What is the Fourier Transform of a Spatial Point Process?

point patterns
spectral analysis
Authors
Affiliations

Tuomas Rajala

Natural Resources Institute Finland

Sofia Olhede

EPFL

Jake P Grainger

EPFL

David J Murrell

UCL

Published

August 1, 2023

Doi

Abstract

This paper determines how to define a discretely implemented Fourier transform when analysing an observed spatial point process. To develop this transform we answer four questions; first what is the natural definition of a Fourier transform, and what are its spectral moments, second we calculate fourth order moments of the Fourier transform using Campbell’s theorem. Third we determine how to implement tapering, an important component for spectral analysis of other stochastic processes. Fourth we answer the question of how to produce an isotropic representation of the Fourier transform of the process. This determines the basic spectral properties of an observed spatial point process.

Fig. 1. A realisation of a log-Gaussian Cox process (left), the estimated against true product density (middle), and estimated against true spectral density function on a decibel scale (right).