Spatial Analysis of Urbanization Patterns in Four Rapidly Growing South Asian Cities Using Sentinel-2 Data

Abstract

The rapid and dominant urbanization in Asian cities has fueled concerns regarding the local and global efforts toward urban sustainability. Specifically, South Asian cities have been a topical issue concerning ecological and environmental threats due to their unplanned and haphazard urban development. However, comparative urbanization studies in South Asian cities remain uncommon. Therefore, in this study, we sought to comparatively examine the land use and land cover (LULC) dynamics and to detect the urbanization patterns of four rapidly developing South Asian lowland cities: Mumbai (India), Colombo (Sri Lanka), Karachi (Pakistan), and Dhaka (Bangladesh). Sentinel-2 (10 m) data and various geospatial approaches, including urban–rural gradient and grid-based methods, statistics, and urban landscape metric techniques, were used to facilitate the analysis. The study revealed that Mumbai, Karachi, and Dhaka had larger built-up landscapes compared to Colombo. Mumbai had the highest percentage of green spaces, followed by Colombo. Dhaka and Karachi had relatively small percentages of green spaces. Colombo and Dhaka had more croplands, which consistently increased along the urban–rural gradient compared to Mumbai and Karachi. Karachi showed that the only major land use was built-up, while most of the areas were left as open lands. On the other hand, Colombo’s urban setup was more fragmented than the other three cities. Mumbai and Karachi had larger patches of urban footprints compared to Colombo and Dhaka. Thus, this study provides vital information on the past land utilization priorities in the four cities, and comparatively proffers guidance on certain critical areas of focus for local, regional, and global future sustainable urban planning.

Characterizing Spatiotemporal Variations in the Urban Thermal Environment Related to Land Cover Changes in Karachi, Pakistan, from 2000 to 2020

“…Hassan et al [11] conducted a comparative study to examine the changes in the thermal environment in seven South Asian megacities from 2000 to 2019 using yearly average LST from MODIS data with a 1-km spatial resolution. A comparative study was conducted to detect the urbanization patterns of four rapidly developing lowland South Asian cities, including Karachi, in 2019 [29]. Despite these efforts, multitemporal satellite remote sensing data have been insufficiently employed, and our knowledge on the long-term evolution of SUHI and concurrent LULC changes in Karachi is still lacking.…”

Quantification of Urban Patterns and Processes through Space and Time Using Remote Sensing Data: A Comparative Study between Three Saudi Arabian Cities

“…For example, Seto and Fragkias [4] emphasised that the concentric rings capture development processes from the urban centre of various urban-rural areas. Ranagalage et al [62] applied a gradient analysis using concentric rings around the urban core centre to capture the spatial distribution dynamics of land use and cover from the city centre to the rural areas. This is emphasised also in this research, in which the analysis of the concentric rings showed the urban patterns for each buffer during each period, including the outskirts.…”

Assessing the prediction of type 2 diabetes risk using polygenic and clinical risk scores in South Asian study populations

“…13 Details of other demographic characteristics, including anthropometric measurements, physical activity, smoking, alcohol consumption, and diet, are described elsewhere. 38,42 Briefly, BMI was calculated as weight (kg)/height (meter) 2 , and waist-to-hip ratio (WHR) was calculated as the ratio of waist circumference to hip circumference. Blood pressure (BP) was measured twice after a 5-min seated rest period with the participant's feet flat on the floor.…”

“… 1 The region of South Asia (consisting of people from India, Pakistan, Bangladesh, Nepal, Bhutan, and Sri Lanka) is the epicenter of the growing epidemic of T2D due to rapid urbanization, immense population growth, and aging. 2 , 3 Studies performed on immigrant Indians outside India have shown that T2D and coronary artery disease incidence is three to six times higher in immigrant Asian Indians (AIs) than Euro-Caucasians. The onset of T2D is roughly a decade earlier [even at a lower body mass index (BMI)] in AIs than in Europeans.…”