Understanding the spatiotemporal dynamics of croplands is crucial for guiding agricultural transformation, food security, and sustainable land use in Africa. This study employs 30 m resolution land cover data and multi-source datasets to examine the spatiotemporal changes in rainfed and irrigated cropland and their driving factors in Tanzania from 1990 to 2020 through multiple GIS spatial analysis methods. The results indicate a net increase in Tanzania’s total cropland area, primarily driven by the expansion of irrigated cropland that has offset the volatile decline of rainfed cropland. From 1990 to 2000, rainfed cropland showed intense bidirectional conversion with shrubland and forest; thereafter, the scale of this conversion continued to decrease. In contrast, irrigated cropland expansion exhibited phased fluctuations. Spatially, rainfed cropland dominates the central, lake, and western zones, while irrigated cropland is predominantly concentrated in the western and southern highland. Hotspots of rainfed cropland shifted from extensive expansion in the central and western zones during the 1990s to localized growth in mountainous areas by the 2010s. Concurrently, irrigated cropland hotspots evolved from a lakeside-concentrated pattern to contiguous development in the central and western zones. Both cropland types exhibit a northwest–southeast spatial orientation. The center of rainfed cropland shifted northwest before moving southeast, while that of irrigated cropland migrated southeastward and then stabilized. Rainfall is a key determinant of rainfed cropland distribution, whereas river network and road network density exert a growing influence on irrigated cropland.

As China’s urban–rural integrated development strategy advances, traditional urban–rural boundaries are undergoing rapid restructuring. However, it remains unclear whether these boundaries are becoming distinct through factor flow or blurring due to urban–rural functional coupling. To address this, this study examines the dynamic evolution of boundaries across three core dimensions—population, land, and function—to evaluate the efficacy of integration. We employ the Land Continuity Index, POI Diversity Index, and Gaussian Smoothing Index to characterize transitions in land use structure, spatial functional complexity, and population gradients, respectively. Additionally, a comprehensive Urban–Rural Fuzziness Index (URFI) is developed to quantify boundary blurring trends. Results indicate that Zhengzhou’s urban–rural boundaries exhibit a sustained weakening trend. Notably, changes in functional and population dimensions significantly outpace the land dimension, identifying functional urbanization and population mobility as the primary drivers of this blurring. Consequently, the URFI serves as a robust indicator of integration effectiveness. Overall, boundary blurring is not merely an external manifestation of urban expansion but a profound outcome of factor reorganization, spatial optimization, and the reshaping of urban–rural relationships. This study provides a novel quantitative tool for assessing policy effectiveness, offering both theoretical insights and practical implications for understanding urban–rural integrated development.