期刊
REMOTE SENSING OF ENVIRONMENT
卷 123, 期 -, 页码 339-346出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2012.03.028
关键词
Mesoscale; Front; Filament; Automatic detection; Satellite data; Upwelling; Canary system
An improved automatic detection of mesoscale frontal activity is proposed, based on the edge detection algorithm initially presented by Cayula and Cornillon (1992). The performance and the sensitivity of their original method have been extensively tested on a very large MODIS SST data set at 1 km resolution, over the Canary Upwelling System, and compared to the results of a classic gradient based method. Its evaluation, including the companion method using a contour-following algorithm, shows that a significant part of the fronts was not detected by the earlier method despite an overall robustness. We propose here an improved implementation of the single image edge detection algorithm, from the best combination of multiple detections based on sliding windows (referred to as CMW). The results show a very significant increase of the overall performance: using a time series of 6 years (1,988 images), we observed an average increase of 140% in the edge detection and 30% improvement in the average length of the segments. Additionally, the sensitivity to the size of the detection window is lower, and the necessity of using the following algorithm is greatly reduced. We applied the CMW improvements to the Canary Current System, and showed frontal activity developed along the whole coast, with more intense fronts between Cape Ghir (30 degrees 30' N) and Cape Beddouza (32 degrees 30' N), and between Cape Juby (28 degrees N) and Cape Bojador (26 degrees 30' N). The highest filament activity was associated with Cape Bojador followed by Cape Ghir and Cape Blanco (21 degrees N). Considering the seasonality, two main areas were identified, north and south of Cape Juby, with marked seasonality in the fronts and filaments. No major interannual differences in frontal activity were observed in 2002-2007, except less seasonality during 2007. (C) 2012 Elsevier Inc. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据