한국측량학회지 (Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)

  • 제36권4호
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  • Pages.263-270
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  • 2018
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  • 1598-4850(pISSN)
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  • 2288-260X(eISSN)
한국측량학회 (Korean Society of Surveying, Geodesy, Photogrammetry and Cartography)
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무인항공기에 탑재된 열적외선 센서 기반의 지표면 온도 정사영상 제작 및 피복별 온도 정확도 분석

Generation of Land Surface Temperature Orthophoto and Temperature Accuracy Analysis by Land Covers Based on Thermal Infrared Sensor Mounted on Unmanned Aerial Vehicle

  • Park, Jin Hwan (Korea Land and Geospatial InformatiX Corporation) ;
  • Lee, Ki Rim (Department of Geospatial Information, Kyungpook National University) ;
  • Lee, Won Hee (School of Convergence & Fusion System Engineering, Kyungpook National University) ;
  • Han, You Kyung (School of Convergence & Fusion System Engineering, Kyungpook National University)
  • 투고 : 2018.06.21
  • 심사 : 2018.08.19
  • 발행 : 2018.08.31
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초록

지표면 온도는 지면-대기의 상호 순환을 이해하는데 중요한 요소로 알려져 있지만 시공간적 변동성이 크기 때문에 정규적인 관측은 거의 이루어지지 못하고 있다. 기존의 지표면 온도는 위성 영상을 이용하여 관측하고 있지만 위성의 특성상 긴 재방문주기와 낮은 정확도의 한계를 가지고 있다. 본 연구에서는 기존의 위성 영상을 활용한 지표면 온도 관측의 대체가능성을 확인하기 위해 무인항공기에 열적외선 센서를 탑재하여 단일 영상을 취득하였다. 취득된 영상은 JPEG 영상에서 TiFF 영상으로 변환하여 정사영상을 제작하였으며 정사영상의 DN값을 이용하여 실제 지표면 온도로 계산하였다. 계산된 피복별 지표면 온도의 정확도를 평가하기 위해 영상촬영과 동시에 적외선 온도계로 직접 관측한 지표면 온도와 비교하였다. 두 가지 방법으로 관측한 지표면 온도를 비교 했을 때, 모든 피복들에 대해서 정확도가 열적외선 센서의 관측 정확도 이하로 나타났다. 따라서 무인항공기에 탑재된 열적외선 센서를 이용하여 기존의 지표면 온도 관측 방법인 위성 영상의 대체 가능성을 확인하였다.

Land surface temperature is known to be an important factor in understanding the interactions of the ground-atmosphere. However, because of the large spatio-temporal variability, regular observation is rarely made. The existing land surface temperature is observed using satellite images, but due to the nature of satellite, it has the limit of long revisit period and low accuracy. In this study, in order to confirm the possibility of replacing land surface temperature observation using satellite imagery, images acquired by TIR (Thermal Infrared) sensor mounted on UAV (Unmanned Aerial Vehicle) are used. The acquired images were transformed from JPEG (Joint Photographic Experts Group) to TIFF (Tagged Image File Format) format and orthophoto was then generated. The DN (Digital Number) value of orthophoto was used to calculate the actual land surface temperature. In order to evaluate the accuracy of the calculated land surface temperature, the land surface temperature was compared with the land surface temperature directly observed with an infrared thermometer at the same time. When comparing the observed land surface temperatures in two ways, the accuracy of all the land covers was below the measure accuracy of the TIR sensor. Therefore, the possibility of replacing the satellite image, which is a conventional land surface temperature observation method, is confirmed by using the TIR sensor mounted on UAV.

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참고문헌

  1. Aubrecht, D.M., Helliker, B.R., Goulden, M.L., Roberts, D.A., Still, C.J., and Richardson, A.D. (2016), Continuous, long-term, high-frequency thermal imaging of vegetation: Uncertainties and recommended best practices, Agricultural and Forest Meteorology, Vol. 228, pp. 315-326.
  2. Bae, D.H., Kim, H.M., and Ha, S.R. (2018), The factor analysis of land surface temperature (LST) change using MODIS imagery and panel data, Journal of the Korean Association of Geographic Information Studies, Vol. 21, No. 1, pp. 46-56. (in Korean with English abstract) https://doi.org/10.11108/KAGIS.2018.21.1.046
  3. Baek, J.J. and Choi, M.H. (2012), Availability of land surface temperature from the COMS in the Korea peninsula, Journal of Korean Water Resources Association, Vol. 45, No. 8, pp. 755-765. (in Korean with English abstract) https://doi.org/10.3741/JKWRA.2012.45.8.755
  4. Cho, C.Y., Jee, J.B., Park, M.S., Park, S.H., and Choi, Y.J. (2016), Comparison of surface temperatures between thermal infrared image and landsat 8 satellite, Journal of Korean Society for Atmospheric Environment, Vol. 32, No. 1, pp. 46-56. https://doi.org/10.5572/KOSAE.2016.32.1.046
  5. Cho, H.S., Joung, Y.J., and Choi, M.J. (2014), Effects of the urban spatial characteristics on urban heat island, Journal of Environmental Policy and Administration, Vol. 22, No. 2, pp. 27-43. https://doi.org/10.15301/jepa.2014.22.4.27
  6. Di Felice, F., Mazzini, A., Di Stefano, G., and Romeo, G. (2018), Drone high resolution infrared imaging of the lusi mud eruption, Marine and Petroleum Geology, Vol. 90, pp. 38-51. https://doi.org/10.1016/j.marpetgeo.2017.10.025
  7. Gonzalez-Dugo, V., Zarco-Tejada, P., Nicolas, E., Nortes, P.A., Alarcon, J.J., Intrigliolo, D.S., and Fereres, E. (2013), Using high resolution UAV thermal imagery to assess the variability in the water status of five fruit tree species within a commercial orchard, Precision Agriculture, Vol. 14, No. 6, pp. 660-678. https://doi.org/10.1007/s11119-013-9322-9
  8. Kang, K.M., Kim, D.J., Kim, S.H., Cho, Y.K., and Lee, S.H. (2014), Extraction of sea surface temperature in coastal area using ground-based thermal infrared sensor on-boarded to aircraft, Korean Journal of Remote Sensing, Vol. 30, No. 6, pp. 797-807. (in Korean with English abstract) https://doi.org/10.7780/kjrs.2014.30.6.10
  9. Karbou, F. and Prigent, C. (2005), Calculation of microwave land surface emissivity from satellite observations: Validity of the specular approximation over snow-free surfaces?, IEEE Geoscience and Remote Sensing Letters, Vol. 2, No. 3, pp. 311-314. https://doi.org/10.1109/LGRS.2005.847932
  10. Khanal, S., Fulton, J., and Shearer, S. (2017), An overview of current and potential applications of thermal remote sensing in precision agriculture, Computers and Electronics in Agriculture, Vol. 139, pp. 22-32. https://doi.org/10.1016/j.compag.2017.05.001
  11. Lee, G.S. and Lee, J.J. (2017), The detection of heat emission to solar cell using UAV-based thermal infrared sensor, Journal of the Korean Society for Geospatial Information Science, Vol. 25, No. 1, pp. 71-78. (in Korean with English abstract) https://doi.org/10.7319/kogsis.2017.25.1.071
  12. Lowe, D.G. (2004), Distinctive image features from scale-invariant keypoints, International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110. https://doi.org/10.1023/B:VISI.0000029664.99615.94
  13. Ryu, T.H. and Um, J.S. (2013), Evaluating changing trends of surface temperature in winter according to rooftop color using remotely sensed thermal infrared, Journal of the Korean Society for Geo-spatial Information Science, Vol. 21, No. 1, pp. 27-37. (in Korean with English abstract)
  14. Santesteban, L.G., Di Gennaro, S.F., Herrero-Langreo, A., Miranda, C., Royo, J.B., and Matese, A. (2017), High-resolution UAV-based thermal imaging to estimate the instantaneous and seasonal variability of plant water status within a vineyard, Agricultural Water Management, Vol. 183, pp. 49-59. https://doi.org/10.1016/j.agwat.2016.08.026
  15. Suh, M.S. (2012), Land Surface Temperature (LST) Algorithm Technical Analysis (LST-v5.0), NMSC/SCI/ATBD/LST, Issue 1, rev.0, National Meteorological Satellite Center, Jincheon, pp. 1-38.
  16. Thomas, H. (2018), Some like it hot: The impact of next generation FLIR systems thermal cameras on archaeological thermography, Archaeological Prospection, Vol. 25, No. 1, pp. 81-87. https://doi.org/10.1002/arp.1588
  17. Turner, D., Lucieer, A., Malenovsky, Z., King, D.H., and Robinson, S.A. (2014), Spatial co-registration of ultrahigh resolution visible, multispectral and thermal images acquired with a micro-UAV over Antarctic moss beds, Remote Sensing, Vol. 6, No. 5, pp. 4003-4024. https://doi.org/10.3390/rs6054003