In order to stop climate change, it is inevitable to transition to more environmental-friendly ways of transportation, such as cycling. An important criterion for selecting the bicycle as a modality is the distance to the destination. An increase in travel distance coincides with a decrease in modal share of bicycles compared to alternative modalities. Literature does not explain why cycling is preferred for certain distances and not for others, except for some practical reasons. This thesis investigates the built environment in relation to cycling distance. Literature indicates the built environment as being important for destination choice, mode choice and route choice. Moreover, literature also indicates a relationship between cycling distance and these decision choices. As urbanization of the built environment increases, more destinations are within reach and this tends to reduce travel distance. At the same time, network friction reduces due to increasing network density. Finally, preferences to cycle through or avoid certain characteristics of the built environment may result in detours, which increase travel distance. People’s decisions on travel destination, transportation mode and route appear to be crucial for choosing the bicycle as mode of transport. Humans make these decisions simultaneously, but in this thesis, it is assumed that it is done in the order: destination, mode, and route. By making this assumption, it is possible to say that (a) destination choice is connected to Euclidean distance, (b) mode choice is connected to network friction, and (c) route choice is connected to behavioural detour. The 7D’s framework of Ewing & Cevero (2010) has been used to quantify the built environment. It will turn out that only the first three D’s (Design, Density and Diversity) are influencing cycling distance. The choices for destination, mode and route choice are also influenced by the following elements: network density, cycle paths, green environments, smooth surface, built environment density and the mixture of functions in the built environment. This research has been conducted with bicycle trip data within the municipalities of Amsterdam, Amstelveen, Diemen and Ouder-Amstel. Those municipalities offer a fitting case study, since the ‘Greater Amsterdam’ has a varied built environment and has a need to reduce car traffic significantly. In this thesis, the relation of the elements with cycling distance are statistically tested with a multiple linear regression analysis. In order to do so, elements have to been quantified and combined with the bicycle trips. Explanatory models are developed to explain cycling distance, Euclidean distance, and detour distance with the elements of the built environment. The models constructed in this thesis show that the elements green environments, waterbodies, smooth surface material, and cycle paths have a positive increasing impact on cycling distance, while network density and built environment have a negative decreasing impact. No clear impact on travel distance is found for the element mixture of functions. This thesis also show that the built environment is more important for determining the Euclidean distance than its importance detour distance. The results from this thesis confirm the relationship between built environment and cycling distance. To be specific, the results show that the built environment density is most important for Euclidean distance and therefore destination choice. Green environments and waterbodies are incentive elements of the built environment to overcome the distance added by the network friction. The two elements can also affect the cycling distance due to the choice of behavioural detour. This shows that bicycle use for longer distances can be stimulated by adding more green and potential waterbodies in the built environment.