Human‐wildlife conflict (HWC) is increasingly associated with rapid land‐use and land‐cover (LULC) changes and broader environmental shifts. While previous studies have focused on causal factors and coexistence strategies, the spatiotemporal dynamics of human-wildlife interactions under shifting LULC remain poorly quantified. This study examines the spatiotemporal patterns of LULC and their association with HWC around the Hluhluwe‐iMfolozi Park in South Africa. The detailed landscape dynamics were captured using Sentinel‐2 imagery at 5‐year intervals (2015, 2020, and 2025) with machine‐ and deep‐learning classification algorithms. Among the evaluated algorithms, the Two‐dimensional Convolutional Neural Network outperformed the others, achieving an average overall accuracy of 99.92% and a kappa coefficient of 0.9991. The findings show substantial LULC changes during the study, including a notable decrease in cultivated land, changes in vegetation structure, and an increase in built-up areas. Shrubland grew significantly by 2025, suggesting continuous landscape change, while woodland increased between 2015 and 2020. Anthropogenic activities and vegetation gains dominated earlier transitions, while natural vegetation transitions drove later changes. Outside protected regions, these trends were more pronounced, indicating greater anthropogenic pressure. Integration of LULC transitions with HWC data revealed that conflict events were increasingly linked to grassland, woodland, and transitional landscapes and were concentrated along protected area boundaries. Hotspots were closely associated with regions undergoing active land-cover change, and the frequency and spatial extent of HWC increased over time. These results demonstrate how landscape dynamics spatially overlap with human‐wildlife interactions and emphasize the need for sophisticated geospatial technologies to pinpoint conflict hotspots and guide targeted conservation and mitigation efforts.