Quantifying persistence in nighttime light trends with memory-modulated Brownian motion

Abstract

This study investigates the dynamics of nighttime light (NTL) trends using NASA's Black Marble dataset. NTL is a widely used proxy for various socio-economic indicators, and here, we employ a stochastic framework that captures the memory and modulation of past NTL values. The analysis reveals persistent trends and quantifies the degree of fluctuation across different time scales using Mean Squared Displacements (MSD). Notably, the model parameters derived from MSD fitting exhibit consistency across different regions, suggesting a universality in the underlying processes governing NTL trend variations. Furthermore, the First Passage Time Density (FPTD) analysis highlights regional differences in critical times needed for NTL to reach specific thresholds. This study demonstrates the feasibility of a memory-modulated Brownian Motion in modeling NTL trend dynamics, offering insights into the complex socio-economic and environmental factors reflected in nighttime lights.