The goal of “double carbon” puts forward higher requirements for the control of transport carbon emissions, and the exploration of transport carbon emission modelling driven by big data is an important attempt to reduce carbon accurately. Based on the land Vehicle Miles Traveled data (VMT) and the sea Automatic Identification System (AIS) data, this study establishes a refined, high-resolution carbon emission measurement model that incorporates the use of motor vehicles and ships from a bottom-up approach and analyzes the spatial distribution characteristics of land and sea transport carbon emissions in Tianjin using geospatial analysis. The results of the study show that (1) the transportation carbon emissions in Tianjin mainly come from land road traffic, with small passenger cars contributing the most to the emissions; (2) high carbon emission zones are concentrated in economically developed, densely populated, and high road network density areas, such as the urban center Binhai New Area, and the marine functional zone of Tianjin; (3) carbon emission values are generally higher in the segments where ports, airports, and interchanges are connected. The transportation carbon emission measurement model developed in this study provides practical, replicable, and scalable insights for other coastal cities.