研究目的
To validate the AMSR-E ASI sea ice concentration products using MODIS data and aerial images, and compare sea ice extent and area derived from different algorithms.
研究成果
The AMSR-E ASI SIC products underestimate sea ice concentrations by an average of 17.9% compared to aerial images and 8.5% compared to MODIS images, with higher errors in low SIC regions. SIE and SIA from DT-ASI algorithm show biases compared to ASI, with seasonal variations. The study highlights the need for improved validation and algorithm adjustments in polar sea ice monitoring.
研究不足
The validation is based on a limited dataset from a specific region and time (Antarctic Amery Ice Shelf on January 9, 2011), which may not represent all polar conditions. The DT-ASI algorithm has not been applied in the Antarctic, limiting the comparison scope. Potential underestimation factors like thin ice or snow flooding are noted but not fully quantified.
1：Experimental Design and Method Selection:
The study involves validating AMSR-E ASI SIC products by comparing them with SICs derived from high-resolution aerial images and MODIS data. Methods include the MINERROR threshold algorithm for ice-water discrimination in aerial images and tie-point method for MODIS SIC retrieval.
2：Sample Selection and Data Sources:
Data sources include daily mean AMSR-E SIC products from Bremen University, aerial photographs from a helicopter survey in front of the Antarctic Amery Ice Shelf on January 9, 2011, and MODIS L1 reflectance data from the Aqua satellite.
3：List of Experimental Equipment and Materials:
Equipment includes a helicopter with an anchored camera for aerial photography, AMSR-E and AMSR2 sensors, and MODIS aboard Aqua satellite.
4：Experimental Procedures and Operational Workflow:
Aerial images were composited and geolocated, then processed using MINERROR algorithm to create ice-water binary images. MODIS data were processed using tie-point method to retrieve SICs. SICs from aerial and MODIS images were projected onto AMSR-E grids for comparison.
5：Data Analysis Methods:
Statistical comparison of SICs, calculation of biases and relative errors, and analysis of SIE and SIA from different algorithms.
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