Abstract:Understanding urban growth spatiotemporally is important for landscape and urban development planning. In this study, we examined the spatiotemporal pattern of urban growth of the Colombo Metropolitan Area (CMA)-Sri Lanka's only metropolitan area-from 1992 to 2014 using remote sensing data and GIS techniques. First, we classified three land-use/cover maps of the CMA (i.e., for 1992, 2001, and 2014) using Landsat data. Second, we examined the temporal pattern of urban land changes (ULCs; i.e., land changes from non-built-up to built-up) across two time intervals (1992-2001 and 2001-2014). Third, we examined the spatial pattern of ULCs along the gradients of various driver variables (e.g., distance to roads) and by using spatial metrics. Finally, we predicted the future urban growth of the CMA (2014-2050). Our results revealed that the CMA's built-up land has increased by 24,711 ha (221%) over the past 22 years (11,165 ha in 1992 to 35,876 ha in 2014), at a rate of 1123 ha per year. The analysis revealed that ULC was more intense or faster during the 2000s (1268 ha per year) than in the 1990s (914 ha per year), coinciding with the trends of population and economic growth. The results also revealed that most of the ULCs in both time intervals occurred in close proximity to roads and schools, while also showing some indications of landscape fragmentation and infill urban development patterns. The ULC modeling revealed that by 2030 and 2050, the CMA's built-up land will increase to 42,500 ha and 56,000 ha, respectively. Most of these projected gains of built-up land will be along the transport corridors and in proximity to the growth nodes. These findings are important in the context of landscape and urban development planning for the CMA. Overall, this study provides valuable information on the landscape transformation of the CMA, also highlighting some important challenges facing its future sustainable urban development.
Sri Lanka’s education system was suddenly shifted from classroom-based free education to online-based distance learning as an emergency teaching and learning method (ETLM) in response to the COVID-19 pandemic lockdown. This study examines how various stakeholders used online-based distant learning as an ETLM, and highlights the lessons learned from such a transition in Sri Lanka through a case study of the Kandy education zone (KEZ), in response to the country’s COVID-19 pandemic lockdown. We obtained the data through a questionnaire survey from 19 schools in KEZ, selecting the teachers, students, and parents as a survey sample. The findings revealed that nearly 64.7% of teachers used social media for the teaching–learning process (TLP), 27.9% used standard online teaching platforms, and only 7.4% used traditional teaching methods during the pandemic lockdown. Additionally, 36.5% of teachers and 41.2% of students favored the WhatsApp mobile application for the TLP, while others preferred other applications. However, during the COVID-19 lockdown, most of the less privileged schools in the peripheral areas of the KEZ adopted traditional teaching methods (TTM). The extent of the gap in ETLM adaptation and the driving factors that led to observable discrepancies between privileged and non-privileged schools, even in the urban settings of the KEZ, are also discussed in this study. These findings are significant in terms of educational policy making and management. Overall, this research contributes to understanding the ETLM adaptation of the KEZ by proposing policy directions that policymakers and other higher education authorities in the country should consider in an emergency.
In past decades, gradient pattern analysis has been used effectively to characterize the spatial pattern of population distribution in cities worldwide. Most of these studies have focused only on individual case studies or a limited number of cities. However, measuring, analyzing, and understanding complex spatial patterns of city population distribution requires comparative studies that extend beyond the isolated case of cities. Therefore, the present study analyses the spatial pattern of population distribution along the gradient distance from the city centers of the world’s 50 largest cities using LandScan™ population data from 2013 through a geospatial approach. For each city, the city center was demarcated based on a landmark place, and population density was calculated using concentric buffers from the city center. The study mainly identified five basic spatial patterns of population distribution along the gradient distance to the city center. In addition, the study contrasted the spatial patterns of population distribution between cities in developing and developed countries.
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