This inventory of traffic areas in the city of Brunswick, Germany, is based on image sequences acquired during six flight campaigns at different times of the day and year in 2019 and 2020. Each aerial image is segmented by a neural network into the classes (1) Parking area, (2) Road, and (3) Access way, with the latter two classes differing in terms of their primary transportation function (mobility versus access). The individual segmentations are subsequently merged, since in addition to dedicated parking areas, those traffic areas that are regularly used for parking a motorized vehicle (e.g., at the curbside) are also to be classified as such. Furthermore, the multitemporal fusion enhances the robustness and completeness of the traffic area map (TAM). Potential applications include: urban planning, traffic modeling, and parking management. For more information about the project, the reader is referred to: https://elib.dlr.de/147964/1/Hellekes_et_al_2021_Assimilation_parking_space_ITS_World_Congress.pdf
UrMo Digital - Traffic Area Map (TAM) - Brunswick, Germany
2022
Research Data
Electronic Resource
English
Preempting Fire Engines at Traffic Signals in Brunswick, Germany, Using ITS-G5
Springer Verlag | 2022
|Farm tractor constructed by H. Bussing, Brunswick, Germany
Engineering Index Backfile | 1921
Floodlighting of historic monuments in Brunswick, West Germany
Engineering Index Backfile | 1962
|GWLB - Gottfried Wilhelm Leibniz Bibliothek | 1945
|Brunswick Airpark Airport, Brunswick, Georgia
NTIS | 1973