PURPOSES : We propose a framework to evaluate the reliability of integrating homogeneous or heterogeneous mobility data to produce the various data required for greenhouse gas emission estimation. METHODS : The mobility data used in the framework were collected at a fixed time from a specific point and were based on raster data. In general, the traffic volume for all traffic measurement points over 24 h can be considered raster data. In the future, the proposed framework can be applied to specific road points or road sections, depending on the presence or absence of raster data. RESULTS : The activity data required to calculate greenhouse gas emissions were derived from the mobility data analysis. With recent developments in information, communication, and artificial intelligence technologies, mobility data collected from different sources with the same collection purpose can be integrated to increase the reliability and accuracy of previously unknown or inaccurate information. CONCLUSIONS : This study will help assess the reliability of mobility data fusion as it is collected on the road, and will ultimately lead to more accurate estimates of greenhouse gas emissions.

PURPOSES : This study proposes an index for analyzing mobility based on smartcard and taxi data to evaluate imbalances in public transit. METHODS : The proposed mobility index is calculated based on the difference between the mobility indexes of public transit and taxis using the variables of the in-vehicle time, waiting time, and driving ratio. For a more detailed analysis, the distances are divided into short distances, medium distances, and long distances. RESULTS : Public transit mobility indexes are generally evenly distributed, but the taxi mobility indexes are located in the largest legend. When comparing the respective mobilities of public transit and taxis, many areas with a high mobility of taxis (similar to the distribution) exist, especially in the outskirts such as Dobong-gu, Nowon-gu, Gangdong-gu, Guro-gu, Geumcheon-gu, and Eunpyeong-gu. On average, the mobility of public transit according to the distance is smaller in a short distance and higher in a long distance. CONCLUSIONS : The results demonstrate the use of the proposed index for analyzing the basic statuses of complementary indexes for evaluating public transit imbalances. In the future, more detailed results (including socioeconomic variables corresponding to the grid areas) should be studied to identify the impacts of the mobility index.