE Trnasactions on Geoscience and Remote Sensing, Vol. 46, No. 12, pp. 4162-4172. https://doi.org/10.1109/TGRS.2008.2001035
  4. Huang, Z., Shi, Z., and Yang, S. (2013), Nonlocal similarity regularized sparsity model for hyperspectral target detection, IEEE Geoscience and Remote Sensing Letters, Vol. 10, No. 6, pp. 1532-1536. https://doi.org/10.1109/LGRS.2013.2261455
  5. Kim, G., Park, N., Choi, S., and Choi, J. Performance evaluation of pansharpening algorithms for Worldview-3 satellite imagery, Journal of Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 34, No. 4, pp. 413-423. https://doi.org/10.7848/ksgpc.2016.34.4.413
  6. Kim, K. (2015), Study on improving hyperspectral target detection by target signal exclusion in matched filtering, Korean Journal of Remote Sensing, Vol. 31, No. 5, pp. 433-440. https://doi.org/10.7780/kjrs.2015.31.5.7
  7. Le, B.T., Xiao, D., Okello, D., He, D., Xu, J., and Doan, T.T. (2017), Coal exploration technology based on visible-infrared spectra and remote sensing data, Spectroscopy, Letters, Vol. 50, No. 8, pp. 440-450. https://doi.org/10.1080/00387010.2017.1354889
  8. Manolakis, D., Siracusa, C., and Shaw, G. (2001), Hyperspectral subpixel target detection using the linear mixing model, IEEE Transactions on Geoscience and Remote Sensing, Vol. 39, No. 7, pp. 1392-1409. https://doi.org/10.1109/36.934072
  9. Park, H., Choi, J., Park, N., and Choi, S. (2017) Sharpening the VNIR and SWIR bands of Sentinel-2A imagery through modified selected and synthesized bands schemes, Remote Sensing, Vol. 9, No. 10, pp. 1080-1099. https://doi.org/10.3390/rs9101080
  10. Rahmani, S., Strait, M., Merkurjev, D., Moelloer, M., and Wittman, T. (2010), An adaptive IHS pan-sharpening method, IEEE Geoscience and Remote Sensing, Vol. 7, No. 4, pp. 746-750. https://doi.org/10.1109/LGRS.2010.2046715
  11. Samsudin, S.H., Shafri, H., and Hamedianfar, A. (2016), Development of spectral indices for roofing material condition status detection using field spectroscopy and Worldview-3 data, Journal of Applied Remote Sensing, Vol. 10, No. 2, pp. 025021-1-025021-18. https://doi.org/10.1117/1.JRS.10.025021
  12. Selva, M., Aiazzi, B., Butera, F., Chiarantini, L., and Boronti, S. (2015), Hyper-sharpening: A first approach on SIM-GA data, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 8, No. 6, pp. 3008-3024. https://doi.org/10.1109/JSTARS.2015.2440092
  13. Sun, Y., Tian, S, and Di, B. (2017), Extracting mineral alteration information using Worldview-3 data, Geoscience Frontiers, Vol. 8, No. 5, pp. 1051-1062. https://doi.org/10.1016/j.gsf.2016.10.008