Combining Remote Sensing Inputs and Census Data for Assessing Urban Growth Patterns in Puducherry District, India

International audience

English. Monitoring the spatiotemporal changes that affect the landscape and coast due to urbanization process is important because of its impacts on the environment and population. In relation to that, this research aims to explore the use of remote sensing imagery, census data and different spatial metrics to assess the urban growth patterns and processes that occurred in Puducherry district (India) between 2011 and 2020. Urban development forms, landscape patterns and urban sprawl measurements are, respectively, performed using three complementary software packages: Urban Landscape Analysis Tool (ULAT), FRAGSTAT program and Urban Sprawl Metrics (USM) Toolset. Four land cover maps of 2011, 2014, 2017 and 2020 are created by using image interpretation of very high-resolution remote sensing images. In parallel, urbanized areas and urban footprint maps are generated and new development patterns during the study time periods are analyzed. The results highlight a significant increase in built-up areas, which are unevenly distributed over space and time. In addition to that, the analysis of spatial metrics illustrates a continuous fragmentation process of built-up area. Besides, the quantitative analysis of urban growth process indicates that the urban development from 2011 to 2020 was dominated by the expansion and leapfrogging growth patterns. The Weighted Urban Proliferation (WUP) metric, which is computed based on 2011 census data, indicates that the spatial urban patterns presented a low level of urban sprawl during the last decade. This study can help the city decision-makers to manage urban expansion in a sustainable way by providing useful results and input data for further analysis including the evaluation of the effectiveness of past urban planning policies and the simulation of future urban development scenarios.