Urban green space (UGS) is although play a vital role in the mitigation of negative impacts of urbanization, but it often abominably affected by the process of land-use land-cover (LULC) changes in an urban area. Thus, the present study aims to examine the loss in urban green space (UGS) in relation to LULC change by using a multitemporal land-use transition scenario and to predict the loss of UGS in the future in the city Kolkata. Landsat satellite data (for years 1980, 1991, 2001, 2011 and 2018) were used for analysis. We have adopted three comparative land classification algorithms for the assessment of urban growth pattern. An integrated cellular automata-Markov chain (CA-MC) model was applied to simulate LULC dynamics and the state of UGS in 2025 and 2035. Land use dynamic degree index (LUDD), UGS change intensity index (CII) and UGS land index were used to measure the rate and speed of urban growth, the ratio of change of green space and UGS coverage in respect to the total area of all LULC types, respectively. To measure UGS availability, per-capita urban green space (PCG) was estimated. The model was validated using observed and simulated LULC map 2018. The standard Kappa coefficient value was 0.861 and overall level of agreement was 91.15%, which signifies the efficiency of this simulation. The result shows that the built-up areas were increased from 92.71 sq. km in 1980 to 148.30 sq. km in 2018 and predicted to increase 155.67 sq. km which will be about 84% of the total area.
Correspondingly, the predicted results displayed that, vegetation and grassland area were decreased about 17.42% and 11.69% for the period of 2025–2035, respectively. The present study provides some productive methodological approach for future LULC simulation research and also the findings of this study can help implement UGS management strategies not only for the Kolkata but other cities as well.
An integrated simulation approach to the assessment of urban growth pattern and loss in urban green space in Kolkata, India: A GIS-based analysis
Year: 2021
