TY - CHAP A1 - Sílvia Antunes A2 - Oliveira Pires A3 - Alfredo Rocha ED1 - Parinya Sanguansat Y1 - 2012-03-07 PY - 2012 T1 - Improving the Knowledge of Climatic Variability Patterns Using Spatio-Temporal Principal Component Analysis N2 - This book is aimed at raising awareness of researchers, scientists and engineers on the benefits of Principal Component Analysis (PCA) in data analysis. In this book, the reader will find the applications of PCA in fields such as energy, multi-sensor data fusion, materials science, gas chromatographic analysis, ecology, video and image processing, agriculture, color coating, climate and automatic target recognition. BT - Principal Component Analysis SP - Ch. 10 UR - https://doi.org/10.5772/38448 DO - 10.5772/38448 SN - PB - IntechOpen CY - Rijeka Y2 - 2019-11-18 ER -