NSI Specialist Quantifies Causal Drivers of Vegetation Degradation in the Chad Basin , Africa

A paper authored by Dr. Arnob Bormudoi and Prof. Dr. Masahiko Nagai, associated with Yamaguchi University and New Space Intelligence, Inc., has been published in the international journal, GeoHazards.

Paper Abstract

This study establishes rigorous, quantitative causal relationships between climatic drought indicators and vegetation degradation in the Chad Basin from 2000 to 2023

• Analysis Method: The research implemented a Machine Learning-Enhanced Transfer Entropy (ML-TE) framework

By utilizing a Feed-forward Neural Network trained on 10,000 synthetic samples, the study successfully overcame the statistical limitations traditionally associated with analyzing short-term remote sensing time series

• Key Finding: The study revealed that precipitation and land surface temperature exert comparable causal influences on vegetation dynamics, but their geographic "causal hotspots" differ significantly. Furthermore, the basin experienced an accelerating 13.8% reduction in mean vegetation (NDVI) between 2019 and 2023, highlighting the urgent need for specific management strategies. 

This research provides a replicable, spatially explicit foundation for assessing ecosystem vulnerability and informing climate adaptation policies in data-limited dryland environments.

Publication Details

• Authors: Arnob Bormudoi, Masahiko Nagai

• Paper Title: Quantifying Causal Impact of Drought on Vegetation Degradation in the Chad Basin (2000–2023) with Machine Learning-Enhanced Transfer Entropy

• Journal: GeoHazards 2026, 7(1), 2

• DOI: 10.3390/ geohazards7010002