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.
