Assessing Urban Environmental Vulnerability Through CRITIC-Weighted Biophysical and Atmospheric Remote Sensing Indicators

Rapid urbanization in Sub-Saharan Africa demands integrative frameworks capable of capturing coupled land–atmosphere vulnerability dynamics. This study develops a high-resolution, multi-parameter assessment of urban environmental vulnerability in Ibadan, Nigeria. Multi-source satellite data (Landsat 8, Sentinel-5P, VIIRS, MODIS) acquired for 2020 and 2025 were integrated to derive indicators spanning biophysical, thermal, and atmospheric domains, including the Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Land Surface Temperature (LST), nitrogen dioxide (NO₂), sulphur dioxide (SO₂), methane (CH₄), Aerosol Optical Depth (AOD), and Nighttime Light (NTL). The CRITIC method was applied to objectively weight these parameters and construct an Urban Environmental Vulnerability Index (UEVI) for each year, and Land use/ land cover (LULC) maps for 2015, 2020, and 2025 were produced from Sentinel-2 using a Random Forest classifier. LULC change (2015–2025) shows a net built-up increase of + 2.09% and a − 7.40% decline in vegetation, indicating reduced ecological buffering. The decisive shift occurred during the post-COVID recovery phase, when atmospheric concentrations increased in magnitude and spatial extent across the metropolis, as evidenced by the expansion and intensification of nitrogen dioxide (NO₂) and methane (CH₄) pollution. CRITIC weights confirm pollutant dominance in 2020 and 2025, respectively—AOD (0.22, 0.15), SO₂ (0.18, 0.22), CH₄ (0.15, 0.16), and NO₂ (0.13, 0.13)—while surface indicators remained secondary. Synthesized within UEVI, these cumulative pressures correspond with a net + 11.18% expansion of Critical zones and a − 8.56% contraction of Resilient areas between 2020 and 2025, indicating rapid deterioration in environmental stability. The findings demonstrate that expanding vulnerability reflects the combined effect of land transformation and intensifying atmospheric stressors, providing actionable evidence for air-quality governance and risk-sensitive spatial planning aligned with SDGs 11, 13, and 15.

The graphical abstract presents a comprehensive and integrated framework for assessing urban environmental vulnerability using CRITIC-weighted biophysical and atmospheric remote sensing indicators. It begins with urban transformation (2015–2025), illustrating land use/land cover changes that highlight increasing built-up areas and declining vegetation. These changes are linked to a multi-sensor data integration approach incorporating Sentinel-2 (LULC), Landsat 8 (NDVI, LST), Sentinel-5P (NO₂, SO₂, CH₄), MODIS (AOD), and VIIRS-DNB (nighttime lights). The indicators are grouped into biophysical (NDVI, NDBI, LST, NTL) and atmospheric (NO₂, SO₂, CH₄, AOD) components, showing contrasting trends between ecological decline and pollutant intensification. Using the CRITIC objective weighting method, the framework identifies atmospheric pollutants as dominant contributors to vulnerability in both 2020 and 2025. The resulting Urban Environmental Vulnerability Index (UEVI) maps reveal spatial shifts toward increased Critical zones and reduced Resilient areas between 2020 and 2025. Overall, the graphic conveys a coherent flow from urban change and multi-source data integration to weighted vulnerability assessment and policy implications for sustainable urban management.