Impact of Roads on Vegetation Dynamics in the Semi-Arid Baringo County, Kenya

The semi-arid lowlands of Baringo County, Kenya provide numerous ecosystem services to pastoral and agro-pastoral communities. However, these services have been significantly impacted by gradual changes in land cover, climate change, shrub encroachment, and invasion of grasslands by species like Prosopis juliflora. This study aimed to investigate how changes in land cover and roads affect vegetation dynamics between 2000 and 2024. This period was chosen due to the availability of consistent satellite-derived Normalized Difference Vegetation Index (NDVI) data for time series analysis. Using the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), we analyzed NDVI data for five land cover classes, namely: natural shrubland, artificial grassland, forest, irrigated land, and Prosopis-infested areas. The impact of roads was assessed by calculating the instantaneous energy of high-frequency Intrinsic Mode Functions (IMFs) at buffer distances of 100, 250, 500, 1000, and 1500 meters from the roads in natural ecosystems. The results revealed diverse NDVI trends for different land cover classes. Forest exhibited mixed trends, with some pixels showing positive trends while others remained stable over time. Irrigated agricultural land indicated an increase in trend until 2017, after which it plateaued. Shrubland and artificial grassland maintained steady NDVI values with modest positive trends. Prosopis-infested areas exhibited a positive trend from 2000 to 2017, followed by a decline, likely linked to community-led invasion management efforts. The positive NDVI trends observed in forests and natural shrublands may be attributed to an increased invasion of Prosopis. Seasonal variations were associated with climatic conditions. Statistical analysis indicated that distance from the road had a significant difference on instantaneous energy but with a small effect size. These findings contribute to understanding how infrastructure and land use changes influence vegetation, providing valuable insights for sustainable management of semi-arid rural landscapes.