This study examines the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023, using high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments and climate variables from CHIRPS and ERA5 datasets. The analysis employs Google Earth Engine (GEE) for efficient processing and statistical methodologies including linear regression, Mann–Kendall trend tests, Sen’s slope estimator, partial correlation, and cross-wavelet transform analyses. Key findings include significant spatial and temporal variations in NDVI, with an annual increase of 0.00197 per year (p < 0.0001) and an increase in precipitation of 0.4801 mm/year (p = 0.0016). Temperature decreased slightly at −0.01011 °C/year (p < 0.05), and solar radiation decreased by −0.27526 W/m²/year (p < 0.05). Cross-wavelet transform analysis revealed significant coherence between NDVI and climatic factors, highlighting periods of synchronized fluctuations and distinct lagged relationships. Precipitation was identified as a primary driver of vegetation growth, with vegetation health most responsive during the monsoon season. The study provides crucial insights for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in Pakistan.This study examines the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023, using high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments and climate variables from CHIRPS and ERA5 datasets. The analysis employs Google Earth Engine (GEE) for efficient processing and statistical methodologies including linear regression, Mann–Kendall trend tests, Sen’s slope estimator, partial correlation, and cross-wavelet transform analyses. Key findings include significant spatial and temporal variations in NDVI, with an annual increase of 0.00197 per year (p < 0.0001) and an increase in precipitation of 0.4801 mm/year (p = 0.0016). Temperature decreased slightly at −0.01011 °C/year (p < 0.05), and solar radiation decreased by −0.27526 W/m²/year (p < 0.05). Cross-wavelet transform analysis revealed significant coherence between NDVI and climatic factors, highlighting periods of synchronized fluctuations and distinct lagged relationships. Precipitation was identified as a primary driver of vegetation growth, with vegetation health most responsive during the monsoon season. The study provides crucial insights for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in Pakistan.