A method for change detection with multi-temporal satellite images based on Principal Component Analysis

Abstract

Currently remote sensing, based on satellite images is one of the most important source of information for multitemporal change detection. From all types of satellite images, the multispectral images present the advantage of characterizing the earth surface in different bands; each band provides different and useful information. In this work we propose a new methodology based on linear PCA to extract useful and meaningful information from signals provided by the remote sensing, and based on it, detect temporal changes Experiments based on images of the satellite CBERS-2B corresponding to the urban and peri urban region of Rio Cuarto of Córdoba state in Argentina have given satisfactory results in change detection.