Abstract
Conventional deforestation risks models rely on linear approaches, failing to account for causal relationships among drivers. Yet several factors such as energy demand, urbanisation and agricultural expansion play different roles in deforestation. We propose a novel method integrating GIS-based spatial analysis and structural equation modeling to quantify direct and indirect effects of deforestation drivers. Results show that energy demand is a primary driver of deforestation and urbanization, while urbanization itself does not directly cause deforestation but influences indirectly through increased energy demand. This scalable model offers insights to support decision-making for balancing climate, urbanisation, energy security, and forest conservation.
| Original language | English |
|---|---|
| Title of host publication | 33rd Annual GIS Research UK Conference (GISRUK) |
| Number of pages | 8 |
| DOIs | |
| Publication status | Published - 23 Apr 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 13 Climate Action
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GeoSEM model for assessing deforestation risks
Abudu, D. (Creator), Bastin, L. (Creator), Chong, K. (Creator) & Röder, M. (Creator), 28 Feb 2025
DOI: 10.5281/zenodo.14758683, https://zenodo.org/records/14758683
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