Empirical Mode Decomposition (EMD) transform for spatial analysis

Advances in Spatial Analysis and Decision Making 2026 Book chapter

View at publisher
Authors: Zizhao Li, Kourosh Khoshelham, Xiaoli Ding, Dawei Zheng
DOI: 10.1201/9781003762638-4
Cited by: 4

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.

Fields of Study & Subjects

Machine Fault Diagnosis Techniques

Publication details

Journal / source
Advances in Spatial Analysis and Decision Making
Publisher
CRC Press
Volume
1
Pages
19–29
Publication date
11 February 2026
Language
EN
Document type
Book chapter