Long-distance travel, respectively interurban travel, makes up a considerable share in transport performance: nearly half of the passenger transport performance is accounted by trips of more than 100 km. Furthermore passenger long-distance travel is achieving considerable growth while other segments of transport rather remain static. Above that passenger long-distance travel is in the focus of politics and research against the background of energy and climate objectives and due to a dynamic supply development. Despite the relevance of this transport segment, an appropriate depiction of long-distance travel behavior within the framework of a multimodal model is missing in Germany and most other countries. One fundamental reason for that is the heterogeneous data situation, resulting from the fact that the topic is of interest by different institutions that generate relevant data. By means of different survey methods the data on long-distance travel behavior is collected, but mostly with deviant focuses or different objectives. The question arises, whether it is possible to generate a consistent and exclusive data set from the different data sources, which can build the basis for long-distance travel model. The aim is, to apply and enhance statistic and econometric methods, to build a model respectively an instrument for data fusion of long-distance travel data. An essential basic work hereby is to clearly differentiate and define the segment of long-distance travel. In the next step the today available data sources are listed and contrasted with each other. Finally I provide a methodological framework on how the available data can enhance the current data basis for long-distance travel behavior. The work intends to contribute to presently existing fundamental challenges in modelling long-distance passenger travel through combining available data in a creative and innovative manner.