The impact of urbanization on land use land cover change using geographic information system and remote sensing: a case of Mizan Aman City Southwest Ethiopia
Abstract Land use land cover change due to urbanization is the prime driving forces to environmental problem and land surface temperature. The gap of the study is the lack of awareness of stakeholders regarding the protection of native forests, fruit trees, and BEBEKA coffee plantations. Deforestati...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-94189-6 |
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| Summary: | Abstract Land use land cover change due to urbanization is the prime driving forces to environmental problem and land surface temperature. The gap of the study is the lack of awareness of stakeholders regarding the protection of native forests, fruit trees, and BEBEKA coffee plantations. Deforestation for urban functions, including timber production, construction materials, and firewood, adversely affects the environment. The aim of this study was to analyze the effect of urbanization on Land Use Land Cover Change (LULCC) at Mizan Aman city, southwest Ethiopia from 1992 to 2022 using geographic information systemand remote sensing technique. The study employed systematic sampling household surveys and high-resolution remote sensing techniques to identify the impact of urbanization on land use land cover change and land surface temperature change. Sample household survey was focused on family size, education level, parcel, year of construction of the house, type of employment and monthly household income. The LULC classification were based on eight land cover class (settlement, dense forest, moderate forest, sparse forest, closed grassland, open grassland, open shrub land, annual crop land). Preprocessing, classification of the images and accuracy assessment were tested separately using the kappa coefficient. The analysis incorporates factor graph optimization for ambiguity resolution. The results indicated that cumulative accuracy were 81.52%, 82.96%, 85.41% and 84.46% and kappa coefficient 82.41%, 84.86%, 89.45% and 88.76%% for the year 1992, 2002, 2012 and 2022 respectively. This research showed that dense forest, moderate forest, sparse forest and open shrub land were significantly decreased by 68.96%, 24.60%, 31.36% and 8.28% respectively in the last 30 years. Urban settlement were increased at alarming rate due to land demand for housing, infrastructure and manufacturing. Therefore, urban planners must prioritize sustainable environmental management, integrated land use zoning, and active community involvement in order to protect against unsustainable changes in land use and land cover. For future research, incorporating methodologies such as multi-source remote sensing and high-resolution imaging will help differentiate land cover more effectively. Mizan Aman City experiences a nine-month rainy season with a hot climate, and cloud cover can affect image quality, making it challenging to map land covers clearly. Utilizing SENTINEL high-resolution data can enhance ambiguity resolution and improve spatio-temporal monitoring frameworks. Furthermore, integrating CO2 estimation techniques could offer deeper insights into the environmental changes associated with urbanization. |
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| ISSN: | 2045-2322 |