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<p>Informal settlements (ISs), characterized by unauthorized occupation and construction without legal recognition, represent a critical urban challenge in rapidly developing cities like Addis Ababa, Ethiopia, where 23.8% of the urban population resides in ISs, driving substantial socio-economic and environmental losses. This study integrates Geographic Information Systems (GIS) and Logistic Regression (LR) modeling to map historical IS growth (2002–2022) using SPOT 5, 6 and Sentinel-2 imagery and project future expansion to 2042. Findings reveal a 224% increase in IS area from 2,260.5&#xa0;ha (2002) to 7,329.5&#xa0;ha (2022), primarily converting farmland and open spaces. The validated LR model (Kappa = 0.73, Pseudo-R<sup>2</sup> = 0.32) identified&#xa0;proximity to existing ISs&#xa0;(strongest positive influence; OR = 0.45, p &lt; 0.001),&#xa0;distance to roads&#xa0;(negative influence; OR = 0.74,&#xa0;p &lt; 0.01), and&#xa0;low population density&#xa0;(positive influence; OR = 1.65,&#xa0;p &lt; 0.05) as statistically significant drivers. Projections under current trends indicate IS expansion to 11,483.5&#xa0;ha (95% CI 10,850 –12,117&#xa0;ha) by 2032 and 18,557.9&#xa0;ha (95% CI) by 2042, with uncertainty quantified through sensitivity analysis and assuming static driver conditions. Model robustness also confirmed via spatial validation and advanced error metrics (quantity/allocation disagreement 10%). The study underscores regulatory inefficacy and urges spatially targeted interventions particularly protecting vulnerable public lands in high-probability peri-urban peripheries providing an evidence base for adaptive urban policy reform in Addis Ababa.</p>

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Geospatial mapping and prediction of informal settlement growth in Addis Ababa using GIS and logistic regression model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月27日

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  • Alazer Bergene Bante,
  • Kanenus Fufa Dararo,
  • Natnael Ketema Taddesse,
  • Indale Niguse Dejene

摘要

Informal settlements (ISs), characterized by unauthorized occupation and construction without legal recognition, represent a critical urban challenge in rapidly developing cities like Addis Ababa, Ethiopia, where 23.8% of the urban population resides in ISs, driving substantial socio-economic and environmental losses. This study integrates Geographic Information Systems (GIS) and Logistic Regression (LR) modeling to map historical IS growth (2002–2022) using SPOT 5, 6 and Sentinel-2 imagery and project future expansion to 2042. Findings reveal a 224% increase in IS area from 2,260.5 ha (2002) to 7,329.5 ha (2022), primarily converting farmland and open spaces. The validated LR model (Kappa = 0.73, Pseudo-R2 = 0.32) identified proximity to existing ISs (strongest positive influence; OR = 0.45, p < 0.001), distance to roads (negative influence; OR = 0.74, p < 0.01), and low population density (positive influence; OR = 1.65, p < 0.05) as statistically significant drivers. Projections under current trends indicate IS expansion to 11,483.5 ha (95% CI 10,850 –12,117 ha) by 2032 and 18,557.9 ha (95% CI) by 2042, with uncertainty quantified through sensitivity analysis and assuming static driver conditions. Model robustness also confirmed via spatial validation and advanced error metrics (quantity/allocation disagreement 10%). The study underscores regulatory inefficacy and urges spatially targeted interventions particularly protecting vulnerable public lands in high-probability peri-urban peripheries providing an evidence base for adaptive urban policy reform in Addis Ababa.