Abstract:

Arctic melt pond over sea ice surface is of great significance in the study of Arctic sea ice mass balance and heat and salt balances in the ocean mixed layer. In order to obtain accurate melt pond fraction, this paper proposes a method for extracting Arctic melt pond and roughness information from the sea ice surface based on unmanned aerial vehicle (UAV) observations. We made UAV observations over the sea ice surface in the Canada basin during the 7th Chinese National Arctic Research Expedition. Improvment on the dark-channel- prior defogging algorithm based on the special environment of Arctic, a mosaic process ,melt pond discrimination on the mosaic image , and melt pond fraction calculation were done step by step. Meanwhile, we used three-dimentional aerial-image modeling to calculate the sea ice surface relative elevation and sea ice surface roughness. Study on the relationship of melt pond and sea ice surface roughness distribution showed that areas with higher surface roughness generally have more smaller melt ponds, whereas dissolved and larger melt ponds usually occur in areas with lower surface roughness.

Key words: Arctic, unmanned aerial vehicle(UAV), melt pond fraction, defogging algorithm, sea ice surface roughness