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

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
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Calculation of correction coefficients for the RedEdge-MX multispectral camera through intercalibration with a hyperspectral sensor

초분광센서와의 상호교정을 통한 RedEdge-MX 다분광 카메라의 보정계수 산출

  • Baek, Seungil (Dept. of Civil and Environmental Engineering, Pusan National University) ;
  • Koh, Sooyoon (Dept. of Civil and Environmental Engineering, Pusan National University) ;
  • Kim, Wonkook (Dept. of Civil and Environmental Engineering, Pusan National University)
  • Received : 2020.11.25
  • Accepted : 2020.12.23
  • Published : 2020.12.31
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Abstract

Spectroradiometers have recently been drawing great attention in earth observing communities for its capability for obtaining target's quantitative properties. In particular, light-weighted multispectral cameras are gaining popularity in many field domains, as being utilized on UAV's. Despite the importance of the radiometric accuracy, studies are scarce on the performance of the inexpensive multispectral camera sensors that have various applications in agricultural, vegetation, and water quality analysis. This study conducted assessment of radiometric accuracy for MicaSense RedEdge-MX multispectral camera, by comparing the radiometric data with an independent hyperspectral sensor having NIST-traceable calibration quality. The comaprison showed that radiance from RedEdge-MX is lower than that of TriOS RAMSES by 5 to 16% depending on the bands, and the irradiance from RedEdge-MX is also lower than RAMSES by 1~20%. The correction coefficients for RedEdge-MX alculated through the 1-st and the 3-rd order regression analysis were presented as a result of the study.

원격탐사 분야에서 물체의 특성을 정략적으로 추정할 수 있는 분광센서에 대한 관심이 늘어나고 있으며, 특히, 최근 드론에 탑재하여 운영할 수 있는 경량 다분광 카메라의 활용이 주목받고 있다. 정량적 원격탐사를 위해서는 카메라 또는 센서에서 획득된 복사량의 정확도가 중요하지만, 저가의 다분광 카메라의 경우 복사정확도에 대한 독립적인 검증이 충분히 수행되지 않았다. 본 연구에서는 최근 농작물 모니터링, 식생 분석, 수질 분석 등에 다양하게 활용되고 있는 MicaSense사의 RedEdge-MX 카메라에 대한 복사 정확도 분석을 수행하였다. 미국 NIST 표준에 따라 교정된 초분광 센서인 TriOS RAMSES를 이용하여, RedEdge-MX 센서의 복사휘도 및 복사조도에 대한 상대 보정계수를 산출하였다. 분석결과, RedEdge-MX의 복사휘도는 밴드별로 RAMSES보다 5~16% 가량 낮게 나타났고, 복사조도 역시 1~20% 가량 낮은 것이 확인되었다. 본 연구에서는 RedEdge-MX의 관측값을 RAMSES에 상응하는 값으로 변환시키기 위한 보정계수를 1차 그리고 3차 회귀분석을 통하여 제공한다.

Keywords

References

  1. Cao, S., Danielson, B., Clare, S., Koenig, S., Campos-Vargas, C., and Sanchez-Azofeifa, A. (2019), Radiometric calibration assessments for UAS-borne multispectral cameras: Laboratory and field protocols, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 149, No. 3, pp. 132-145. https://doi.org/10.1016/j.isprsjprs.2019.01.016
  2. Chander, G., Hewison, T.J., Fox, N., Wu, X., Xiong, X., and Blackwell, W.J. (2013), Overview of Intercalibration of Satellite Instruments, IEEE Transactions on Geoscience and Remote Sensing, Vol. 51, pp. 1056-1080. https://doi.org/10.1109/TGRS.2012.2228654
  3. Choi, S., Kim, T., and Yu, W. (2009), Performance Evaluation of RANSAC Family, British Machine Vision Conference 2009, 7-10, September, London, United Kingdom, pp. 81.1-81.12.
  4. Dinguirard, M., and Slater, P.N. (1999), Calibration of Space-Multispectral Imaging Sensors: A Review, Remote Sensing of Environment, Vol. 68, pp. 194-205. https://doi.org/10.1016/S0034-4257(98)00111-4
  5. Duan, T., Chapman, S.C., Guo, Y., and Zheng, B. (2017), Dynamic monitoring of NDVI in wheat agronomy and breeding trials using an unmanned aerial vehicle, Field Crops Research, Vol. 210, pp. 71-80. https://doi.org/10.1016/j.fcr.2017.05.025
  6. Durfee, N., Ochoa, C., and Mata-Gonzalez, R. (2019), The Use of Low-Altitude UAV Imagery to Assess Western Juniper Density and Canopy Cover in Treated and Untreated Stands, Forests, Vol. 10, No. 4, pp. 296. https://doi.org/10.3390/f10040296
  7. Fischler, M.A. and Bolles, R.C. (1981), Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography, Communications of the ACM, Vol. 24, No. 6, pp. 381-395. https://doi.org/10.1145/358669.358692
  8. Garaba, S.P., Badewien, T.H., Braun, A., Schulz, A.-C., and Zielinski, O. (2014), Using ocean colour remote sensing products to estimate turbidity at the Wadden Sea time series station Spiekeroog, Journal of the European Optical Society-Rapid publications, Vol. 9. pp. 14020. https://doi.org/10.2971/jeos.2014.14020
  9. Gong, C., Buddenbaum, H., Retzlaff, R., and Udelhoven, T. (2019), An Empirical Assessment of Angular Dependency for RedEdge-M in Sloped Terrain Viticulture, Remote Sensing, Vol. 11, No. 21, pp. 2561. https://doi.org/10.3390/rs11212561
  10. Gorrono, J., Banks, A.C., Fox, N.P., and Underwood, C. (2017), Radiometric inter-sensor cross-calibration uncertainty using a traceable high accuracy reference hyperspectral imager, ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 130, pp. 393-417. https://doi.org/10.1016/j.isprsjprs.2017.07.002
  11. Guo, Y., Senthilnath, J., Wu, W., Zhang, X., Zeng, Z., and Huang, H. (2019), Radiometric calibration for multispectral camera of different imaging conditions mounted on a UAV platform, Sustainability, Vol. 11, No. 4, pp. 978. https://doi.org/10.3390/su11040978
  12. Iqbal, F., Lucieer, A., and Barry, K. (2018), Simplified radiometric calibration for UAS-mounted multispectral sensor, European Journal of Remote Sensing, Vol. 51, No. 1, pp. 301-313. https://doi.org/10.1080/22797254.2018.1432293
  13. Kim, W., Jung, S., Yongseon Moon, and Stephen C. Mangum. (2020), Morphological Band Registration of Multispectral Cameras for Water Quality Analysis with Unmanned Aerial Vehicle, Remote Sensing, Vol. 12, No. 12, pp. 2024. https://doi.org/10.3390/rs12122024
  14. Kim, W., Roh, S.H., Moon, Y., and Jung, S. (2019), Evaluation of Rededge-M Camera for Water Color Observation after Image Preprocessing, Journal of the Korean Society of Surveying, Vol. 37, No. 3, pp. 167-175. (in Korean with English abstract)
  15. Liang, S. (2005), Quantitative remote sensing of land surfaces (Vol. 30), John Wiley & Sons Inc., New York, N.Y.
  16. Matthews, M.W. (2011), A current review of empirical procedures of remote sensing in inland and near-coastal transitional waters, International Journal of Remote Sensing, Vol. 32, No. 21, pp. 6855-6899. https://doi.org/10.1080/01431161.2010.512947
  17. MicaSense, (2020), RedEdge Camera Radiometric Calibration Model, MicaSense, https://support.micasense.com/hc/en-us/articles/115000351194-RedEdge-Camera-Radiometric-Calibration-Model (last date accessed: 18 June 2020)
  18. Steven, M.D., Malthus, T.J., Baret, F., Xu, H., and Chopping, M.J. (2003), Intercalibration of vegetation indices from different sensor systems, Remote Sensing of Environment, Vol. 88, No. 4, pp. 412-422. https://doi.org/10.1016/j.rse.2003.08.010
  19. Teillet, P.M., Guindon, B., and Goodenough, D.G. (1982), On the Slope-Aspect Correction of Multispectral Scanner Data, Canadian Journal of Remote Sensing, Vol. 8, No. 4, pp.84-106. https://doi.org/10.1080/07038992.1982.10855028
  20. Yao, Xinfeng, Yao, Xia, Jia, W., Tian, Y., Ni, J., Cao, W., and Zhu, Y. (2013), Comparison and Intercalibration of Vegetation Indices from Different Sensors for Monitoring Above-Ground Plant Nitrogen Uptake in Winter Wheat, Sensors, Vol. 13, No. 3, pp. 3109-3130. https://doi.org/10.3390/s130303109
  21. Oh, E., An, G.B., Kang, H., Cho, S.I., and Park, Y.J. (2014), Development of relative radiometric calibration system for in-situ measurement spectroradiometers, Korean Journal of Remote Sensing, Vol. 30, No. 4, pp. 455-464. (in Korean with English abstract) https://doi.org/10.7780/kjrs.2014.30.4.4

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