ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume V-3-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 319–324, 2022
https://doi.org/10.5194/isprs-annals-V-3-2022-319-2022
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 319–324, 2022
https://doi.org/10.5194/isprs-annals-V-3-2022-319-2022
 
17 May 2022
17 May 2022

PROCEDURE OF EXTRACTING THIN ICE AREAS IN THE SEA OF OKHOTSK USING MODIS DATA

K. Cho and K. Naoki K. Cho and K. Naoki
  • Tokai University Research & Information Center, 2-3-23, Takanawa, Minato-ku, Tokyo, 108-8619, Japan

Keywords: sea ice, Aqua, global warming, ice thickness, RSI, OLI

Abstract. The latest IPCC report clearly stated that the human influence is the main reason of sea ice reduction in the Arctic. Importance of sea ice monitoring from space is increasing. In addition, the heat flux of ice in thin ice areas is strongly affected by the ice thickness difference. Therefore, ice thickness is one of the important parameters of sea ice. The authors have been studying on extracting thin ice areas using optical sensor such as MODIS for years. In this paper, the authors summarized the procedure of our study starting from comparing in-situ measurement of ice thickness with high resolution optical sensor RSI data, and finally developing the thin ice area extraction algorithm using MODIS. Estimating ice thickness from optical sensor data is not easy. However, through our study, the authors have verified the possibility of extracting thin ice areas using optical sensor data observed from satellites. In this study, the authors define “thin ice areas” as ice which thickness is less than about 30 cm with reflectance much lower than thick ice. The basic idea of the algorithm is to use the scatterplots of MODIS band 1 & 2 reflectance and extract thin ice areas using the distribution difference of thin ice against water, thick ice, clouds. Not all but most of the thin ice areas could be extracted using the algorithm.