Urban growth monitoring using spatial landscape matrices

Removing some of the content that was a bit irrelevant.

Working on the maps I used to make them better visually

With over 80% of global GDP created in cities, urbanization may contribute to long-term growth if properly managed. (The World Bank, 2021). In Uganda, the population living in urban areas are rising at a rate of 2.335% since 1990 to 2020. Cities must act fast to plan for expansion and provide the fundamental services, infrastructure, and affordable housing that their growing populations require. Urbanisation occurs at the expense of transformation of other landscapes hence the process of urbanization has a large influence on landscape and ecosystem function. For assessing policy alternatives for future growth and sustainable development of urban planning must be considered. Through mapping and analyzing land use/land cover transition in urban areas, as well as monitoring their environmental effects with the help of landscape metrices was the focus of this research. Landsat Images of 1990, 2000, 2010 and 2020 were used for this study, band ratios of NDVI, NDBI, NDWI were used for image enhancement to clearly identify the vegetated areas, built up areas and the areas that were covered with water, then a maximum likelihood classification technique was used to classify the images accordingly with an accuracy assessment of above 80% was accepted, the resulting classified images were then taken to FRAGSTATS for computation of landscape metrices. The metrices examined included class area, number of patches, total core area, core area percent of landscape, splitting Index, and landscape division index. It was discovered that the urban areas that converged between 1990 and 2020 contributed significantly to the fragmentation of predominantly the primarily vegetated regions of the research area, as well as the loss of the core portions of several habitats.