A Semi Automated Method for Laminated Sediments Analysis  

作　　者：Mapathe Ndiaye Eric Davaud Daniel Ariztegui Meissa Fall 

机构地区：[1]Laboratoire de Mécanique et Modélisation, Université de Thiès, Thiès, Senegal

出　　处：《International Journal of Geosciences》2012年第1期206-210,共5页地球科学国际期刊（英文）

摘　　要：We developed a software performing laminae counting, thickness measurements, spectral and wavelet analysis of laminated sediments embedded signal. We validated the software on varved sediments. Varved laminae are automatically counted using an image analysis classification method based on K-Nearest Neighbors (KNN) algorithm. In a next step, the signal corresponding to varved black laminae thickness variation is retrieved. The obtained signal is a good proxy to study the paleoclimatic constraints controlling sedimentation. Finally, the use of spectral and wavelet analysis methods on the variation of black laminae thickness revealed the existence of frequencies and periods which can be linked to known paleoclimatic events.We developed a software performing laminae counting, thickness measurements, spectral and wavelet analysis of laminated sediments embedded signal. We validated the software on varved sediments. Varved laminae are automatically counted using an image analysis classification method based on K-Nearest Neighbors (KNN) algorithm. In a next step, the signal corresponding to varved black laminae thickness variation is retrieved. The obtained signal is a good proxy to study the paleoclimatic constraints controlling sedimentation. Finally, the use of spectral and wavelet analysis methods on the variation of black laminae thickness revealed the existence of frequencies and periods which can be linked to known paleoclimatic events.

关 键 词：VARVE LAMINATED SEDIMENT K-Nearest NEIGHBOR Signal Time-Series Spectral ANALYSIS WAVELET ANALYSIS 

分 类 号：R73[医药卫生—肿瘤]