The COVID-19 pandemic's footprint in India: An assessment on the district-level susceptibility and vulnerability

In this nationwide study, we trace the COVID-19 global pandemic's footprint across India's districts. We identify its primary epicentres, which are the major international airports of Mumbai and Delhi. We then track the outbreak into India's hinterlands in four separate time-steps that encapsulate the different lockdown stages implemented. Using a detailed district-level database that encompasses climatic, demographic and socioeconomic parameters, we identify hotspots and significant clusters of COVID-19 cases, which are examined to discern temporal changes and predict areas where the pandemic can next spread into. Of prime concern are the significant clusters in the country's western and northern parts and the threat of rising numbers in the east. Encouraging insights emerge from Kerala in South India, where virus hotspots have been eradicated through effective contact-tracing, mass testing and accessible treatment. Allied with this, we perform epidemiological and socioeconomic susceptibility and vulnerability analyses. The former elicits areas whose resident populations are likely to be physiologically weaker in combating the virus and therein we expect a high incidence of cases. The latter shows regions that can report high fatalities due to ambient poor demographic and health-related factors. Correlations derived from the generalised additive model show that a high share of urban population and high population density (1500-2500 people/km2), particularly in slum areas, elevate the COVID-19 risk. Aspirational districts have a higher magnitude of transmission (susceptibility) as well as fatality (vulnerability). Discerning such locations can allow targeted resource allocation by governments to combat the next phase of this pandemic in India

Monitoring Metropolitan Growth Dynamics for Achieving Sustainable Urbanization (SDG 11.3) in Kolkata Metropolitan Area, India

From MDPI via Jisc Publications RouterHistory: accepted 2021-10-29, pub-electronic 2021-11-03Publication status: PublishedThe mass accumulation of population in the larger cities of India has led to accelerated and unprecedented peripheral urban expansion over the last few decades. This rapid peripheral growth is characterized by an uncontrolled, low density, fragmented and haphazard patchwork of development popularly known as urban sprawl. The Kolkata Metropolitan Area (KMA) has been one of the fastest-growing metropolitan areas in India and is experiencing rampant suburbanization and peripheral expansion. Hence, understanding urban growth and its dynamics in these rapidly changing environments is critical for city planners and resource managers. Furthermore, understanding urban expansion and urban growth patterns are essential for achieving inclusive and sustainable urbanization as defined by the United Nations in the Sustainable Development Goals (e.g., SDGs, 11.3). The present research attempts to quantify and model the urban growth dynamics of large and diverse metropolitan areas with a distinct methodology considering the case of KMA. In the study, land use and land cover (LULC) maps of KMA were prepared for three different years (i.e., for 1996, 2006, and 2016) through the classification of Landsat imagery using a support vector machine (SVM) classification approach. Then, change detection analysis, landscape metrics, a concentric zone approach, and Shannon’s entropy approach were applied for spatiotemporal assessment and quantification of urban growth in KMA. The achieved classification accuracies were found to be 89.75%, 92.00%, and 92.75%, with corresponding Kappa values of 0.879, 0.904, and 0.912 for 1996, 2006, and 2016, respectively. It is concluded that KMA has been experiencing typical urban sprawl. The peri-urban areas (i.e., KMA-rural) are growing rapidly, and are characterized by leapfrogging and fragmented built-up area development, compared to the central KMA (i.e., KMA-urban), which has become more compact in recent years

Where Is the Peri-Urban? A Systematic Review of Peri-Urban Research and Approaches for Its Identification and Demarcation Worldwide

Metropolitan areas worldwide have grown rapidly and are usually surrounded by peri-urban zones that are neither urban nor rural. Despite widespread use of the term ‘peri-urban’, physical determination of these spaces is difficult due to their transient nature and multiple definitions. While many have identified peri-urban areas regionally or globally, questions persist on where exactly the peri-urban is located, and what are the most apt methods to delineate its boundaries. The answers are pertinent towards framing targeted policies for governing the dynamic socio-spatial transformations in these zones. This paper reviews peri-urban research over the last 50-plus years to discern the existing methodologies for its identification/demarcation and their applications. For this, a total of 3124 documents on peri-urban studies were identified through keyword searches in Scopus and Google Scholar databases. Thereafter, 56 documents were examined that explicitly dealt with demarcating peri-urban zones. Results reveal that there is no standout/generalized method for peri-urban demarcation. Rather, these approaches are geographically specific and vary across developed and developing countries, due to differences in land-use patterns, socioeconomic drivers, and political systems. Thus, we recommend developing a ‘pluralistic’ framework for determining peri-urban boundaries at the regional–global scale to enable better framing of relevant policies

Preparing turbidity and aquatic vegetation inventory for waterlogged wetlands in Lower Barpani sub-watersheds (Assam), India using geospatial technology

AbstractWetlands play a significant role in maintaining environmental stability. These have a complex of values like food storage, water quality maintenance, livelihood and support species diversity, etc. Wetlands inventory is the pre-requisite process for conservation and management practices. The study makes an attempt to delineate wetlands and prepare inventory for turbidity and aquatic vegetation in Lower Barpani sub-watersheds (Assam), India. The study utilized Landsat 8 OLI (Operational Land Imager) data during pre- and post-monsoon seasons, 2014. Wetlands during pre- and post-monsoon were delineated using supervised classification and threshold method. Wetland inventory for turbidity and aquatic vegetation was prepared during pre- and post-monsoon seasons. Single-band turbidity retrieval algorithm and normalized difference vegetation index (NDVI) were used to assess the level of turbidity and aquatic vegetation in GIS environment. The study revealed that the variation in the extent of water logged wetlands in sub-watersheds was due to water spread variation during pre- and post-monsoon seasons. All the sub-watersheds were characterized by medium turbidity which was attributed to sediments and silts brought with runoff in wetlands. Aquatic vegetation showed variation in its distribution across sub-watersheds. High vegetation indicated high turbidity and presence of nutrients. The study shows usefulness of remote sensing data in mapping and characterization of wetlands for preparing inventory and monitoring seasonal variation