Quantifying deforestation drivers through multi-temporal LULC analysis and population-forest correlation modeling: A case study of Dara Woreda, Ethiopia

Abstract

This study introduces a novel approach to analyzing deforestation in Dara Woreda, Ethiopia, by quantitatively modeling the correlation between population growth and forest cover decline using multi-temporal Land Use and Land Cover (LULC) data. Employing Geographic Information Systems (GIS) and Remote Sensing, the research rigorously collected and analyzed statistical and spatial data from satellite imagery, census records, and official reports. A key strength of this study lies in the precisely assessed accuracy of LULC classifications for 1990, 2005, and 2020, demonstrating a high level of agreement with reference data, thereby providing a robust foundation for understanding long-term changes. The findings reveal a significant and quantifiable decline in forest cover from 16.90 km² (6.76 %) in 1990 to 6.25 km² (2.50 %) by 2020, underscoring a substantial deforestation trend. Conversely, agricultural land significantly expanded from 113.37 km² (45.35 %) to 141.92 km² (56.77 %), highlighting the extent of natural ecosystem conversion. Notably, the study demonstrates a strong temporal correlation between the 87.2 % population growth in Dara Woreda between 1990 and 2020 and the corresponding 63.0 % degradation in forest cover during the same period. The most rapid deforestation (48.7 %) occurred between 1990 and 2005, suggesting the influence of specific socio-economic drivers during this time. While the rate of forest loss slowed between 2005 and 2020, the continued decline indicates persistent unsustainable land use practices. These temporally specific and quantitatively robust findings offer critical and novel insights for policymakers and stakeholders in Dara Woreda, providing a strong evidence base for the development and implementation of targeted sustainable land management strategies to effectively combat ongoing deforestation.