Land use/land cover dynamics on vulnerable regions in Uruguay approached by a method combining Maximum Entropy and Population Dynamics

TL;DR

This paper introduces a novel method combining Lotka-Volterra equations and maximum entropy to model and predict land use and cover changes in Uruguay, outperforming traditional Markov chain models.

Contribution

The paper presents a new approach integrating population dynamics and maximum entropy for land cover change prediction, applied to Uruguayan vulnerable regions.

Findings

LVPME method outperforms Markov chains in prediction accuracy

Effective modeling of LULC class interactions over time

Application to Uruguayan data demonstrates method's utility

Abstract

We present an exploratory population dynamics approach, described by Lotka-Volterra (LV) generalized equations, to explain/predict the dynamics and competition between land use/land cover (LULC) classes over vulnerable regions in Uruguay. We use the Mapbiomas-Pampa dataset composed by 20 annual LULC maps from 2000-2019. From these LULC maps we extract the main LULC classes, their spatial distribution and the time series of areas covered for each class. The interaction coefficients between species are inferred through the pairwise maximum entropy (PME) method from the spatial covariance matrices for different training periods. The main finding is that this LVPME method globally outperforms the more traditional Markov chains approach at predicting the trajectories of areas of LULC classes.