Investigating the Relationship Between Sustainable Urban Planning and Carbon Emission Using GIS

Abstract

Cabron emissions significantly contribute towards climate change and has become a major concern. To develop mitigation strategies against increasing carbon emissions, understanding of contribution factors influencing carbon emissions is important. This impact can be reduced by executing sustainable urban planning and adopting mitigating measures. This study examines the relationship between carbon emissions and landscape matrices by using panel data regression model. The study found that continuous increase in urban extent from 141 sqkm in 2013 to 413 sqkm in 2021. Using this urban extent, four landscape matrices of number of patches, patch density, mean perimeter area ratio and Euclidian nearest neighbor distance, were analyzed to study the impact of increasing urban extent. Results show decrease in number of patches and patch density showing inward urban sprawl. Decrease in mean perimeter area ratio shows fragmented development. Increasing Euclidian nearest neighbor distance show development of scattered population. For panel data analysis, disaggregated carbon emission maps were prepared using nighttime lights data and population counts. Disaggregated maps show an increase in carbon emission at a finer resolution. There is a 0.00398% average increase in carbon emissions per kilotonnes of population growth. A panel data regression model was employed to incorporate both temporal and spatial dimensions in the analysis between disaggregated carbon emissions and four landscape metrics. In conclusion the results show useful insights into the relationships between land use patterns and increase in carbon emissions. The panel data results can be used effectively to develop more sustainable land management practices and adoption of climate change mitigation strategies.