Analysing spatial and geometrical patterns of urbanization using spatial metrics – A case study of Tiruchirappalli urban, India

Abstract The understanding of spatial and geometrical patterns in urbanization is crucial in tackling its associated problems. As urbanization progresses through various stages of development, it reflects different forms, patterns, and interactions based on physical and functional aspects. Spatial metrics, a well-regarded technique for quantifying urban characteristics, is one of several methods developed to achieve this. The current study was conducted in Tiruchirappalli and six other urban centres located within a 40-kilometre radius; which helps to comprehend the comparative growth and spatial patterns in relation to Tiruchirappalli urban centre. The urban centres were divided into eight zones based on direction for more precise quantification. The study employed Landsat 5 and 8 satellite images to classify land use/cover for the periods 1996, 2008, and 2020, which were then used to assess urban spatial growth and quantify spatial and geometrical patterns. Fragstat, a comprehensive application with several metrics, was used to analyse spatial metrics, including patch, class, and landscape levels, which focus on spatial configurations such as area and edge, aggregation, diversity, and shape. The study generated significant data about spatial and geometric properties, patterns, and obstructions of growth. The area and edge metrics and aggregation metrics indicated that Manachanallur, Manapparai, Musiri, Thiruverumbur, and Thuraiyur had the most unpredictable, random growth with highly protrusive urban growth in few zones across the study period. Diversity metrics demonstrated that Tiruchirappalli had the most abundant urban patches, with few patches from other classes. Shape metrics revealed significant improvements from 2008–2020 across all urban centres, whereas from 1996–2008, urban patches were more irregular in shape. The current study is a significant contribution to the urban research in understanding the relative spatial and geometric patterns of urbanization. The knowledge generated could aid in sustainable urban development planning and focus.