ANNOUNCEMENTS
Urban green infrastructure becomes increasingly crucial to mitigate air pollution in cities like Delhi, where the air quality is frequently in the 'poor' to 'severe' zone. This study examines the role of tree canopy density for pollution removal and carbon sequestration in Deer Park and District Park, Hauz Khas District. There are 1022 individual trees of 62 species in Deer Park, which were surveyed, and 415 trees of 45 species were geolocated in District Park. Using an integrated platform with i-Tree Eco, GIS, remote sensing, and machine learning libraries in Python. This study geolocates trees' spatial position, quantifies NDVI, change in NDVI, changes in canopy cover between 2013 and 2025 using Landsat 8, Google Earth Pro. ArcMap GIS tools were used to map tree locations and then interpolate pollution levels using IDW, and conduct buffer-based zonal statistics to analyze the carbon storage and sequestration patterns around Hauz Khas Lake. Pollution removal estimates were generated using i-Tree Eco report. Future pollution removal trends were predicted by modeling tree growth and environmental factors using Predictive Modeling in Jupyter Notebook.
The results of study revealed notable changes in canopy density from the year 2013 to 2025, with NDVI showing a decline in the year 2019 and significant recovery by 2025, reaching up to 85–90% in core park zones. i-Tree Eco simulations confirmed that mature trees provided the highest carbon storage and pollution removal benefits. Machine learning projections indicated continued increases in carbon sequestration and pollutant removal over the next 50 years. Zonal statistical analysis further highlighted maximum carbon storage within the buffer of 100–175 meters of Hauz Khas lake, with gradual declines towards park boundaries.
