Assessment of how well vegetation health and nature-based solutions can offset climate change is vital for mitigation and adaptation planning but has rarely been done. This study assessed the role of vegetation health and NbS in mitigating climate change effects using the Normalised Difference Vegetation Index and Normalised Different Bare Surface Index, which were derived from Google Earth Engine and ArcGIS Pro 3.2. Precipitation and temperature data were collected from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and TERRACLIMATE, respectively. Pearson correlation explored the relationship between remote sensing indices, NbS and climate data. Four afforestation NbS case study projects were noted. NDVI increased by 35% over the study period. NDVI increase was noted (1990–2013), while decline was noted (2013–2023). NDBSI decreased (1990–2013) and increased (2013–2023). Precipitation increased by 22.7% (427.3 mm) (1990–2023), while temperature increased by 7.43% (1.5 °C) over the same period. Positive relationship between precipitation and NDVI (r = 0.5549) was noted, while a negative correlation between precipitation and NDBSI (r = −0.139) was realised. Temperature was both positively correlated with NDVI (r = 0.8237) and NDBSI (r = 0.1916). There was a strong positive significant correlation between NDVI and precipitation before and after the introduction of various NbS (r = 0.9692, p > 0.05). Therefore, vegetation health and NbS controlled the climatic conditions of the basin. This study prioritises the adoption of NbS for climate change mitigation. The study findings can be used as a reference for measuring the effectiveness of NbS in mitigating climate change in the world.