How can multi-source heterogeneous data contribute to assessing urban transportation carrying capacity?

摘要

? 2023Urban transportation carrying capacity (UTCC) plays a crucial role in sustainable urban development during rapid urbanisation. With the booming of big-data technologies, diverse multi-source heterogeneous data, including point of interest data, nighttime light data and congestion performance data, have been employed extensively to evaluate transportation performance. However, limited research has explored UTCC using such diverse data sources. Therefore, this study developed a multi-source heterogeneous data-based (MHDB) model by incorporating 12 types of research data to assess UTCC performance across different transportation analysis zones (TAZs) within a given city. A case demonstration of the proposed method is conducted using data collected from 144 TAZs in Chongqing City for 2021. The results demonstrate that 1) UTCC performance in these 144 TAZs exhibits a distinct spatial pattern characterised as ‘central region > eastern region > western region’, 2) TAZs in central areas of Chongqing present a “Over-Utilization” UTCC performance level, which is considered that urban policy-makers should take effective measures to alleviate traffic pressure. 3) TAZs with Low-Utilization UTCC performance level are located in the western and eastern regions of Chongqing. Tailor-made policy measures should be designed and implemented in these TAZs to better utilize existing transportation infrastructures. The demonstration confirms that the MHDB model used can provide an effective tool for comparing UTCC performance in different TAZs within a city.