The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLIII-B3-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 893–898, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-893-2020
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 893–898, 2020
https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-893-2020

  21 Aug 2020

21 Aug 2020

STUDY ON ARCTIC MELT POND FRACTION RETRIEVAL ALGORITHM USING MODIS DATA

J. Su1,2, P. Yu1,3, Y. Qin1,2, G. Zhang1, and M. Wang1,4 J. Su et al.
  • 1Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China
  • 2Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266100, China
  • 3Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Finland
  • 4Earth Observation and Modelling, Department of Geography, Kiel University, Kiel, Germany

Keywords: Arctic, melt pond fraction, retrieval algorithm, MODIS

Abstract. During spring and summer, melt ponds appear on the sea ice surface in the Arctic and play an important role in sea ice-albedo feedback effect. The melt pond fraction (MPF) can be retrieved using multi-band linear equations, but the calculation is complicated by the ill-conditioned reflectance matrix. In this paper, we calculated the condition numbers which represent the degree of the ill-conditioned reflectance matrix in the results of the MPF from a MODIS-based unmixing algorithm. The condition number is introduced here as a criterion for the sensitivity of the solution in the system to the error in the input value. By combining 3 bands among 5 visible and near-infrared bands of MODIS data, the results show that the three-band combination with the lowest sensitivity to the error of input is B245. To improve the algorithm, we introduce pre-processing to remove open water from the four surface types and then remove one reflectance equation from the original set. The best two-band combination algorithm is B15. Compared with the discrimination results from Landsat5-TM, the RMS is 0.14. This algorithm is applied in pan-Arctic scale, the MPF results are larger than that from University of Hamburg, especially in the Pacific sector.