Empirical Mode Decomposition (EMD) transform for spatial analysis

Abstract

This paper describes a new method for spatial analysis – the Empirical Mode Decomposition (EMD) transform, which is the latest development in methods for signal decomposition. EMD is a data-driven method. In this transform, the basis of decomposition is derived from the data, instead of by using an a priori basis (sine, cosine and Wavelet) as is currently the case for all existing methods of data analysis; e.g., Fourier and Wavelet transforms. This adaptiveness has made EMD superior to some other methods in many ways. Examples of the use of EMD for spatial analysis such as signal extraction and data filtering are demonstrated. They show that EMD can be a powerful tool for spatial analysis.