所属领域：
印太交汇区海洋物质能量中心形成演化过程与机制
资源类型：
人工智能与海洋大数据
/ 海洋大数据
文献作者：
Kim, KwangJin; Lee, Yang-Won
文献发表年份：
2013
文献期刊：
HIGH-PERFORMANCE COMPUTING IN REMOTE SENSING III
文献摘要：Despite the same purpose, each satellite product has different value because of its inescapable uncertainty. Also the satellite products have been calculated for a long time, and the kinds of the products are various and enormous. So the efforts for reducing the uncertainty and dealing with enormous data will be necessary. In this paper, we create an ensemble Sea Surface Temperature(SST) using MODIS Aqua, MODIS Terra and COMS(Communication Ocean & Meteorological Satellite). We used Bayesian Model Averaging(BMA) as ensemble method. The principle of the BMA is synthesizing the conditional probability density function(PDF) using posterior probability as weight. The posterior probability is estimated using EM algorithm. The BMA PDF is obtained by weighted average. As the result, the ensemble SST showed the lowest RMSE and MAE, which proves the applicability of BMA for satellite data ensemble. As future work, parallel processing techniques using Hadoop framework will be adopted for more efficient computation of very big satellite data.
文献类型： Proceedings Paper
文献语种： English
关键词： Ensemble; BMA; EM algorithm; SST; COMS; Big data; Hadoop
文献作者地址： [Kim, KwangJin; Lee, Yang-Won] Pukyong Natl Univ, Dept Spatial Informat Engn, Pusan 608737, South Korea
