Capturing Rural–Urban Region (RUR) Assessment through Integrated Conceptual and Geo–Big Data Approaches: A Case Study from Penajam Paser Utara, Neighboring Indonesia’s New Capital (IKN)

The increasingly dynamic development of rural-urban regions (RUR) necessitates the advancement of classification methods for RUR areas. Traditional boundaries, primarily based on land use patterns and population distribution, are no longer sufficient to capture the complex socio-economic dynamics and spatial integration that characterise contemporary RUR landscapes. Penajam Paser Utara (PPU), which directly borders Indonesia’s Nusantara Capital City (IKN), exhibits a high degree of regional dynamism, making it an exemplary case for the application of typological assessment approaches. This research aims not only to redefine RUR by integrating the most recent theories and advancements in data acquisition technologies but also to identify the typology of RUR in PPU Regency. The spatial method of Kernel Density was applied to evaluate critical variables, including activity accumulation, land-use characteristics, connectivity, government services, and population size and density using integrated field data and geospatial big data (e.g., satellite imagery, mobile data). Despite evolving RUR assessment methods, unresolved debates persist regarding the selection of optimal indicators, particularly the role of connectivity in delineating urban boundaries. The findings not only successfully provide new evidence for the application of advanced kernel density models that incorporate multiple data sources to represent key land use and connectivity features, but they also reveal that the study area was mostly rural, with limited urban areas. Penajam and Babulu had larger peri-urban areas, suggesting future urbanization potential. Waru and Sepaku lacked urban areas, confirming their rural nature. These results underline the critical importance of RUR delineation for spatial analysis in PPU and highlight the need for further research on sustainable urban-rural linkages to promote balanced development. This research contributes novel insights into the assessment and classification of RURs, particularly in high-dynamic regions.