STUDY ON ARCTIC MELT POND FRACTION RETRIEVAL ALGORITHM USING MODIS DATA

• Published in: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
• Main Authors: Su, J., Yu, P., Qin, Y., Zhang, G., Wang, M.
• Format: Text
• Language: English
• Published: 2020
• Subjects: Arctic; Pacific; albedo; Sea ice
• Online Access: https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-893-2020; https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/893/2020/

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.