Search

Urban form is generally accepted to be the most significant aspect controlling LST. This study analyzes the spatio-temporal urban growth pattern in India's rapidly urbanizing National Capital Region (NCR) to discern its dominant urban form based on urban sprawl metrics (USM - a neighborhood based built-up density approach) and traces its spatio-temporal growth patterns. It then gauges the relations between the landscape composition and various development modes of this dominant urban form with the ascertained nighttime LST distribution. The results of the USM based analysis show that the NCR's dominant urban form is constituted by the urban core, which has expanded markedly during the study period of 2000-2018. Within the urban core, nighttime LST increased, particularly during the fall months. Linear regression models (both non-spatial and spatial) reveal a positive relation between the nighttime LST and the built-up area and infilling growth mode. Contrarily, nighttime LST is negatively correlated with the edge-expansion and the respective areas under urbanized green and non-green open spaces. New planning approaches are thus required to restrict infilling based densification and promote well-planned edge-expansion with the designation of new green spaces as well as the greening existing non-green open spaces, particularly in areas underprovided with greenery.

The 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.