Urban Growth Analysis and Modeling Using the MOLUSCE Model: A Case of Woliso Town

Abstract

Urbanization has been the major demographic trend globally. The purpose of this study was to analyze the spatio-temporal dynamics of urban growth in Woliso Town from 2004 to 2022 and predict its possible expansion up to 2031 using the MOLUSCE Model. As urban land use expand another land use/land cover were disproportionality affected. Rapid urban expansion has caused not only social problems, but also environmental and socioeconomic problems in the town. Thus, the town administration has to develop a mechanism that reduces urban expansion. To do this study there is high rate of urban expansion in Woliso town. This research used geospatial techniques for evaluate urban growth analysis and modeling using the MOLUSCE model: A Case of Woliso Town between 2004 and 2022. The data sets used were Landsat ETM 2004, 2013, and sentinel 2A of 2022. The train support vector machine classifier has used the algorithm to generate land-use/land-cover maps and assessment of urban dynamics. The MOLUSCE plugin was used to forecast land-use change for 2031. Analysis of Landsat image data of Woliso Town from 2004 –2022 showed there are significant land use and land cover changes in the town. In 2004, farm-land, vegetation, built-up area and open space covered 45.03 %, 45.6 %, 6.0 % and 3.34 % of the total area, respectively. In 2022, after two decades, the built-up area increased from 6% to 36.83% of the area. On the other hand, farm-land, vegetation and open space area were decreased from 45.03%, to 29.78%, 45.6% to32.83% and 3.34 to 0.54%, respectively. With existing conditions, the simulated LULC map of the year 2031 indicates the same trends that built-up areas will increase by 9.59% whereas Farm-land, vegetation and open space areas will be expected to decrease by 5.37%, 3.82% and 0.40% respectively. Therefore, the government has to provide different innovative policy reform strategies to overcome the business as usual scenario.