ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Citation
Articles | Volume X-3-2024
https://doi.org/10.5194/isprs-annals-X-3-2024-237-2024
https://doi.org/10.5194/isprs-annals-X-3-2024-237-2024
04 Nov 2024
 | 04 Nov 2024

Evaluating the Spatio-Temporal Distribution of Nitrogen Dioxide, Land Surface Temperature and NDVI in Nairobi City County

Patricia Mwangi

Keywords: Air Pollution, Sentinel-5P, Nitrogen Dioxide, Land Surface Temperature, Population Density, NDVI

Abstract. Cities are becoming larger and it is estimated that by the year 2050, more than 6 billion people will be living in cities. As cities expand and grow, the quality of life and conditions will also transform. An integral part of environmental studies has been statistical analysis in modelling the spatial dynamics of land use changes. The research involved the use of satellite imagery to determine yearly averaged values of LST and NDVI from Landsat 8 OLI/TIR and monthly mean values of Nitrogen Dioxide (NO2) from Sentinel 5-Precursor (Sentinel-5P) across Nairobi City County. The datasets covered the period 2019, 2020, 2021, 2022 and 2023 and were analysed in Google Earth Engine. Results indicated that the yearly mean values in NO2 and LST in 2020 reduced by 2% and 12% respectively from 2019, while the mean NDVI value significantly increased by 28% in 2020 from 2019. NO2 has a negative correlation with LST in all years and a positive correlation with NDVI. Pearson correlation with population densities in constituencies in Nairobi in 2019 and 2023 indicate a negative correlation with NDVI and a positive correlation with NO2 and LST. Constituencies that have higher population densities tend to have lower vegetation densities and higher NO2 concentrations and temperature. Vegetation therefore plays a crucial role in air quality and that climatic factors such as precipitation and temperature influence the concentration of pollutants.